From 3e64f648d9d9eabe86acde3299fbd7b13421ebe8 Mon Sep 17 00:00:00 2001 From: talhaiqbal-10xe Date: Fri, 23 Aug 2024 18:13:01 +0500 Subject: [PATCH] Squashed commit of the following: MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit commit 27345a8ba41bdd15f57b3eba89895ca5b9ea4f3d Author: sohaibimran-10xe <87118558+sohaibimran-10xe@users.noreply.github.com> Date: Thu Aug 22 19:38:31 2024 +0500 Fixed 2A internal crop, automated testing, osd, yuv rev, ycbcr matrix… (#17) * Fixed 2A internal crop, automated testing, osd, yuv rev, ycbcr matrix fixed * fix osd configs and linting * fixed linting --- .github/pull_request_template.md | 12 + .pylintrc | 5 +- README.md | 16 +- config/configs.yml | 30 +- docs/UserGuide.md | 2 - docs/assets/10xLogo.txt | 64 +++++ .../infinite-isp-architecture-initial.png | Bin 81307 -> 248797 bytes .../Indoor1_2592x1536_10bit_GRBG-configs.yml | 14 +- .../Outdoor1_2592x1536_10bit_GRBG-configs.yml | 14 +- .../Outdoor2_2592x1536_10bit_GRBG-configs.yml | 14 +- .../Outdoor3_2592x1536_10bit_GRBG-configs.yml | 14 +- .../Outdoor4_2592x1536_10bit_GRBG-configs.yml | 14 +- infinite_isp.py | 175 ++++++++++-- isp_pipeline.py | 4 - isp_pipeline_multiple_images.py | 10 +- modules/auto_exposure.py | 44 +-- modules/auto_white_balance.py | 39 +-- modules/bayer_noise_reduction.py | 23 +- modules/black_level_correction.py | 8 +- modules/color_correction_matrix.py | 6 +- modules/color_space_conversion.py | 10 +- modules/crop.py | 31 +- modules/dead_pixel_correction.py | 7 +- modules/demosaic.py | 6 +- modules/digital_gain.py | 8 +- modules/gamma_correction.py | 7 +- modules/invalid_region_crop.py | 15 +- modules/noise_reduction_2d.py | 7 +- modules/oecf.py | 7 +- modules/on_screen_display.py | 194 +++++++++++++ modules/rgb_conversion.py | 12 +- modules/scale.py | 14 +- modules/white_balance.py | 7 +- modules/yuv_conv_format.py | 9 +- test_vector_generation/README.md | 78 ------ test_vector_generation/automate_execution.py | 220 --------------- test_vector_generation/tv_config.yml | 47 ---- test_vector_generation/tv_utils.py | 264 ------------------ tests/test_data/.gitkeep | 0 .../Indoor1_2592x1536_10bit_GRBG-configs.yml | 168 +++++++++++ .../Indoor1_2592x1536_10bit_GRBG.raw | Bin 0 -> 7962624 bytes tests/test_data/ReadMe.md | 5 + tests/test_data/default_configs.yml | 164 +++++++++++ tests/test_pipleine_output.py | 82 ++++++ util/config_utils.py | 1 - util/utils.py | 230 ++++++++------- 46 files changed, 1164 insertions(+), 937 deletions(-) create mode 100644 .github/pull_request_template.md create mode 100644 docs/assets/10xLogo.txt create mode 100644 modules/on_screen_display.py delete mode 100644 test_vector_generation/README.md delete mode 100644 test_vector_generation/automate_execution.py delete mode 100644 test_vector_generation/tv_config.yml delete mode 100644 test_vector_generation/tv_utils.py create mode 100644 tests/test_data/.gitkeep create mode 100644 tests/test_data/Indoor1_2592x1536_10bit_GRBG-configs.yml create mode 100644 tests/test_data/Indoor1_2592x1536_10bit_GRBG.raw create mode 100644 tests/test_data/ReadMe.md create mode 100644 tests/test_data/default_configs.yml create mode 100644 tests/test_pipleine_output.py diff --git a/.github/pull_request_template.md b/.github/pull_request_template.md new file mode 100644 index 0000000..7ade647 --- /dev/null +++ b/.github/pull_request_template.md @@ -0,0 +1,12 @@ +### Pull request checklist: +- [ ] Issue created + +**ReadMe** +- [ ] Block Diagram +- [ ] Results +- [ ] UserGuide + +**Documentation** +- [ ] Block Diagram +- [ ] Module description +- [ ] Results diff --git a/.pylintrc b/.pylintrc index 71d56e5..1c713b3 100644 --- a/.pylintrc +++ b/.pylintrc @@ -1,5 +1,5 @@ [MESSAGES CONTROL] -disable=unsubscriptable-object,E1136, E1137, R,E0401, C3001, E1121, E0001, C0209, W1514, C0302, W0621, W0201, C0413 +disable=unsubscriptable-object,E1136, E1137, R,E0401, C3001, E1121, E0001, C0209, W1514, C0302, W0621, W0201, C0413, E0606 # E0401: Unable to import 'util.utils' (import-error) # C3001: Lambda expression assigned to a variable. @@ -8,4 +8,5 @@ disable=unsubscriptable-object,E1136, E1137, R,E0401, C3001, E1121, E0001, C0209 # C0302: Too many lines in module (too-many-lines) # W0621: Redefining name 'x' from outer scope (redefined-outer-name) # W0201: Attribute 'x' defined outside __init__ (attribute-defined-outside-init) -# C0413: Import "import infinite_isp" should be placed at the top of the module (wrong-import-position) \ No newline at end of file +# C0413: Import "import infinite_isp" should be placed at the top of the module (wrong-import-position) +# E0606: Possibly using variable 'r_channel' before assignment (possibly-used-before-assignment) diff --git a/README.md b/README.md index 16cf526..7dc8be8 100644 --- a/README.md +++ b/README.md @@ -32,17 +32,15 @@ ISP pipeline for `InfiniteISP_ReferenceModel v1.0` 1. **RTL-friendly Code**: The model provides a Python implementation of camera pipeline modules that can be directly translated to RTL, with optimizations such as lookup tables, custom approximations, and integer calculations. -2. **Test Vector Generation**: The project includes automated scripts for generating test vectors for individual as well as multiple modules, simplifying the testing process. +2. **Dataset Processing**: The model facilitates execution for multiple images with different or same configuration files. -3. **Dataset Processing**: The model facilitates execution for multiple images with different or same configuration files. - -4. **Video Processing**: The model also features a video processing script that allows for sequential frame processing, with operational 3A Statistics data flowing between frames. +3. **Video Processing**: The model also features a video processing script that allows for sequential frame processing, with operational 3A Statistics data flowing between frames. ## Objectives -The primary objective of Infinite-ISP_ReferenceModel is to create a open source Python-based Model that streamlines the process of implementing camera pipeline modules into RTL-friendly implementations. This enables seamless integration with hardware designs and simplifies the development of efficient image processing systems. By providing optimized algorithms, test vector generation, and video processing capabilities, the model aims to be an invaluable tool for developers working on image processing projects and RTL implementations. +The primary objective of Infinite-ISP_ReferenceModel is to create a open source Python-based Model that streamlines the process of implementing camera pipeline modules into RTL-friendly implementations. This enables seamless integration with hardware designs and simplifies the development of efficient image processing systems. By providing optimized algorithms, and video processing capabilities, the model aims to be an invaluable tool for developers working on image processing projects and RTL implementations. # Features List @@ -67,6 +65,7 @@ The table below provides a feature list of the model. The version `1.0` of the m | Noise Reduction | [Non-local means filter](https://www.ipol.im/pub/art/2011/bcm_nlm/article.pdf)
- Implements intensity level difference through a LUT| | RGB Conversion | Converts YCbCr digital image to RGB| | Invalid Region Crop | Crops image to a fixed size| +|On Screen Display | Adds 10x Logo on top left corner | | Scale | Nearest Neighbor
- Integer Scaling | | YUV Format | YUV
- 444
- 422 | @@ -90,7 +89,7 @@ git clone https://github.com/10xEngineersTech/Infinite-ISP_ReferenceModel ```shell pip install -r requirements.txt ``` -3. Run [isp_pipeline.py](isp+pipeline.py) +3. Run [isp_pipeline.py](isp_pipeline.py) ```shell python isp_pipeline.py ``` @@ -129,7 +128,7 @@ DATASET_PATH = './in_frames/normal/data' ```shell git submodule add -git submodule update –-init –-recursive +git submodule update --init --recursive ``` @@ -142,9 +141,6 @@ DATASET_PATH = './in_frames/normal/' 5. Run `isp_pipeline_dataset.py` or `video_processing.py` 6. The processed images are saved in [out_frames](out_frames/) folder. -## Test Vector Generation -Please refer to the provided [instructions](test_vector_generation/README.md) for generating test vectors for multiple images, considering individual or multiple modules as the Device Under Test (DUT). - ## Contributing Please read the [Contribution Guidelines](docs/CONTRIBUTIONS.md) before making a Pull Request diff --git a/config/configs.yml b/config/configs.yml index 5596481..811a1cd 100644 --- a/config/configs.yml +++ b/config/configs.yml @@ -3,8 +3,6 @@ platform: disable_progress_bar: false leave_pbar_string: false save_lut: false - generate_tv: false - rev_yuv_channels: false save_format: npy # png # npy # both render_3a: false @@ -19,8 +17,8 @@ sensor_info: crop: is_enable: false is_debug: false - new_width: 1280 - new_height: 720 + new_width: 2592 + new_height: 1536 is_save: false dead_pixel_correction: @@ -44,7 +42,7 @@ black_level_correction: is_save: false oecf: - is_enable: false + is_enable: true # Make sure the LUT has the right bit range i.e. if image is of 10 bit LUT should be from [0 - (2^10)-1] # LUT here does nothing to the sensor response i.e. a value of 800 maps to 800 and 2000 maps to 2000 r_lut: 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@@ -65,7 +63,7 @@ digital_gain: is_save: false bayer_noise_reduction: - is_enable: false + is_enable: true filter_window: 9 r_std_dev_s: 1 r_std_dev_r: 0.1 @@ -81,7 +79,6 @@ auto_white_balance: stats_window_offset: [16, 16, 16, 16] underexposed_percentage: 5 overexposed_percentage: 5 - is_save: false white_balance: is_enable: true @@ -118,14 +115,13 @@ auto_exposure: stats_window_offset: [4, 4, 4, 4] center_illuminance: 90 histogram_skewness: 0.9 - is_save: false color_space_conversion: conv_standard: 2 is_save: false 2d_noise_reduction: - is_enable: false + is_enable: true window_size: 9 wts: 5 is_save: false @@ -138,11 +134,23 @@ invalid_region_crop: # 1: 1920x1080, 2: 1920x1440 is_enable: false crop_to_size: 2 - height_start_idx: 5 - width_start_idx: 6 + height_start_idx: 40 + width_start_idx: 40 is_debug: true is_save: false +on_screen_display: + is_enable: true + is_debug: false + height: 64 + width: 128 + x_offset: 50 + y_offset: 50 + fg_color: [0, 90, 160] + bg_color: [255, 255, 255] + alpha: 50 + is_save: false + scale: is_enable: false is_debug: true diff --git a/docs/UserGuide.md b/docs/UserGuide.md index b18b679..dd42f11 100644 --- a/docs/UserGuide.md +++ b/docs/UserGuide.md @@ -14,8 +14,6 @@ Platform contains configuration parameters that are not part of the ISP pipeline | disable_progress_bar| Enables or disables the progress bar for time taking modules| | leave_pbar_string | Hides or unhides the progress bar upon completion | | save_lut | Flag to store LUT files for 2DNR and BNR | -| generate_tv | Indicates that ISP pipeline is running through [automate_execution.py](../test_vector_generation/automate_execution.py) for debugging instead of [isp_pipeline.py](../isp_pipeline.py)| -|rev_yuv_channels| Use for debugging - Generate YUV test vectors with reversed channels (VUY)| |save_format| Use for Debugging - Set module output format
- `npy`
- `png`
- `both` | |rendered_3a| Returns 3a rendered final image with awb gains and correct exposure| diff --git a/docs/assets/10xLogo.txt b/docs/assets/10xLogo.txt new file mode 100644 index 0000000..e0787fe --- /dev/null +++ b/docs/assets/10xLogo.txt @@ -0,0 +1,64 @@ +0x0, 0x0, 0x0, 0xc, +0x0, 0x0, 0x0, 0x18, +0x0, 0x1fe, 0x0, 0x70, +0x0, 0x3fe, 0x0, 0xe0, +0x1f, 0xfc0003fe, 0x0, 0x3c0, +0xff, 0xfc0007ff, 0x0, 0x7c0, +0x3ff, 0xfc003fff, 0xe0000000, 0x1f80, +0xfff, 0xfc01ffff, 0xfc700000, 0x3f00, +0x7fff, 0xf8e7ffff, 0xfffc0000, 0x7e00, +0x1ffff, 0xf8fff800, 0xfffe0000, 0xfc00, +0x7ffff, 0xf87fc000, 0x1fff0000, 0x1f800, +0x1fffff, 0xf8ff0000, 0x7ff0000, 0x3f800, +0x1fffff, 0xf87c1fff, 0x81fe0000, 0x7f000, +0x1fffff, 0xf0387fff, 0xe0fe0000, 0xfe000, +0x1fffff, 0xf001ffff, 0xf87e0000, 0x1fc000, +0x3ffcff, 0xf007ffff, 0xfe3e0000, 0x3f8000, +0x3fe0ff, 0xf00fffff, 0xff1f0000, 0x3f0000, +0x3f81ff, 0xf01fffff, 0xff9f00f0, 0x67e0000, +0x3c01ff, 0xe03fffff, 0xff8f87fc, 0xcfc0000, +0x3001ff, 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(2000). CRC Standard Probability and Statistics Tables and Formulae. Chapman & Hall: New York. 2000. Section 2.2.24.1 """ - + img_orig = np.copy(img) # First subtract central luminance to calculate skewness around it img = img.astype(np.float64) - self.center_illuminance @@ -120,18 +122,28 @@ def get_luminance_histogram_skewness(self, img): if self.is_debug: print(" - AE - Actual_Skewness = ", skewness) - sign_m3 = np.sign(m_3) - - m_2 = m_2 >> 6 - m_3 = abs(m_3) >> 9 - - approx_sqrt_m_2 = approx_sqrt(m_2) - new_skewness, _ = get_approximate(m_3 / (m_2 * approx_sqrt_m_2), 16, 8) - new_skewness = sign_m3 * new_skewness + # all integer calc + img_int = img_orig.astype(np.int64) - self.center_illuminance + img_int_size = img_int.size + m_2_int = np.sum(np.power(img_int, 2)).astype(np.int64) + m_3_int = np.sum(np.power(img_int, 3)).astype(np.int64) + m_2_int = np.int64(m_2_int / img_int_size) + m_3_int = np.int64(m_3_int / img_int_size) + sign_m3_int = np.sign(m_3_int) + # all integer calc + + m_2_int = m_2_int >> 6 + m_3_int = abs(m_3_int) >> 9 + + approx_sqrt_m_2_int = approx_sqrt(m_2_int, 13) + new_skewness_int = ( + np.int64((m_3_int * 256) / (m_2_int * approx_sqrt_m_2_int)) / 256 + ) + new_skewness_int = sign_m3_int * new_skewness_int if self.is_debug: - print(" - AE - Approx_Skewness = ", new_skewness) + print(" - AE - Approx_Skewness Int = ", new_skewness_int) - return new_skewness + return new_skewness_int def execute(self): """ @@ -143,6 +155,6 @@ def execute(self): return None else: start = time.time() - ae_feedback = self.get_exposure_feedback() + ae_feedback, _ = self.get_exposure_feedback() print(f" Execution time: {time.time()-start:.3f}s") return ae_feedback diff --git a/modules/auto_white_balance.py b/modules/auto_white_balance.py index 1f0fb95..beb68b4 100644 --- a/modules/auto_white_balance.py +++ b/modules/auto_white_balance.py @@ -16,7 +16,6 @@ class AutoWhiteBalance: """ def __init__(self, raw, sensor_info, parm_awb): - self.raw = raw self.sensor_info = sensor_info @@ -48,20 +47,23 @@ def determine_white_balance_gain(self): self.raw = self.apply_window_offset_crop() - max_pixel_value = 2**self.bit_depth - appox_percenntage, _ = get_approximate(max_pixel_value / 100, 16, 8) - # Removed overexposed and underexposed pixels for wb gain calculation - overexposed_limit = ( - max_pixel_value - (self.overexposed_percentage) * appox_percenntage + max_pixel_value = (2**self.bit_depth) - 1 + # appox_percenntage, _ = get_approximate(max_pixel_value / 100, 16, 8) + delta_overexposed = np.uint16( + max_pixel_value * (self.overexposed_percentage / 100) + ) + delta_underexposed = np.uint16( + max_pixel_value * (self.underexposed_percentage / 100) ) - underexposed_limit = (self.underexposed_percentage) * appox_percenntage + # Removed overexposed and underexposed pixels for wb gain calculation + overexposed_limit = np.uint16(max_pixel_value - delta_overexposed) + underexposed_limit = np.uint16(delta_underexposed) if self.is_debug: print(" - AWB - Underexposed Pixel Limit = ", underexposed_limit) print(" - AWB - Overexposed Pixel Limit = ", overexposed_limit) if self.bayer == "rggb": - r_channel = self.raw[0::2, 0::2] gr_channel = self.raw[0::2, 1::2] gb_channel = self.raw[1::2, 0::2] @@ -90,8 +92,8 @@ def determine_white_balance_gain(self): bad_pixels = np.sum( np.where( - (bayer_channels < underexposed_limit) - | (bayer_channels > overexposed_limit), + (bayer_channels <= underexposed_limit) + | (bayer_channels >= overexposed_limit), 1, 0, ), @@ -100,20 +102,22 @@ def determine_white_balance_gain(self): self.flatten_raw = bayer_channels[bad_pixels == 0] # print(self.flatten_raw.shape) - channels_mean = np.mean(self.flatten_raw, axis=0) - # print(channels_mean) + channels_sum = np.sum(self.flatten_raw, axis=0, dtype=np.uint64) + # print(channels_sum) - g_mean = np.mean(channels_mean[1:3], axis=0) + # g_sum = (gr_sum + gb_sum) / 2 + g_sum = np.mean(channels_sum[1:3], axis=0, dtype=np.uint64) + g_sum = g_sum * 256 - rgain = np.nan_to_num(g_mean / channels_mean[0]) - bgain = np.nan_to_num(g_mean / channels_mean[3]) + rgain = np.uint16(np.nan_to_num(np.uint16(g_sum / channels_sum[0]))) + bgain = np.uint16(np.nan_to_num(np.uint16(g_sum / channels_sum[3]))) # Check if r_gain and b_gain go out of bound rgain = 1 if rgain <= 0 else rgain bgain = 1 if bgain <= 0 else bgain - rgain_approx, rgain_approx_bin = get_approximate(rgain, 16, 8) - bgain_approx, bgain_approx_bin = get_approximate(bgain, 16, 8) + rgain_approx, rgain_approx_bin = get_approximate(rgain / 256, 16, 8) + bgain_approx, bgain_approx_bin = get_approximate(bgain / 256, 16, 8) if self.is_debug: print(" - AWB Actual Gains: ") @@ -143,4 +147,5 @@ def execute(self): rgain, bgain = self.determine_white_balance_gain() print(f" Execution time: {time.time() - start:.3f}s") return np.array([rgain, bgain]) + return None diff --git a/modules/bayer_noise_reduction.py b/modules/bayer_noise_reduction.py index 467bb05..77305d1 100644 --- a/modules/bayer_noise_reduction.py +++ b/modules/bayer_noise_reduction.py @@ -12,7 +12,7 @@ import os import numpy as np from scipy import ndimage -from util.utils import create_coeff_file, save_output_array +from util.utils import create_coeff_file class BayerNoiseReduction: @@ -20,7 +20,7 @@ class BayerNoiseReduction: Noise Reduction in Bayer domain """ - def __init__(self, img, platform, sensor_info, parm_bnr): + def __init__(self, img, platform, sensor_info, parm_bnr, save_out_obj): self.img = img.copy() self.enable = parm_bnr["is_enable"] self.is_save = parm_bnr["is_save"] @@ -30,6 +30,7 @@ def __init__(self, img, platform, sensor_info, parm_bnr): self.is_progress = platform["disable_progress_bar"] self.is_leave = platform["leave_pbar_string"] self.save_lut = platform["save_lut"] + self.save_out_obj = save_out_obj def apply_bnr(self): """ @@ -60,12 +61,8 @@ def apply_bnr(self): # in_img = np.float32(in_img) / (2 ** bit_depth - 1) interp_g = np.zeros((height, width), dtype=np.int16) - in_img_r = np.zeros( - (int(height / 2), int(width / 2)), dtype=np.int16 - ) - in_img_b = np.zeros( - (int(height / 2), int(width / 2)), dtype=np.int16 - ) + in_img_r = np.zeros((int(height / 2), int(width / 2)), dtype=np.int16) + in_img_b = np.zeros((int(height / 2), int(width / 2)), dtype=np.int16) # convert bayer image into sub-images for filtering each colour ch in_img_raw = in_img.copy() @@ -124,12 +121,8 @@ def apply_bnr(self): kern_filt_g_at_b = np.clip(kern_filt_g_at_b, 0, 2**bit_depth - 1) interp_g = in_img.copy() - interp_g_at_r = np.zeros( - (int(height / 2), int(width / 2)), dtype=np.int16 - ) - interp_g_at_b = np.zeros( - (int(height / 2), int(width / 2)), dtype=np.int16 - ) + interp_g_at_r = np.zeros((int(height / 2), int(width / 2)), dtype=np.int16) + interp_g_at_b = np.zeros((int(height / 2), int(width / 2)), dtype=np.int16) if bayer_pattern == "rggb": # extract R and B location Green pixels to form interpG image @@ -453,7 +446,7 @@ def save(self): Function to save module output """ if self.is_save: - save_output_array( + self.save_out_obj.save_output_array( self.platform["in_file"], self.img, "Out_bayer_noise_reduction_", diff --git a/modules/black_level_correction.py b/modules/black_level_correction.py index 4f189e5..13a0a29 100644 --- a/modules/black_level_correction.py +++ b/modules/black_level_correction.py @@ -7,7 +7,7 @@ """ import time import numpy as np -from util.utils import get_approximate, save_output_array +from util.utils import get_approximate class BlackLevelCorrection: @@ -15,7 +15,7 @@ class BlackLevelCorrection: Black Level Correction """ - def __init__(self, img, platform, sensor_info, parm_blc): + def __init__(self, img, platform, sensor_info, parm_blc, save_out_obj): self.img = img.copy() self.enable = parm_blc["is_enable"] self.is_save = parm_blc["is_save"] @@ -24,6 +24,7 @@ def __init__(self, img, platform, sensor_info, parm_blc): self.platform = platform self.param_blc = parm_blc self.is_linearize = self.param_blc["is_linear"] + self.save_out_obj = save_out_obj def apply_blc_parameters(self): """ @@ -67,7 +68,6 @@ def apply_blc_parameters(self): print(" - BLC - B linearization factor (U16.14): " + b_linfact_bin) if bayer == "rggb": - # implementing this formula with condition # ((img - blc) / (sat_level-blc)) * bitRange @@ -128,7 +128,7 @@ def save(self): Function to save module output """ if self.is_save: - save_output_array( + self.save_out_obj.save_output_array( self.platform["in_file"], self.img, "Out_black_level_correction_", diff --git a/modules/color_correction_matrix.py b/modules/color_correction_matrix.py index ed13071..2d932c7 100644 --- a/modules/color_correction_matrix.py +++ b/modules/color_correction_matrix.py @@ -7,13 +7,12 @@ """ import time import numpy as np -from util.utils import save_output_array class ColorCorrectionMatrix: "Apply the color correction 3x3 matrix" - def __init__(self, img, platform, sensor_info, parm_ccm): + def __init__(self, img, platform, sensor_info, parm_ccm, save_out_obj): self.img = img.copy() self.enable = parm_ccm["is_enable"] self.is_save = parm_ccm["is_save"] @@ -22,6 +21,7 @@ def __init__(self, img, platform, sensor_info, parm_ccm): self.parm_ccm = parm_ccm self.bit_depth = sensor_info["bit_depth"] self.ccm_mat = None + self.save_out_obj = save_out_obj def apply_ccm(self): """ @@ -55,7 +55,7 @@ def save(self): Function to save module output """ if self.is_save: - save_output_array( + self.save_out_obj.save_output_array( self.platform["in_file"], self.img, "Out_color_correction_matrix_", diff --git a/modules/color_space_conversion.py b/modules/color_space_conversion.py index 0538226..f8fb951 100644 --- a/modules/color_space_conversion.py +++ b/modules/color_space_conversion.py @@ -15,15 +15,13 @@ import time import numpy as np -from util.utils import save_output_array_yuv - class ColorSpaceConversion: """ Color Space Conversion """ - def __init__(self, img, platform, sensor_info, parm_csc): + def __init__(self, img, platform, sensor_info, parm_csc, save_out_obj): self.img = img.copy() self.is_save = parm_csc["is_save"] self.platform = platform @@ -34,6 +32,7 @@ def __init__(self, img, platform, sensor_info, parm_csc): self.rgb2yuv_mat = None self.yuv_img = None self.yuv2rgb_mat = None + self.save_out_obj = save_out_obj def rgb_to_yuv_8bit(self): """ @@ -46,11 +45,10 @@ def rgb_to_yuv_8bit(self): [[47, 157, 16], [-26, -86, 112], [112, -102, -10]] ) else: - # for BT.601/407 # conversion metrix with 8bit integer co-efficients - m=8 self.rgb2yuv_mat = np.array( - [[77, 150, 29], [131, -110, -21], [-44, -87, 138]] + [[77, 150, 29], [-44, -87, 138], [131, -110, -21]] ) # make nx3 2d matrix of image @@ -92,7 +90,7 @@ def save(self): Function to save module output """ if self.is_save: - save_output_array_yuv( + self.save_out_obj.save_output_array_yuv( self.platform["in_file"], self.img, "Out_color_space_conversion_", diff --git a/modules/crop.py b/modules/crop.py index f1b8b7d..eea4b94 100644 --- a/modules/crop.py +++ b/modules/crop.py @@ -9,7 +9,6 @@ import time import re import numpy as np -from util.utils import save_output_array class Crop: @@ -24,16 +23,16 @@ class Crop: as the input image. """ - def __init__(self, img, platform, sensor_info, parm_cro): + def __init__(self, img, platform, sensor_info, parm_cro, save_out_obj): self.img = img.copy() self.sensor_info = sensor_info self.platform = platform self.parm_cro = parm_cro self.enable = parm_cro["is_enable"] self.is_save = parm_cro["is_save"] + self.save_out_obj = save_out_obj def crop(self, img, rows_to_crop=0, cols_to_crop=0): - """ Crop 2D array. Parameter: @@ -46,18 +45,18 @@ def crop(self, img, rows_to_crop=0, cols_to_crop=0): Output: cropped image """ - if rows_to_crop or cols_to_crop: - if rows_to_crop % 4 == 0 and cols_to_crop % 4 == 0: - img = img[ - rows_to_crop // 2 : -rows_to_crop // 2, - cols_to_crop // 2 : -cols_to_crop // 2, - ] - - else: - print( - " - Input/Output heights are not compatible." - " Bayer pattern will be disturbed if cropped!" - ) + if rows_to_crop != 0 and rows_to_crop % 4 == 0: + img = img[rows_to_crop // 2 : -rows_to_crop // 2, :] + + if cols_to_crop != 0 and cols_to_crop % 4 == 0: + img = img[:, cols_to_crop // 2 : -cols_to_crop // 2] + + if rows_to_crop % 4 != 0 or cols_to_crop % 4 != 0: + print( + " - Input/Output heights are not compatible. " + "Bayer pattern will be disturbed if cropped!\n" + f" - Image size: {img.shape} " + ) return img def apply_cropping(self): @@ -104,7 +103,7 @@ def save(self, filename_tag): self.platform["in_file"], ) if self.is_save: - save_output_array( + self.save_out_obj.save_output_array( self.platform["in_file"], self.img, filename_tag, diff --git a/modules/dead_pixel_correction.py b/modules/dead_pixel_correction.py index c2711a9..59b9293 100644 --- a/modules/dead_pixel_correction.py +++ b/modules/dead_pixel_correction.py @@ -10,13 +10,12 @@ import numpy as np from tqdm import tqdm from scipy.ndimage import maximum_filter, minimum_filter, correlate -from util.utils import save_output_array class DeadPixelCorrection: "Dead Pixel Correction" - def __init__(self, img, platform, sensor_info, parm_dpc): + def __init__(self, img, platform, sensor_info, parm_dpc, save_out_obj): self.img = img.copy() self.enable = parm_dpc["is_enable"] self.is_save = parm_dpc["is_save"] @@ -28,6 +27,7 @@ def __init__(self, img, platform, sensor_info, parm_dpc): self.bpp = self.sensor_info["bit_depth"] self.threshold = parm_dpc["dp_threshold"] self.is_debug = parm_dpc["is_debug"] + self.save_out_obj = save_out_obj def padding(self): """Return a mirror padded copy of image.""" @@ -372,7 +372,6 @@ def apply_dead_pixel_correction(self): # center_pixel is good if pixel value is between min and max of a 3x3 neighborhhood. if not min(neighbors) < center_pixel < max(neighbors): - # ""center_pixel is corrected only if the difference of center_pixel and every # neighboring pixel is greater than the speciified threshold. # The two if conditions are used in combination to reduce False positives."" @@ -432,7 +431,7 @@ def save(self): Function to save module output """ if self.is_save: - save_output_array( + self.save_out_obj.save_output_array( self.in_file, self.img, "Out_dead_pixel_correction_", diff --git a/modules/demosaic.py b/modules/demosaic.py index c22e3d7..f159cb0 100644 --- a/modules/demosaic.py +++ b/modules/demosaic.py @@ -8,19 +8,19 @@ import time import numpy as np from scipy.signal import correlate2d -from util.utils import save_output_array class Demosaic: "CFA Interpolation - Demaosicing" - def __init__(self, img, platform, sensor_info, parm_dem): + def __init__(self, img, platform, sensor_info, parm_dem, save_out_obj): self.img = img.copy() self.is_save = parm_dem["is_save"] self.platform = platform self.sensor_info = sensor_info self.bayer = sensor_info["bayer_pattern"] self.bit_depth = sensor_info["bit_depth"] + self.save_out_obj = save_out_obj def masks_cfa_bayer(self): """ @@ -203,7 +203,7 @@ def save(self): Function to save module output """ if self.is_save: - save_output_array( + self.save_out_obj.save_output_array( self.platform["in_file"], self.img, "Out_demosaic_", diff --git a/modules/digital_gain.py b/modules/digital_gain.py index ae2348c..f4c38d2 100644 --- a/modules/digital_gain.py +++ b/modules/digital_gain.py @@ -9,15 +9,13 @@ import time import numpy as np -from util.utils import save_output_array - class DigitalGain: """ Digital Gain """ - def __init__(self, img, platform, sensor_info, parm_dga): + def __init__(self, img, platform, sensor_info, parm_dga, save_out_obj): self.img = img.copy() self.is_save = parm_dga["is_save"] self.is_debug = parm_dga["is_debug"] @@ -28,6 +26,7 @@ def __init__(self, img, platform, sensor_info, parm_dga): self.sensor_info = sensor_info self.platform = platform self.param_dga = parm_dga + self.save_out_obj = save_out_obj def apply_digital_gain(self): """ @@ -48,7 +47,6 @@ def apply_digital_gain(self): # 'ae_correction < 0' - Image is underexposed if self.is_auto: - if self.ae_feedback < 0: # max/min functions is applied to not allow digital gains exceed the defined limits self.current_gain = min( @@ -73,7 +71,7 @@ def save(self): Function to save module output """ if self.is_save: - save_output_array( + self.save_out_obj.save_output_array( self.platform["in_file"], self.img, "Out_digital_gain_", diff --git a/modules/gamma_correction.py b/modules/gamma_correction.py index 0fd4682..017a4eb 100644 --- a/modules/gamma_correction.py +++ b/modules/gamma_correction.py @@ -8,15 +8,13 @@ import time import numpy as np -from util.utils import save_output_array - class GammaCorrection: """ Gamma Correction """ - def __init__(self, img, platform, sensor_info, parm_gmm): + def __init__(self, img, platform, sensor_info, parm_gmm, save_out_obj): self.img = img.copy() self.enable = parm_gmm["is_enable"] self.is_save = parm_gmm["is_save"] @@ -24,6 +22,7 @@ def __init__(self, img, platform, sensor_info, parm_gmm): self.sensor_info = sensor_info self.bit_depth = sensor_info["bit_depth"] self.parm_gmm = parm_gmm + self.save_out_obj = save_out_obj def generate_gamma_8bit_lut(self): """ @@ -58,7 +57,7 @@ def save(self): Function to save module output """ if self.is_save: - save_output_array( + self.save_out_obj.save_output_array( self.platform["in_file"], self.img, "Out_gamma_correction_", diff --git a/modules/invalid_region_crop.py b/modules/invalid_region_crop.py index 3d23300..ce450c0 100644 --- a/modules/invalid_region_crop.py +++ b/modules/invalid_region_crop.py @@ -7,7 +7,6 @@ """ import re import time -from util.utils import save_output_array_yuv, save_output_array class InvalidRegionCrop: @@ -22,7 +21,7 @@ class InvalidRegionCrop: as the input image. """ - def __init__(self, img, platform, sensor_info, parm_irc): + def __init__(self, img, platform, sensor_info, parm_irc, save_out_obj): self.img = img.copy() self.enable = parm_irc["is_enable"] self.platform = platform @@ -32,6 +31,7 @@ def __init__(self, img, platform, sensor_info, parm_irc): self.bit_depth = sensor_info["bit_depth"] self.sensor_info = sensor_info self.is_valid = False + self.save_out_obj = save_out_obj def get_idx_for_rtl(self): """An offset is added to the indices to enbale exact array comparison.""" @@ -53,8 +53,8 @@ def get_idx_for_rtl(self): self.h_idx_rtl = self.h_strat_idx + offset self.w_idx_rtl = self.w_strat_idx - # if the user-defined indices are within this defined range, generated TVs - # can be compared without any removal of rows or columns. + # if the user-defined indices are within this defined range, generated output + # array can be compared without any removal of rows or columns with the RTL output. # Input image size is assumed to be 2592x1536 min_idx_h_gm, min_idx_w_gm = 14, 14 max_idx_w_gm = 644 @@ -69,7 +69,6 @@ def get_idx_for_rtl(self): self.is_valid = idx_valid_h and idx_valid_w def crop_3d(self, img, strat_h, end_h, start_w, end_w): - """This function performs cropping on a 3-channel image. The cropped region is determined by the given starting and ending indices for height and width""" @@ -129,7 +128,7 @@ def apply_cropping(self): print(" - IRC - Output height = ", self.new_h) if self.is_valid: print( - " - IRC - Indices for RTL can be used for TV comparison " + " - IRC - Indices for RTL can be used for output comparison " + "without removal of rows/border." ) @@ -147,7 +146,7 @@ def save(self): ) if self.is_save: if self.platform["rgb_output"]: - save_output_array( + self.save_out_obj.save_output_array( self.platform["in_file"], self.img, "Out_invalid_region_crop_", @@ -155,7 +154,7 @@ def save(self): self.bit_depth, ) else: - save_output_array_yuv( + self.save_out_obj.save_output_array_yuv( self.platform["in_file"], self.img, "Out_invalid_region_crop_", diff --git a/modules/noise_reduction_2d.py b/modules/noise_reduction_2d.py index aa8d5c2..479f087 100644 --- a/modules/noise_reduction_2d.py +++ b/modules/noise_reduction_2d.py @@ -12,7 +12,7 @@ import os import numpy as np from tqdm import tqdm -from util.utils import create_coeff_file, save_output_array_yuv +from util.utils import create_coeff_file class NoiseReduction2d: @@ -20,7 +20,7 @@ class NoiseReduction2d: 2D Noise Reduction """ - def __init__(self, img, sensor_info, parm_2dnr, platform): + def __init__(self, img, sensor_info, parm_2dnr, platform, save_out_obj): self.img = img.copy() self.enable = parm_2dnr["is_enable"] self.is_save = parm_2dnr["is_save"] @@ -30,6 +30,7 @@ def __init__(self, img, sensor_info, parm_2dnr, platform): self.is_progress = platform["disable_progress_bar"] self.is_leave = platform["leave_pbar_string"] self.save_lut = platform["save_lut"] + self.save_out_obj = save_out_obj def make_weighted_curve(self, n_ind): """ @@ -156,7 +157,7 @@ def save(self): Function to save module output """ if self.is_save: - save_output_array_yuv( + self.save_out_obj.save_output_array_yuv( self.platform["in_file"], self.img, "Out_2d_noise_reduction_", diff --git a/modules/oecf.py b/modules/oecf.py index 24bbc63..00a1138 100644 --- a/modules/oecf.py +++ b/modules/oecf.py @@ -7,19 +7,19 @@ """ import time import numpy as np -from util.utils import save_output_array class OECF: "Optical Electronic Conversion Function - correction" - def __init__(self, img, platform, sensor_info, parm_oecf): + def __init__(self, img, platform, sensor_info, parm_oecf, save_out_obj): self.img = img.copy() self.enable = parm_oecf["is_enable"] self.is_save = parm_oecf["is_save"] self.platform = platform self.sensor_info = sensor_info self.parm_oecf = parm_oecf + self.save_out_obj = save_out_obj def apply_oecf(self): """Execute OECF.""" @@ -39,7 +39,6 @@ def apply_oecf(self): raw_oecf = np.zeros(raw.shape) if bayer == "rggb": - raw_oecf[0::2, 0::2] = rd_lut[raw[0::2, 0::2]] raw_oecf[0::2, 1::2] = gr_lut[raw[0::2, 1::2]] raw_oecf[1::2, 0::2] = gb_lut[raw[1::2, 0::2]] @@ -71,7 +70,7 @@ def save(self): Function to save module output """ if self.is_save: - save_output_array( + self.save_out_obj.save_output_array( self.platform["in_file"], self.img, "Out_oecf_", diff --git a/modules/on_screen_display.py b/modules/on_screen_display.py new file mode 100644 index 0000000..91d4122 --- /dev/null +++ b/modules/on_screen_display.py @@ -0,0 +1,194 @@ +""" +File: osd.py +Description: Puts a logo on the final pipeline image +Code / Paper Reference: +Author: 10xEngineers Pvt Ltd +------------------------------------------------------------ +""" +import time +from pathlib import Path +import numpy as np + + +class OnScreenDisplay: + """ + This class implements the functionality for adding an on-screen display (OSD) + to an image. Specifically, it is designed to overlay a 10xEngineers logo onto the image. + The class allows customization of the logo's position and colors, + and supports alpha blending for transparency effects. + """ + + def __init__(self, img, platform, sensor_info, parm_osd, save_out_obj): + """ + Initializes the OnScreenDisplay instance with the image to be processed, + platform information, sensor details, and OSD parameters. + """ + # Image and configuration settings + self.img = img.copy() # Copy of the image to avoid modifying the original + self.enable = parm_osd["is_enable"] # Flag to enable/disable OSD + self.is_save = parm_osd["is_save"] # Flag to enable/disable saving the output + self.platform = platform # Platform information + self.sensor_info = sensor_info # Sensor information + self.parm_osd = parm_osd # OSD parameters + self.save_out_obj = save_out_obj + + # OSD position and appearance settings + self.x_offset = parm_osd["x_offset"] # Horizontal position offset for the logo + self.y_offset = parm_osd["y_offset"] # Vertical position offset for the logo + self.width = parm_osd["width"] # Width of the logo + self.height = parm_osd["height"] # Height of the logo + self.bg_color = parm_osd["bg_color"] # Background color of the logo + self.fg_color = parm_osd["fg_color"] # Foreground color of the logo + self.alpha = parm_osd["alpha"] # Alpha value for transparency + + # Maximum allowed dimensions for the logo + self.maximum_height = 128 + self.maximum_width = 256 + + def get_logo_numpy(self): + """ + Reads a logo from a specified text file and converts it into a NumPy array. + The text file should contain the logo in a bitmap format represented by hexadecimal values. + Each line in the file represents a row of the logo. + """ + + file_path = "./docs/assets/10xLogo.txt" + + if not Path(file_path).exists(): + # search recursively in the subdirectories + file_path = list(Path.cwd().rglob("*Logo.txt"))[0] + + with open(file_path, "r") as file: + img = [] + for line in file: + # Split the line by commas + # Convert each hexadecimal value in the line into a binary string + hex_numbers = line.strip().split(",")[:-1] + row = "" + for hex_num in hex_numbers: + row = row + bin(int(hex_num, 16))[2:].zfill(32) + img.append(np.array([int(bit) for bit in row])) + return np.array(img) + + def blend_pixels(self, foreground_pixel, background_pixel, alpha): + """ + Performs alpha blending on a pair of pixels. + This function blends a foreground pixel with a background pixel based on the alpha value. + Alpha blending is used to combine the logo and the image with transparency. + """ + blended_pixel = [ + (int(alpha * f + (255 - alpha) * b) >> 8) + for f, b in zip(foreground_pixel, background_pixel) + ] + return blended_pixel + + def alpha_blend(self, foreground_image, background_image, alpha): + """ + Applies alpha blending to overlay a foreground image (logo) onto a background image. + Assumes that both images are of the same dimensions and each pixel is in RGB format. + The alpha parameter determines the transparency level of the foreground image. + """ + # Assuming both images have the same dimensions and each pixel is in RGB format + blended_image = [] + for fg_row, bg_row in zip(foreground_image, background_image): + blended_row = [] + for fg_pixel, bg_pixel in zip(fg_row, bg_row): + blended_row.append(self.blend_pixels(fg_pixel, bg_pixel, alpha)) + blended_image.append(blended_row) + return blended_image + + def apply_osd(self): + """ + Applies the On-Screen Display (OSD) to the image. + It first retrieves the logo, checks size constraints, and + then overlays the logo onto the image. + The logo is positioned based on specified offsets and is + blended using the alpha_blend method. + """ + + logo = self.get_logo_numpy() + + height, width = logo.shape + # Check size constraints and return original image if constraints are not met + if ( + height + self.y_offset > self.sensor_info["height"] + or width + self.x_offset > self.sensor_info["width"] + ): + return self.img + + if height > max(self.height, self.maximum_height) or width > max( + self.width, self.maximum_width + ): + return self.img + + logo_img = np.empty((self.height, self.width, 3)) + + # Create a colorized version of the logo and apply alpha blending + logo_img[:, :, 0] = np.vectorize( + lambda x: self.bg_color[0] if x == 0 else self.fg_color[0] + )(logo) + logo_img[:, :, 1] = np.vectorize( + lambda x: self.bg_color[1] if x == 0 else self.fg_color[1] + )(logo) + logo_img[:, :, 2] = np.vectorize( + lambda x: self.bg_color[2] if x == 0 else self.fg_color[2] + )(logo) + + transparent_logo = self.alpha_blend( + logo_img, + self.img[ + self.y_offset : self.y_offset + height, + self.x_offset : self.x_offset + width, + :, + ], + self.alpha, + ) + + # Overlay the logo on the original image at the specified position + self.img[ + self.y_offset : self.y_offset + height, + self.x_offset : self.x_offset + width, + :, + ] = transparent_logo + + return self.img + + def save(self): + """ + Saves the output image with the applied OSD. + The function is called only if the saving option is enabled. + It utilizes utility functions for saving, handling file naming and format. + """ + if self.is_save: + if self.platform["rgb_output"]: + self.save_out_obj.save_output_array( + self.platform["in_file"], + self.img, + "Out_on_screen_display_", + self.platform, + self.sensor_info["bit_depth"], + ) + else: + self.save_out_obj.save_output_array_yuv( + self.platform["in_file"], + self.img, + "Out_on_screen_display_", + self.platform, + ) + + def execute(self): + """ + Executes the OSD application process. + It first checks if OSD is enabled, applies the OSD to the image, + measures the execution time, and saves the output if required. + This is the main method that orchestrates the OSD mdoules from infinite_isp. + """ + print("On-screen Display Function = " + str(self.enable)) + + if self.enable: + start = time.time() + oecf_out = self.apply_osd() + print(f" Execution time: {time.time() - start:.3f}s") + self.img = oecf_out + self.save() + return self.img diff --git a/modules/rgb_conversion.py b/modules/rgb_conversion.py index b7a1d6a..558cdfa 100644 --- a/modules/rgb_conversion.py +++ b/modules/rgb_conversion.py @@ -14,7 +14,6 @@ import time import numpy as np -from util.utils import save_output_array_yuv, save_output_array class RGBConversion: @@ -22,7 +21,7 @@ class RGBConversion: YUV to RGB Conversion """ - def __init__(self, img, platform, sensor_info, parm_rgb, parm_csc): + def __init__(self, img, platform, sensor_info, parm_rgb, parm_csc, save_out_obj): self.img = img.copy() self.platform = platform self.sensor_info = sensor_info @@ -33,6 +32,7 @@ def __init__(self, img, platform, sensor_info, parm_rgb, parm_csc): self.conv_std = parm_csc["conv_standard"] self.yuv_img = img self.yuv2rgb_mat = None + self.save_out_obj = save_out_obj def yuv_to_rgb(self): """ @@ -55,8 +55,8 @@ def yuv_to_rgb(self): self.yuv2rgb_mat = np.array([[74, 0, 114], [74, -13, -34], [74, 135, 0]]) else: # for BT.601/407 - # conversion metrix with 8bit integer co-efficients - m=8 - self.yuv2rgb_mat = np.array([[64, 87, 0], [64, -44, -20], [61, 0, 105]]) + # conversion metrix with 8bit integer co-efficients - m=6 + self.yuv2rgb_mat = np.array([[64, 0, 87], [64, -20, -44], [61, 105, 0]]) # convert to RGB rgb_2d = np.matmul(self.yuv2rgb_mat, mat2d_t) @@ -79,7 +79,7 @@ def save(self): """ if self.is_save: if self.enable: - save_output_array( + self.save_out_obj.save_output_array( self.platform["in_file"], self.img, "Out_rgb_conversion_", @@ -87,7 +87,7 @@ def save(self): self.bit_depth, ) else: - save_output_array_yuv( + self.save_out_obj.save_output_array_yuv( self.platform["in_file"], self.img, "Out_rgb_conversion_", diff --git a/modules/scale.py b/modules/scale.py index 5daa81d..25fb4b6 100644 --- a/modules/scale.py +++ b/modules/scale.py @@ -9,19 +9,20 @@ import time import re import numpy as np -from util.utils import crop, stride_convolve2d, save_output_array, save_output_array_yuv +from util.utils import crop, stride_convolve2d class Scale: """Scale color image to given size.""" - def __init__(self, img, platform, sensor_info, parm_sca): + def __init__(self, img, platform, sensor_info, parm_sca, save_out_obj): self.img = img.copy() self.enable = parm_sca["is_enable"] self.is_save = parm_sca["is_save"] self.sensor_info = sensor_info self.platform = platform self.parm_sca = parm_sca + self.save_out_obj = save_out_obj self.get_scaling_params() def apply_scaling(self): @@ -39,7 +40,6 @@ def apply_scaling(self): # Loop over each channel to resize the image for i in range(3): - ch_arr = self.img[:, :, i] scale_2d = Scale2D(ch_arr, self.sensor_info, self.parm_sca) scaled_ch = scale_2d.execute() @@ -75,7 +75,7 @@ def save(self): ) if self.is_save: if self.platform["rgb_output"]: - save_output_array( + self.save_out_obj.save_output_array( self.platform["in_file"], self.img, "Out_scale_", @@ -83,7 +83,7 @@ def save(self): self.sensor_info["bit_depth"], ) else: - save_output_array_yuv( + self.save_out_obj.save_output_array_yuv( self.platform["in_file"], self.img, "Out_scale_", @@ -114,7 +114,6 @@ def __init__(self, single_channel, sensor_info, parm_sca): self.get_scaling_params() def fast_nearest_neighbor(self, new_size): - """Down scale by an integer factor using NN method using convolution.""" old_height, old_width = ( @@ -133,7 +132,6 @@ def fast_nearest_neighbor(self, new_size): return scaled_img def scale_nearest_neighbor(self, new_size): - """ Upscale/Downscale 2D array by any scale factor using Nearest Neighbor (NN) algorithm. """ @@ -163,7 +161,6 @@ def hardware_dep_scaling(self): return self.apply_algo(scale_info) def apply_algo(self, scale_info): - """ Scale 2D array using hardware friendly approach comprising of 2 steps: 1. Downscale with int factor @@ -186,7 +183,6 @@ def apply_algo(self, scale_info): else: # step 1: Downscale by int fcator if scale_info[0][0] > 1 or scale_info[1][0] > 1: - self.single_channel = self.fast_nearest_neighbor( ( self.old_size[0] // scale_info[0][0], diff --git a/modules/white_balance.py b/modules/white_balance.py index 2b5fa09..1e148a2 100644 --- a/modules/white_balance.py +++ b/modules/white_balance.py @@ -7,7 +7,7 @@ """ import time import numpy as np -from util.utils import get_approximate, save_output_array +from util.utils import get_approximate class WhiteBalance: @@ -15,7 +15,7 @@ class WhiteBalance: White balance Module """ - def __init__(self, img, platform, sensor_info, parm_wbc): + def __init__(self, img, platform, sensor_info, parm_wbc, save_out_obj): """ Class Constructor """ @@ -30,6 +30,7 @@ def __init__(self, img, platform, sensor_info, parm_wbc): self.bayer = self.sensor_info["bayer_pattern"] self.bpp = self.sensor_info["bit_depth"] self.raw = None + self.save_out_obj = save_out_obj def apply_wb_parameters(self): """ @@ -73,7 +74,7 @@ def save(self): Function to save module output """ if self.is_save: - save_output_array( + self.save_out_obj.save_output_array( self.platform["in_file"], self.img, "Out_white_balance_", diff --git a/modules/yuv_conv_format.py b/modules/yuv_conv_format.py index 72de740..d366ec2 100644 --- a/modules/yuv_conv_format.py +++ b/modules/yuv_conv_format.py @@ -14,13 +14,14 @@ import time import re import numpy as np -from util.utils import save_output_array class YUVConvFormat: "YUV Conversion Formats - 444, 442" - def __init__(self, img, platform, sensor_info, parm_yuv): # parm_csc): + def __init__( + self, img, platform, sensor_info, parm_yuv, save_out_obj + ): # parm_csc): self.img = img.copy() self.shape = img.shape self.enable = parm_yuv["is_enable"] @@ -30,6 +31,7 @@ def __init__(self, img, platform, sensor_info, parm_yuv): # parm_csc): self.platform = platform self.param_yuv = parm_yuv self.in_file = self.platform["in_file"] + self.save_out_obj = save_out_obj def convert2yuv_format(self): """Execute YUV conversion.""" @@ -69,12 +71,11 @@ def save(self): save_format = self.platform["save_format"] self.platform["save_format"] = "npy" - save_output_array( + self.save_out_obj.save_output_array_yuv( self.in_file, self.img, f"Out_yuv_conversion_format_{self.param_yuv['conv_type']}_", self.platform, - self.sensor_info["bit_depth"], ) # restore the original save format self.platform["save_format"] = save_format diff --git a/test_vector_generation/README.md b/test_vector_generation/README.md deleted file mode 100644 index 433d88d..0000000 --- a/test_vector_generation/README.md +++ /dev/null @@ -1,78 +0,0 @@ -# Automated Testing for Infinite-ISP -The automated script is designed to streamline the testing and debugging process of Infinite-ISP. It includes a configuration file that allows for customization of automation settings. The script provides comprehensive analysis of the Device Under Test (DUT), which can be a single module or a sequence of modules. It returns input to the DUT as well as its output, which can be in the form of a numpy array or a PNG image. The configuration file contains specific details and parameters for the automated script, enabling efficient and effective testing and debugging of the Infinite-ISP. - -## How to Run? - -Follow the following steps to run the automated testing: - -1. Go to [test_vector_generation](test_vector_generation) - -2. Set automation preferences through [tv_config.yml](test_vector_generation/tv_config.yml). - -3. Run [automate_execution.py](test_vector_generation/automate_execution.py) - -## Automation Configuration Parameters - -The configuration file [tv_config.yml](test_vector_generation/tv_config.yml) plays a crucial role in the automated script, allowing users to customize and control the various parameters of the Infinite-ISP for optimal testing and debugging. By utilizing this configuration file, users can effortlessly modify the Infinite-ISP settings without the need to manually enable or disable individual modules within the default configuration. Below are the detailed configuration parameters for the script: - -| Parameters | Details | -|--------------------|---------------------------------------------------| -| dataset_path | Path to the dataset
    Testing is done on all raw images using respective config files provided in the mentioned folder | -| config_path | Path to the config file for dataset images
    This file is used only if image-specific config file is not found | -| dut | Device Under Test
    It can be single module or set of modules in sequence. Details of how to set DUT are below | -| is_enable | Flag to enable non-default modules | -| is_save | Flag to save the test vector for default modules | - -### DUT - -The DUT (Device Under Test) refers to the specific module or set of modules that are being tested. The DUT can be any of the following modules: - -1. crop -2. dead_pixel_correction -3. black_level_correction -4. oecf -5. digital_gain -6. bayer_noise_reduction -7. white_balance -8. demosaic -9. color_correction_matrix -10. gamma_correction -11. color_space_conversion -12. 2d_noise_reduction -13. rgb_conversion -14. invalid_region_crop -15. scale -16. yuv_conversion_format - -When specifying the DUT (Device Under Test), it is important to use the exact names from the provided list. The DUT can be defined in two ways: - -1. Single Module: The DUT can be any individual module from the list above, such as "demosaic" or "scale" - -2. Multiple Modules in Sequence: When testing multiple modules in sequence, it is crucial to follow the specified order. For example, "crop, white_balance, scale" would be a valid sequence. However, "white_balance" cannot precede the "digital_gain" in the DUT list. - -By accurately matching the DUT name to the provided list, it is ensured that the correct modules are being tested, either individually or in the specified order, while considering any dependencies between the modules. - -### Default Automation Config Parameters - -The aforementioned parameters are intrinsic to the automated script, while the remaining configuration parameters are sourced from the given config. During automated testing, these parameters take precedence over the given script, allowing for their replacement and utilization. Once the testing is completed, the given config is restored to ensure consistency and proper functioning of the system. This approach enables a seamless integration of the automated scripts with the given configuration, providing reliable and efficient testing capabilities. - -1. platform: -
    - save_lut: True -
    - is_debug: True -
    - generate_tv: True -
    - save_format: npy or both -
    - render_3a: False - -2. For non-default modules in DUT list: -
    - is_enable: True -
    - is_save: True - - ## Results - - After automated script execution, results are stored in a folder in [test_vectors](test_vector_generation/test_vectors) with a name that includes Time-Stamp and DUT. The final result folder contains: - - 1. Input-Output results (numpy-array and png-image) for each DUT. - 2. Final output of Infinite-ISP - 3. Configuration files of Infinite-ISP - 4. Configuration file of automation script. - 5. Logs for ISP-Pipeline execution. \ No newline at end of file diff --git a/test_vector_generation/automate_execution.py b/test_vector_generation/automate_execution.py deleted file mode 100644 index e270866..0000000 --- a/test_vector_generation/automate_execution.py +++ /dev/null @@ -1,220 +0,0 @@ -""" -DESCRIPTION: ... -""" - -import sys -import os -from pathlib import Path -import shutil -from datetime import datetime -import time -import yaml -import tv_utils - -# add parent path to system path -sys.path.append(".") -import infinite_isp - -# load and read the automation config file -with open("./test_vector_generation/tv_config.yml", "r", encoding="utf-8") as file: - automation_config = yaml.safe_load(file) - -DATASET_PATH = automation_config["dataset_path"] -CONFIG_PATH = automation_config["config_path"] -REV_YUV = automation_config["rev_yuv"] -VIDEO_MODE = automation_config["video_mode"] - -# The input array of the first module and the output array of -# the last module are saved in test_vectors directory. -DUT = automation_config["dut"] - -# Read the status of each module from the config file -CROP = automation_config["crop"] -DPC = automation_config["dead_pixel_correction"] -BLC = automation_config["black_level_correction"] -OECF = automation_config["oecf"] -DG = automation_config["digital_gain"] -BNR = automation_config["bayer_noise_reduction"] -WB = automation_config["white_balance"] -DEM = automation_config["demosaic"] -CCM = automation_config["color_correction_matrix"] -GC = automation_config["gamma_correction"] -CSC = automation_config["color_space_conversion"] -NR2D = automation_config["2d_noise_reduction"] -RGB_CONV = automation_config["rgb_conversion"] -IRC = automation_config["invalid_region_crop"] -SCALE = automation_config["scale"] -YUV = automation_config["yuv_conversion_format"] - -# Define Directory name with datetime stamp to save outputs -dut_names = DUT[0] if len(DUT) == 1 else DUT[0] + "_to_" + DUT[-1] -folder_name = datetime.now().strftime("%Y%m%d_%H%M%S") + "-" + dut_names - -# create a folder to save the Results, delete directory if it exists already -SAVE_PATH = "./test_vectors/Results/" -if os.path.exists(SAVE_PATH): - shutil.rmtree(SAVE_PATH) -time.sleep(1) -Path(SAVE_PATH).mkdir(parents=True, exist_ok=False) - -# Get the list of all files in the DATASET_PATH -DIRECTORY_CONTENT = os.listdir(DATASET_PATH) - -# loop over images -RAW_FILENAMES = [ - filename - for filename in DIRECTORY_CONTENT - if Path(DATASET_PATH, filename).suffix in [".raw"] -] - -# create and infinite_isp object -inf_isp = infinite_isp.InfiniteISP(DATASET_PATH, CONFIG_PATH) -IS_DEFAULT_CONFIG = True - -for frame_count, raw_filename in enumerate(RAW_FILENAMES): - config_file = Path(CONFIG_PATH).name - - if not VIDEO_MODE: - # look for image-specific config file in DATASET_PATH - raw_path_object = Path(raw_filename) - - config_file = raw_path_object.stem + "-configs.yml" - - # check if the config file exists in the DATASET_PATH - if tv_utils.find_files(config_file, DATASET_PATH): - print(f"File {config_file} found.") - CONFIG_PATH = Path(DATASET_PATH).joinpath(config_file) - IS_DEFAULT_CONFIG = False - else: - # use given config if image-specific config file is not found - CONFIG_PATH = automation_config["config_path"] - IS_DEFAULT_CONFIG = True - # load and update config file - with open(CONFIG_PATH, "r", encoding="utf-8") as file: - config = yaml.safe_load(file) - - # remove modules that do not process the current frame - default_modules = ["digital_gain", "demosaic", "color_space_conversion"] - module_tags = list(config.keys())[2:] - remove = [ - "auto_exposure", - "auto_white_balance", - ] - _ = [module_tags.remove(module) for module in remove] - - # Check if the DUT list is defined corectly - if not tv_utils.is_valid(module_tags, DUT): - print("The sequence of modules in DUT is incorrect.") - exit() - - # ensure that the modules are in same order as they are in the default config file - new_params = [ - CROP, - DPC, - BLC, - OECF, - DG, - BNR, - WB, - DEM, - CCM, - GC, - CSC, - NR2D, - RGB_CONV, - IRC, - SCALE, - YUV, - ] - - # Set generate_tv to True to indicate that automation file is being executed - config["platform"]["generate_tv"] = True - - # update save_lut flag in config - config["platform"]["save_lut"] = True - - # update rev_uv flag in config - config["platform"]["rev_yuv_channels"] = REV_YUV - - # disable render_3a flag if video_mode is enabled - if VIDEO_MODE: - config["platform"]["render_3a"] = False - - # It is mandatory to save test vectors as numpy arrays - if config["platform"]["save_format"] == "png": - config["platform"]["save_format"] = "both" - - # update filename in config - config["platform"]["filename"] = raw_filename - - for idx, module in enumerate(module_tags): - # save the input and output arrays of module under test with is_save flag - try: - # save the input to DUT with is_save flag - if module in DUT or module_tags[idx + 1] in DUT: - IS_SAVE = True - elif module in default_modules: - - IS_SAVE = new_params[idx]["is_save"] - else: - IS_SAVE = False - - except IndexError: - IS_SAVE = True if module in DUT else False - - # Enable non-default modules in DUT - if module in DUT and module not in default_modules: - new_params[idx]["is_enable"] = True - - tv_utils.update_config( - config, module, new_params[idx].keys(), new_params[idx].values(), IS_SAVE - ) - - # create directory to save config files - Path(SAVE_PATH).joinpath("config").mkdir(parents=True, exist_ok=True) - tv_utils.save_config(automation_config, Path(SAVE_PATH).joinpath("tv_config.yml")) - tv_utils.save_config(config, Path(SAVE_PATH).joinpath(f"config/{config_file}")) - - # load config file for the first file/frame: - if frame_count == 0: - inf_isp.load_config(Path(SAVE_PATH).joinpath(f"config/{config_file}")) - # for other files/frames - else: - # load config if provided in dataset folder otherwise update the - # filename in inf_isp object - if IS_DEFAULT_CONFIG: - inf_isp.raw_file = raw_filename - else: - inf_isp.load_config(Path(SAVE_PATH).joinpath(f"config/{config_file}")) - - with open( - Path(SAVE_PATH).joinpath("isp_pipeline_log.txt"), - "a", - encoding="utf-8", - ) as text_file: - sys.stdout = text_file - inf_isp.execute() - sys.stdout = sys.__stdout__ - - if VIDEO_MODE: - inf_isp.load_3a_statistics() - -# Remove path from sys path -sys.path.remove(".") - -# rename output files of the previous module to DUT as "In_" to identify these files -# as input to DUT files -if "crop" in DUT: - tv_utils.rename_files(SAVE_PATH, "Inpipeline_crop_") -else: - input_module = module_tags[module_tags.index(DUT[0]) - 1] - tv_utils.rename_files(SAVE_PATH, "Out_" + input_module + "_") - -# restructure the directory -tv_utils.restructure_dir(SAVE_PATH, DUT[-1]) - -# convert the saved numpy arrays to bin files -tv_utils.get_input_tv(SAVE_PATH, REV_YUV, RGB_CONV["is_enable"]) - -# Remove empty folder andrename results folder with datetime stamp -os.rename(SAVE_PATH, f"./test_vectors/{folder_name}") diff --git a/test_vector_generation/tv_config.yml b/test_vector_generation/tv_config.yml deleted file mode 100644 index 558fb9b..0000000 --- a/test_vector_generation/tv_config.yml +++ /dev/null @@ -1,47 +0,0 @@ -dataset_path: "./in_frames/normal/data/" -config_path: "./config/configs.yml" -rev_yuv: True -video_mode: true -# DUT options = ['crop', 'dead_pixel_correction', 'black_level_correction', -# 'oecf', 'digital_gain','bayer_noise_reduction', -# 'white_balance', 'demosaic', 'color_correction_matrix', -# 'gamma_correction', 'color_space_conversion', -# '2d_noise_reduction', 'rgb_conversion', 'invalid_region_crop', -# 'scale', 'yuv_conversion_format'] -dut: [dead_pixel_correction,digital_gain,white_balance,demosaic,color_space_conversion, rgb_conversion, invalid_region_crop] -crop: - is_enable: false -dead_pixel_correction: - is_enable: false -black_level_correction: - is_enable: false -oecf: - is_enable: false -digital_gain: - is_save: false -bayer_noise_reduction: - is_enable: false -auto_white_balance: - is_enable: false -white_balance: - is_enable: false -demosaic: - is_save: false -color_correction_matrix: - is_enable: false -gamma_correction: - is_enable: false -auto_exposure: - is_enable: false -color_space_conversion: - is_save: false -2d_noise_reduction: - is_enable: false -rgb_conversion: - is_enable: false -invalid_region_crop: - is_enable: false -scale: - is_enable: false -yuv_conversion_format: - is_enable: false diff --git a/test_vector_generation/tv_utils.py b/test_vector_generation/tv_utils.py deleted file mode 100644 index 1234c34..0000000 --- a/test_vector_generation/tv_utils.py +++ /dev/null @@ -1,264 +0,0 @@ -""" -File: utils.py -Description: Common helper functions for all algorithms -Code / Paper Reference: -Author: 10xEngineers Pvt Ltd ------------------------------------------------------------- -""" -import os -from shutil import move -from pathlib import Path -import yaml -from fxpmath import Fxp -import numpy as np - - -def get_approximate(decimal, register_bits, frac_precision_bits): - """ - Returns Fixed Float Approximation of a decimal - """ - fixed_float = Fxp(decimal, False, register_bits, frac_precision_bits) - return fixed_float(), fixed_float.bin() - - -def rev_yuv(arr): - """This function reverses the order of YUV channels in yuv image ARR.""" - if len(arr.shape) != 3: - print("Input array must be 3D. Input array not modified.") - return - - out_arr = np.zeros(arr.shape, arr.dtype) - out_arr[:, :, 0] = arr[:, :, 2] - out_arr[:, :, 1] = arr[:, :, 1] - out_arr[:, :, 2] = arr[:, :, 0] - - return out_arr - - -# automation script related utilities -def is_valid(ref_lst, sub_lst): - """This function checks the order of the ennteries of SUB_LST w.r.t - REF_LST. Returns True if SUB_LST entries are in the same order as - REF_LST, False otherwise.""" - - # get indices w.r.t reference list of each entry in sub list - dut_idx = [] - for entry in sub_lst: - if entry in ref_lst: - dut_idx.append(ref_lst.index(entry)) - - dut_array = np.array(dut_idx) - - # compute differences of the consective indices - differences = np.diff(dut_array) - - # The list is in ascending order if all differences are non-negative. - return np.all(differences >= 0) - - -def arrange_channels(arr): - """This function changes the shape of the NumPy array - ARR from (height,width,channel) to (channel, height, width)""" - if len(arr.shape) != 3: - print("Input array must be 3D. Input array not modified.") - return - height, width, channel = arr.shape - out_arr = np.zeros((channel, height, width), arr.dtype) - out_arr[0, :, :] = arr[:, :, 0] - out_arr[1, :, :] = arr[:, :, 1] - out_arr[2, :, :] = arr[:, :, 2] - - return out_arr - - -def rename_files(path, sub_str): - """This function appends In_ substring to files which are input to the DUT. - These files are identified by SUB_STR.""" - - files = [f_name for f_name in os.listdir(path) if sub_str in f_name] - for file in files: - new_name = "In_" + "_".join(file.split("_")[1:]) - os.rename(path + file, path + new_name) - - -def find_files(filename, search_path): - """ - This function is used to find the files in the search_path - """ - for _, _, files in os.walk(search_path): - if filename in files: - return True - return False - - -def restructure_dir(path, out_module_name): - """ - This function restuctures the given folder as follows: - - folder (specified by path) - - input (input to DUT file with "In_" in filename) - - GM_out (output to DUT file with "Out_" in filename) - - config file - - Input to isp_pipeline files - - Output of isp_pipeline files - """ - files = [ - f_name - for f_name in os.listdir(path) - if ".npy" == f_name[-4:] or ".png" == f_name[-4:] - ] - - in_dir = Path(path).joinpath("input") - out_dir = Path(path).joinpath("GM_out") - - in_dir.mkdir(parents=True, exist_ok=True) - out_dir.mkdir(parents=True, exist_ok=True) - - for file in files: - if file[0:3] == "In_": - move(path + file, str(in_dir) + "/" + file) - - if "Out_" + out_module_name + "_" in file: - move(path + file, str(out_dir) + "/" + file) - - -def convert_npytobin(path, nametag, raw_ext=".bin"): - """This function takes a numpy array and saves each channel of the single - file (.npy) as a binary file (.bin) in the given directory.""" - - dir_path = "./" + str(Path(path).parent) + "/" - in_filename = str(Path(path).stem) - - try: - np_arr = np.load(path) - except ValueError: - np_arr = np.load(path, allow_pickle=False) - print("ValueError in", in_filename) - if len(np_arr.shape) == 3: - for idx, channel in enumerate(nametag): - filename = channel + "_" + in_filename + raw_ext - with open(dir_path + filename, "wb") as raw_file: - np_arr[:, :, idx].tofile(raw_file) - else: - if len(np_arr.shape) != 2: - print("Input array must be a 2D array. Input array not saved.") - return - with open(dir_path + in_filename + raw_ext, "wb") as raw_file: - np_arr.tofile(raw_file) - return np_arr - - -def get_input_tv(path, rev_flag, rgb_conv_flag): - - """This function converts the NumPy arrays to binary files in input folder, - and reorders the output files to ensure accurate comparison.""" - - # for Input files convert npy to raw - filelist = [file for file in os.listdir(path + "input/") if ".npy" == file[-4:]] - if not filelist: - print("Empty folder found. Enable is_save flag to save input TVs.") - exit() - # check if module output is RGB or YUV - yuv_out = [ - "color_space_conversion", - "2d_noise_reduction", - ] - rgb_out = [ - "demosaic", - "color_correction_matrix", - "gamma_correction", - ] - - rgb_or_yuv = [ - "rgb_conversion", - "invalid_region_crop", - "scale", - "yuv_conversion_format", - ] - any_file_name = filelist[0] - - if any([m_name in any_file_name for m_name in yuv_out]): - if rev_flag: - f_nametag = "RGB" - else: - f_nametag = "BGR" - - elif any([m_name in any_file_name for m_name in rgb_out]): - f_nametag = "RGB" - - elif any([m_name in any_file_name for m_name in rgb_or_yuv]): - if rev_flag is False and rgb_conv_flag is False: - f_nametag = "BGR" - else: - f_nametag = "RGB" - - else: - f_nametag = "" - - for file in filelist: - f_path = path + "input/" + file - convert_npytobin(f_path, f_nametag) - - # for output files change sequence of channels (h,w,ch)-->(ch,h,w) - files = [file for file in os.listdir(path + "GM_out/") if ".npy" == file[-4:]] - for file in files: - f_path = path + "GM_out/" + file - np_arr = np.load(f_path) - if len(np_arr.shape) == 3: - out_arr = arrange_channels(np_arr) - np.save(path + "GM_out/" + file, out_arr) - - -# update config params -def update_config(config_file, module, keys, values, is_save): - """This function updates a scecific dictionary (module) in a nested dictionary(config file).""" - for key, value in zip(keys, values): - if keys and config_file[module][key] != value: - config_file[module][key] = value - - # enable is_debug flag - config_file[module]["is_debug"] = True - - if is_save: - config_file[module]["is_save"] = True - else: - config_file[module]["is_save"] = False - - -# utilities to save the config_automate exactly as config.yml -class CustomDumper(yaml.Dumper): - - """This class is a custom YAML dumper that overrides the default behavior - of the increase_indent and write_line_break methods. It ensures that indentations - and line breaks are inserted correctly in the output YAML file.""" - - def increase_indent(self, flow=False, indentless=False): - """For indentation""" - return super(CustomDumper, self).increase_indent(flow, False) - - def write_line_break(self, data=None): - """For line break""" - super().write_line_break(data) - if len(self.indents) == 1: - self.stream.write("\n") - - -def represent_list(self, data): - """This function ensures that the lookup table are stored on flow style - to keep the saved yaml file readable.""" - return self.represent_sequence("tag:yaml.org,2002:seq", data, flow_style=True) - - -def save_config(dict_obj, save_path): - """This function saves a dictionary as a yaml file using custom dumper.""" - - # Set list format to flowstyle to dump yaml file - yaml.add_representer(list, represent_list) - - with open(save_path, "w", encoding="utf-8") as file: - yaml.dump( - dict_obj, - file, - sort_keys=False, - Dumper=CustomDumper, - width=17000, - ) diff --git a/tests/test_data/.gitkeep b/tests/test_data/.gitkeep new file mode 100644 index 0000000..e69de29 diff --git a/tests/test_data/Indoor1_2592x1536_10bit_GRBG-configs.yml b/tests/test_data/Indoor1_2592x1536_10bit_GRBG-configs.yml new file mode 100644 index 0000000..56a564a --- /dev/null +++ b/tests/test_data/Indoor1_2592x1536_10bit_GRBG-configs.yml @@ -0,0 +1,168 @@ +platform: + filename: Indoor1_2592x1536_10bit_GRBG.raw + disable_progress_bar: False + leave_pbar_string: False + save_lut: False + save_format: npy + # png # npy # both + render_3a: False + +sensor_info: + bayer_pattern: grbg + range: 1023 + bit_depth: 10 + width: 2592 + height: 1536 + +crop: + is_enable: False + is_debug: False + new_width: 1280 + new_height: 720 + is_save: False + +dead_pixel_correction: + is_enable: True + dp_threshold: 20 + is_debug: True + is_save: False + +black_level_correction: + is_enable: True + is_debug: True + r_offset: 50 + gr_offset: 50 + gb_offset: 50 + b_offset: 50 + is_linear: True + r_sat: 1023 + gr_sat: 1023 + gb_sat: 1023 + b_sat: 1023 + is_save: False + +oecf: + is_enable: True + # Make sure the LUT has the right bit range i.e. if image is of 10 bit LUT should be from [0 - (2^10)-1] + # LUT here does nothing to the sensor response i.e. a value of 800 maps to 800 and 2000 maps to 2000 + r_lut: 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,3222,3223,3224,3225,3226,3227,3228,3229,3230,3231,3232,3233,3234,3235,3236,3237,3238,3239,3240,3241,3242,3243,3244,3245,3246,3247,3248,3249,3250,3251,3252,3253,3254,3255,3256,3257,3258,3259,3260,3261,3262,3263,3264,3265,3266,3267,3268,3269,3270,3271,3272,3273,3274,3275,3276,3277,3278,3279,3280,3281,3282,3283,3284,3285,3286,3287,3288,3289,3290,3291,3292,3293,3294,3295,3296,3297,3298,3299,3300,3301,3302,3303,3304,3305,3306,3307,3308,3309,3310,3311,3312,3313,3314,3315,3316,3317,3318,3319,3320,3321,3322,3323,3324,3325,3326,3327,3328,3329,3330,3331,3332,3333,3334,3335,3336,3337,3338,3339,3340,3341,3342,3343,3344,3345,3346,3347,3348,3349,3350,3351,3352,3353,3354,3355,3356,3357,3358,3359,3360,3361,3362,3363,3364,3365,3366,3367,3368,3369,3370,3371,3372,3373,3374,3375,3376,3377,3378,3379,3380,3381,3382,3383,3384,3385,3386,3387,3388,3389,3390,3391,3392,3393,3394,3395,3396,3397,3398,3399,3400,3401,3402,3403,3404,3405,3406,3407,3408,3409,3410,3411,3412,3413,3414,3415,3416,3417,3418,3419,3420,3421,3422,3423,3424,3425,3426,3427,3428,3429,3430,3431,3432,3433,3434,3435,3436,3437,3438,3439,3440,3441,3442,3443,3444,3445,3446,3447,3448,3449,3450,3451,3452,3453,3454,3455,3456,3457,3458,3459,3460,3461,3462,3463,3464,3465,3466,3467,3468,3469,3470,3471,3472,3473,3474,3475,3476,3477,3478,3479,3480,3481,3482,3483,3484,3485,3486,3487,3488,3489,3490,3491,3492,3493,3494,3495,3496,3497,3498,3499,3500,3501,3502,3503,3504,3505,3506,3507,3508,3509,3510,3511,3512,3513,3514,3515,3516,3517,3518,3519,3520,3521,3522,3523,3524,3525,3526,3527,3528,3529,3530,3531,3532,3533,3534,3535,3536,3537,3538,3539,3540,3541,3542,3543,3544,3545,3546,3547,3548,3549,3550,3551,3552,3553,3554,3555,3556,3557,3558,3559,3560,3561,3562,3563,3564,3565,3566,3567,3568,3569,3570,3571,3572,3573,3574,3575,3576,3577,3578,3579,3580,3581,3582,3583,3584,3585,3586,3587,3588,3589,3590,3591,3592,3593,3594,3595,3596,3597,3598,3599,3600,3601,3602,3603,3604,3605,3606,3607,3608,3609,3610,3611,3612,3613,3614,3615,3616,3617,3618,3619,3620,3621,3622,3623,3624,3625,3626,3627,3628,3629,3630,3631,3632,3633,3634,3635,3636,3637,3638,3639,3640,3641,3642,3643,3644,3645,3646,3647,3648,3649,3650,3651,3652,3653,3654,3655,3656,3657,3658,3659,3660,3661,3662,3663,3664,3665,3666,3667,3668,3669,3670,3671,3672,3673,3674,3675,3676,3677,3678,3679,3680,3681,3682,3683,3684,3685,3686,3687,3688,3689,3690,3691,3692,3693,3694,3695,3696,3697,3698,3699,3700,3701,3702,3703,3704,3705,3706,3707,3708,3709,3710,3711,3712,3713,3714,3715,3716,3717,3718,3719,3720,3721,3722,3723,3724,3725,3726,3727,3728,3729,3730,3731,3732,3733,3734,3735,3736,3737,3738,3739,3740,3741,3742,3743,3744,3745,3746,3747,3748,3749,3750,3751,3752,3753,3754,3755,3756,3757,3758,3759,3760,3761,3762,3763,3764,3765,3766,3767,3768,3769,3770,3771,3772,3773,3774,3775,3776,3777,3778,3779,3780,3781,3782,3783,3784,3785,3786,3787,3788,3789,3790,3791,3792,3793,3794,3795,3796,3797,3798,3799,3800,3801,3802,3803,3804,3805,3806,3807,3808,3809,3810,3811,3812,3813,3814,3815,3816,3817,3818,3819,3820,3821,3822,3823,3824,3825,3826,3827,3828,3829,3830,3831,3832,3833,3834,3835,3836,3837,3838,3839,3840,3841,3842,3843,3844,3845,3846,3847,3848,3849,3850,3851,3852,3853,3854,3855,3856,3857,3858,3859,3860,3861,3862,3863,3864,3865,3866,3867,3868,3869,3870,3871,3872,3873,3874,3875,3876,3877,3878,3879,3880,3881,3882,3883,3884,3885,3886,3887,3888,3889,3890,3891,3892,3893,3894,3895,3896,3897,3898,3899,3900,3901,3902,3903,3904,3905,3906,3907,3908,3909,3910,3911,3912,3913,3914,3915,3916,3917,3918,3919,3920,3921,3922,3923,3924,3925,3926,3927,3928,3929,3930,3931,3932,3933,3934,3935,3936,3937,3938,3939,3940,3941,3942,3943,3944,3945,3946,3947,3948,3949,3950,3951,3952,3953,3954,3955,3956,3957,3958,3959,3960,3961,3962,3963,3964,3965,3966,3967,3968,3969,3970,3971,3972,3973,3974,3975,3976,3977,3978,3979,3980,3981,3982,3983,3984,3985,3986,3987,3988,3989,3990,3991,3992,3993,3994,3995,3996,3997,3998,3999,4000,4001,4002,4003,4004,4005,4006,4007,4008,4009,4010,4011,4012,4013,4014,4015,4016,4017,4018,4019,4020,4021,4022,4023,4024,4025,4026,4027,4028,4029,4030,4031,4032,4033,4034,4035,4036,4037,4038,4039,4040,4041,4042,4043,4044,4045,4046,4047,4048,4049,4050,4051,4052,4053,4054,4055,4056,4057,4058,4059,4060,4061,4062,4063,4064,4065,4066,4067,4068,4069,4070,4071,4072,4073,4074,4075,4076,4077,4078,4079,4080,4081,4082,4083,4084,4085,4086,4087,4088,4089,4090,4091,4092,4093,4094,4095] + is_save: False + +digital_gain: + is_debug: True + is_auto: True + # Array of pre-define Gains + gain_array: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, + 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, + 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, + 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, + 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100] + # Index of default gain + current_gain: 0 + ae_feedback: 0 + is_save: False + +bayer_noise_reduction: + is_enable: True + filter_window: 9 + r_std_dev_s: 1 + r_std_dev_r: 0.1 + g_std_dev_s: 1 + g_std_dev_r: 0.08 + b_std_dev_s: 1 + b_std_dev_r: 0.1 + is_save: False + +auto_white_balance: + is_enable: True + is_debug: True + stats_window_offset: [16, 16, 16, 16] + underexposed_percentage: 2.5 + overexposed_percentage: 2.5 + is_save: False + +white_balance: + is_enable: True + is_debug: True + is_auto: True + r_gain: 1.44921875 + b_gain: 3.2421875 + is_save: False + +demosaic: + is_save: False + +color_correction_matrix: + is_enable: True + corrected_red: [2256, -1116, -116] + corrected_green: [-300, 1340, -16] + corrected_blue: [60, -908, 1872] + is_save: False + +gamma_correction: + is_enable: True + # 8-bit + gamma_lut_8: [0,5,9,13,17,22,25,29,33,37,40,44,47,50,54,57,60,63,66,69,72,75,78,80,83,85,88,90,93,95,97,99,101,103,105,107,109,111,113,115,117,118,120,122,123,125,126,128,129,131,132,134,135,136,138,139,140,141,142,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,162,163,164,165,166,167,167,168,169,170,171,171,172,173,173,174,175,176,176,177,178,179,179,180,181,181,182,183,183,184,185,185,186,187,187,188,188,189,190,190,191,191,192,193,193,194,194,195,195,196,197,197,198,198,199,199,200,200,201,201,202,202,203,203,204,204,205,205,206,206,207,207,208,208,209,209,210,210,211,211,212,212,213,213,214,214,215,215,216,216,217,217,218,218,219,219,220,220,221,221,221,222,222,223,223,224,224,225,225,225,226,226,227,227,228,228,228,229,229,230,230,231,231,231,232,232,233,233,234,234,234,235,235,236,236,237,237,238,238,238,239,239,240,240,241,241,241,242,242,243,243,244,244,244,245,245,246,246,247,247,247,248,248,249,249,250,250,250,251,251,252,252,252,253,253,254,254,255] + # 10-bit + gamma_lut_10: [0, 9, 13, 17, 21, 25, 29, 34, 38, 42, 46, 50, 54, 58, 62, 66, 70, 74, 78, 82, 86, 90, 94, 98, 102, 106, 110, 114, 117, 121, 125, 129, 132, 136, 140, 143, 147, 150, 154, 157, 161, 165, 168, 172, 175, 179, 182, 185, 189, 192, 196, 199, 202, 205, 209, 212, 215, 219, 222, 225, 228, 231, 235, 238, 241, 244, 247, 250, 253, 256, 259, 262, 265, 268, 271, 274, 277, 280, 283, 286, 289, 292, 295, 297, 300, 303, 306, 308, 311, 314, 317, 319, 322, 325, 327, 330, 332, 335, 337, 340, 342, 345, 347, 350, 352, 355, 357, 359, 362, 364, 367, 369, 371, 374, 376, 378, 380, 383, 385, 387, 389, 392, 394, 396, 398, 400, 402, 404, 406, 409, 411, 413, 415, 417, 419, 421, 423, 425, 427, 429, 431, 433, 435, 437, 439, 441, 443, 444, 446, 448, 450, 452, 454, 455, 457, 459, 461, 463, 464, 466, 468, 469, 471, 473, 474, 476, 478, 479, 481, 483, 484, 486, 488, 489, 491, 492, 494, 495, 497, 499, 500, 502, 503, 505, 506, 508, 509, 511, 513, 514, 516, 517, 519, 520, 521, 523, 524, 526, 527, 529, 530, 532, 533, 534, 536, 537, 539, 540, 541, 543, 544, 545, 547, 548, 549, 550, 552, 553, 554, 555, 557, 558, 559, 560, 562, 563, 564, 565, 567, 568, 569, 570, 571, 573, 574, 575, 576, 577, 578, 580, 581, 582, 583, 584, 585, 586, 588, 589, 590, 591, 592, 593, 594, 595, 596, 598, 599, 600, 601, 602, 603, 604, 605, 606, 607, 608, 609, 610, 611, 612, 613, 614, 615, 616, 617, 618, 619, 620, 621, 622, 623, 624, 625, 626, 627, 628, 629, 630, 631, 632, 633, 633, 634, 635, 636, 637, 638, 639, 640, 641, 641, 642, 643, 644, 645, 646, 647, 648, 649, 649, 650, 651, 652, 653, 654, 655, 655, 656, 657, 658, 659, 660, 660, 661, 662, 663, 664, 665, 665, 666, 667, 668, 669, 670, 670, 671, 672, 673, 674, 674, 675, 676, 677, 678, 678, 679, 680, 681, 681, 682, 683, 683, 684, 685, 686, 686, 687, 688, 689, 689, 690, 691, 692, 692, 693, 694, 695, 695, 696, 697, 697, 698, 699, 700, 700, 701, 702, 703, 703, 704, 705, 705, 706, 707, 708, 708, 709, 710, 710, 711, 712, 713, 713, 714, 715, 715, 716, 717, 717, 718, 719, 719, 720, 721, 722, 722, 723, 724, 724, 725, 726, 726, 727, 728, 728, 729, 730, 731, 731, 732, 733, 733, 734, 734, 735, 736, 736, 737, 738, 738, 739, 740, 740, 741, 742, 742, 743, 744, 744, 745, 745, 746, 747, 747, 748, 749, 749, 750, 751, 751, 752, 753, 753, 754, 754, 755, 756, 756, 757, 757, 758, 759, 759, 760, 761, 761, 762, 762, 763, 763, 764, 765, 765, 766, 766, 767, 768, 768, 769, 769, 770, 771, 771, 772, 772, 773, 774, 774, 775, 775, 776, 776, 777, 777, 778, 779, 779, 780, 780, 781, 782, 782, 783, 783, 784, 784, 785, 785, 786, 787, 787, 788, 788, 789, 789, 790, 791, 791, 792, 792, 793, 793, 794, 794, 795, 795, 796, 797, 797, 797, 798, 799, 799, 800, 800, 801, 801, 802, 802, 803, 803, 804, 805, 805, 806, 806, 806, 807, 808, 808, 809, 809, 810, 810, 811, 811, 812, 812, 813, 813, 814, 814, 815, 815, 816, 816, 817, 817, 818, 818, 819, 819, 820, 821, 821, 821, 822, 823, 823, 824, 824, 825, 825, 826, 826, 827, 827, 828, 828, 829, 829, 830, 830, 831, 831, 832, 832, 833, 833, 834, 834, 835, 835, 836, 836, 837, 837, 838, 838, 839, 839, 839, 840, 841, 841, 842, 842, 842, 843, 843, 844, 845, 845, 845, 846, 846, 847, 847, 848, 848, 849, 849, 850, 850, 851, 851, 852, 852, 853, 853, 854, 854, 855, 855, 856, 856, 857, 857, 858, 858, 859, 859, 860, 860, 861, 861, 862, 862, 863, 863, 864, 864, 865, 865, 866, 866, 867, 867, 868, 868, 868, 869, 870, 870, 870, 871, 871, 872, 872, 873, 873, 874, 874, 875, 875, 876, 876, 877, 877, 878, 878, 879, 879, 880, 880, 881, 881, 881, 882, 882, 883, 883, 884, 884, 885, 885, 886, 886, 887, 887, 887, 888, 888, 889, 889, 890, 890, 891, 891, 892, 892, 892, 893, 893, 894, 894, 895, 895, 896, 896, 896, 897, 897, 898, 898, 899, 899, 900, 900, 900, 901, 901, 902, 902, 903, 903, 903, 904, 904, 905, 905, 906, 906, 906, 907, 907, 908, 908, 909, 909, 910, 910, 910, 911, 911, 912, 912, 913, 913, 913, 914, 914, 915, 915, 916, 916, 916, 917, 917, 918, 918, 919, 919, 919, 920, 920, 921, 921, 922, 922, 922, 923, 923, 924, 924, 925, 925, 925, 926, 926, 927, 927, 928, 928, 928, 929, 929, 930, 930, 931, 931, 931, 932, 932, 933, 933, 934, 934, 934, 935, 935, 936, 936, 936, 937, 937, 938, 938, 939, 939, 939, 940, 940, 941, 941, 942, 942, 943, 943, 943, 944, 944, 945, 945, 946, 946, 947, 947, 947, 948, 948, 949, 949, 950, 950, 951, 951, 951, 952, 952, 953, 953, 954, 954, 955, 955, 956, 956, 956, 957, 957, 958, 958, 959, 959, 960, 960, 961, 961, 961, 962, 962, 963, 963, 964, 964, 964, 965, 965, 966, 966, 967, 967, 968, 968, 968, 969, 969, 970, 970, 971, 971, 971, 972, 972, 973, 973, 974, 974, 975, 975, 975, 976, 976, 977, 977, 977, 978, 978, 979, 979, 980, 980, 980, 981, 981, 982, 982, 983, 983, 983, 984, 984, 985, 985, 986, 986, 986, 987, 987, 988, 988, 988, 989, 989, 990, 990, 990, 991, 991, 992, 992, 993, 993, 994, 994, 994, 995, 995, 996, 996, 997, 997, 997, 998, 998, 999, 999, 999, 1000, 1000, 1001, 1001, 1002, 1002, 1002, 1003, 1003, 1004, 1004, 1004, 1005, 1005, 1006, 1006, 1007, 1007, 1007, 1008, 1008, 1009, 1009, 1010, 1010, 1010, 1011, 1011, 1012, 1012, 1013, 1013, 1013, 1014, 1014, 1015, 1015, 1015, 1016, 1016, 1017, 1017, 1018, 1018, 1018, 1019, 1019, 1020, 1020, 1021, 1021, 1021, 1022, 1022, 1023, 1023] + # 12-bit + gamma_lut_12: [0, 11, 21, 30, 37, 42, 46, 50, 53, 57, 61, 65, 70, 74, 78, 82, 86, 90, 94, 98, 102, 106, 110, 114, 118, 122, 126, 131, 135, 139, 143, 147, 151, 155, 159, 163, 167, 171, 175, 179, 183, 187, 191, 195, 199, 203, 207, 212, 216, 220, 224, 228, 232, 236, 240, 245, 249, 253, 257, 261, 265, 269, 273, 277, 281, 285, 289, 293, 297, 301, 305, 309, 313, 317, 321, 326, 330, 334, 338, 342, 346, 350, 354, 358, 362, 365, 369, 373, 377, 381, 385, 390, 394, 398, 401, 405, 409, 413, 417, 421, 425, 429, 432, 436, 440, 443, 447, 451, 455, 458, 462, 466, 470, 473, 477, 481, 485, 488, 492, 496, 500, 503, 507, 511, 515, 519, 522, 526, 530, 533, 537, 540, 544, 547, 551, 555, 559, 562, 566, 569, 573, 576, 580, 584, 588, 591, 595, 598, 602, 605, 609, 612, 616, 619, 622, 626, 630, 633, 637, 641, 645, 648, 652, 655, 659, 662, 665, 669, 673, 676, 680, 683, 687, 690, 693, 696, 700, 703, 707, 711, 715, 718, 721, 724, 728, 731, 734, 738, 742, 745, 749, 752, 756, 759, 762, 765, 769, 772, 775, 779, 783, 786, 789, 792, 796, 799, 802, 805, 809, 812, 815, 818, 822, 825, 828, 832, 836, 839, 842, 845, 849, 852, 855, 858, 862, 865, 868, 871, 875, 878, 881, 884, 888, 890, 893, 896, 900, 903, 906, 910, 914, 917, 920, 923, 926, 929, 932, 935, 939, 942, 945, 948, 952, 954, 957, 960, 964, 967, 970, 973, 977, 979, 982, 985, 989, 992, 995, 998, 1002, 1005, 1007, 1010, 1014, 1016, 1019, 1022, 1026, 1028, 1031, 1034, 1038, 1040, 1043, 1046, 1050, 1052, 1055, 1058, 1062, 1064, 1067, 1070, 1074, 1076, 1079, 1082, 1086, 1088, 1091, 1094, 1098, 1100, 1103, 1106, 1110, 1112, 1115, 1118, 1121, 1123, 1126, 1129, 1133, 1135, 1138, 1141, 1145, 1147, 1150, 1153, 1156, 1158, 1161, 1163, 1167, 1169, 1172, 1175, 1179, 1181, 1184, 1187, 1190, 1192, 1195, 1198, 1201, 1203, 1206, 1209, 1212, 1214, 1217, 1220, 1223, 1225, 1228, 1231, 1234, 1236, 1239, 1242, 1245, 1247, 1250, 1253, 1256, 1258, 1261, 1264, 1267, 1269, 1271, 1274, 1277, 1279, 1282, 1284, 1288, 1290, 1293, 1296, 1299, 1301, 1303, 1306, 1309, 1311, 1314, 1317, 1320, 1322, 1324, 1327, 1330, 1332, 1335, 1338, 1341, 1343, 1345, 1347, 1350, 1352, 1355, 1358, 1360, 1363, 1365, 1367, 1369, 1372, 1375, 1378, 1380, 1383, 1385, 1387, 1389, 1392, 1395, 1397, 1400, 1403, 1405, 1407, 1409, 1412, 1414, 1417, 1419, 1422, 1424, 1427, 1429, 1431, 1434, 1436, 1438, 1441, 1443, 1446, 1448, 1451, 1453, 1456, 1458, 1461, 1463, 1465, 1467, 1469, 1471, 1474, 1476, 1479, 1481, 1484, 1486, 1488, 1491, 1493, 1495, 1497, 1499, 1502, 1504, 1506, 1509, 1511, 1513, 1515, 1518, 1520, 1522, 1524, 1527, 1529, 1531, 1533, 1535, 1538, 1540, 1542, 1544, 1547, 1549, 1551, 1553, 1556, 1558, 1560, 1563, 1565, 1567, 1569, 1571, 1573, 1575, 1577, 1579, 1582, 1584, 1586, 1588, 1590, 1592, 1594, 1596, 1599, 1601, 1603, 1605, 1607, 1609, 1611, 1613, 1616, 1618, 1620, 1622, 1624, 1626, 1628, 1630, 1633, 1635, 1637, 1639, 1641, 1643, 1645, 1647, 1650, 1652, 1654, 1656, 1658, 1660, 1662, 1664, 1666, 1668, 1670, 1672, 1674, 1676, 1678, 1680, 1682, 1684, 1686, 1688, 1691, 1693, 1695, 1697, 1699, 1701, 1703, 1705, 1707, 1709, 1711, 1713, 1715, 1717, 1719, 1721, 1723, 1725, 1727, 1728, 1730, 1732, 1734, 1736, 1738, 1740, 1742, 1744, 1746, 1748, 1750, 1751, 1753, 1755, 1757, 1759, 1761, 1763, 1765, 1767, 1769, 1771, 1773, 1774, 1776, 1778, 1780, 1782, 1784, 1786, 1788, 1789, 1791, 1793, 1795, 1796, 1798, 1800, 1802, 1803, 1805, 1807, 1809, 1811, 1813, 1815, 1817, 1818, 1820, 1822, 1824, 1825, 1827, 1829, 1831, 1832, 1834, 1836, 1838, 1839, 1841, 1843, 1845, 1847, 1849, 1851, 1853, 1854, 1856, 1857, 1858, 1860, 1862, 1864, 1866, 1868, 1870, 1872, 1874, 1875, 1876, 1878, 1880, 1881, 1883, 1885, 1887, 1888, 1890, 1892, 1893, 1895, 1896, 1898, 1900, 1901, 1903, 1905, 1907, 1908, 1910, 1912, 1913, 1915, 1916, 1918, 1920, 1921, 1923, 1925, 1927, 1928, 1930, 1932, 1933, 1935, 1936, 1938, 1940, 1941, 1943, 1945, 1947, 1948, 1949, 1951, 1952, 1954, 1955, 1957, 1959, 1960, 1962, 1964, 1965, 1967, 1968, 1970, 1972, 1973, 1975, 1977, 1978, 1979, 1981, 1982, 1983, 1985, 1987, 1989, 1990, 1992, 1993, 1995, 1997, 1998, 2000, 2002, 2003, 2005, 2006, 2008, 2009, 2011, 2012, 2014, 2015, 2017, 2018, 2020, 2021, 2023, 2024, 2026, 2027, 2029, 2030, 2032, 2033, 2035, 2036, 2038, 2039, 2041, 2042, 2044, 2046, 2047, 2049, 2051, 2052, 2053, 2055, 2056, 2057, 2059, 2061, 2063, 2064, 2066, 2067, 2069, 2070, 2072, 2073, 2075, 2076, 2077, 2079, 2080, 2081, 2083, 2084, 2086, 2087, 2089, 2090, 2092, 2093, 2095, 2096, 2098, 2099, 2101, 2102, 2104, 2105, 2107, 2108, 2110, 2111, 2112, 2114, 2115, 2116, 2117, 2119, 2121, 2122, 2124, 2125, 2127, 2128, 2129, 2130, 2132, 2133, 2135, 2136, 2138, 2139, 2140, 2142, 2143, 2144, 2145, 2147, 2149, 2150, 2152, 2153, 2155, 2156, 2157, 2159, 2160, 2161, 2162, 2163, 2165, 2166, 2168, 2169, 2171, 2172, 2173, 2175, 2176, 2177, 2178, 2179, 2181, 2182, 2184, 2185, 2187, 2188, 2189, 2191, 2192, 2193, 2194, 2195, 2197, 2198, 2199, 2200, 2202, 2203, 2205, 2206, 2208, 2209, 2210, 2212, 2213, 2214, 2215, 2216, 2217, 2218, 2219, 2220, 2222, 2223, 2225, 2226, 2228, 2229, 2230, 2232, 2233, 2234, 2235, 2237, 2238, 2239, 2240, 2241, 2242, 2243, 2244, 2245, 2247, 2248, 2249, 2250, 2252, 2253, 2255, 2256, 2258, 2259, 2260, 2261, 2262, 2263, 2264, 2265, 2267, 2268, 2269, 2270, 2271, 2272, 2273, 2274, 2276, 2277, 2278, 2279, 2281, 2282, 2283, 2284, 2286, 2287, 2288, 2289, 2291, 2292, 2293, 2295, 2296, 2297, 2297, 2299, 2300, 2301, 2302, 2303, 2305, 2306, 2307, 2308, 2309, 2310, 2311, 2312, 2314, 2315, 2316, 2318, 2319, 2320, 2320, 2322, 2323, 2324, 2325, 2326, 2328, 2329, 2330, 2332, 2333, 2334, 2334, 2336, 2337, 2338, 2339, 2340, 2342, 2343, 2343, 2345, 2346, 2347, 2348, 2349, 2351, 2352, 2353, 2354, 2355, 2356, 2356, 2358, 2359, 2360, 2361, 2362, 2364, 2365, 2365, 2367, 2368, 2369, 2370, 2371, 2373, 2374, 2374, 2376, 2377, 2378, 2379, 2380, 2382, 2383, 2383, 2385, 2386, 2387, 2388, 2389, 2391, 2392, 2393, 2394, 2395, 2396, 2396, 2398, 2399, 2400, 2401, 2402, 2404, 2405, 2406, 2407, 2408, 2409, 2409, 2411, 2412, 2413, 2414, 2415, 2417, 2418, 2419, 2420, 2421, 2422, 2422, 2424, 2425, 2426, 2426, 2428, 2429, 2430, 2430, 2432, 2433, 2434, 2434, 2436, 2437, 2438, 2439, 2440, 2442, 2443, 2444, 2445, 2446, 2447, 2447, 2449, 2450, 2451, 2451, 2453, 2454, 2455, 2455, 2457, 2458, 2459, 2459, 2461, 2462, 2463, 2463, 2465, 2466, 2467, 2468, 2469, 2470, 2470, 2471, 2472, 2473, 2473, 2474, 2476, 2477, 2478, 2478, 2480, 2481, 2482, 2482, 2484, 2485, 2486, 2486, 2488, 2489, 2490, 2490, 2492, 2493, 2494, 2494, 2496, 2497, 2498, 2498, 2500, 2501, 2502, 2502, 2504, 2505, 2505, 2506, 2507, 2508, 2509, 2509, 2511, 2512, 2512, 2513, 2514, 2515, 2515, 2516, 2517, 2519, 2520, 2520, 2522, 2523, 2524, 2524, 2526, 2527, 2528, 2528, 2530, 2531, 2531, 2532, 2533, 2534, 2535, 2535, 2537, 2538, 2538, 2539, 2540, 2541, 2542, 2542, 2544, 2545, 2545, 2546, 2547, 2548, 2548, 2549, 2550, 2552, 2553, 2553, 2555, 2556, 2556, 2557, 2558, 2559, 2560, 2560, 2562, 2563, 2563, 2564, 2565, 2566, 2566, 2567, 2568, 2570, 2571, 2571, 2573, 2574, 2574, 2575, 2576, 2577, 2577, 2578, 2580, 2581, 2581, 2582, 2583, 2584, 2584, 2585, 2586, 2587, 2587, 2588, 2589, 2591, 2592, 2592, 2594, 2595, 2595, 2596, 2597, 2598, 2598, 2599, 2600, 2601, 2602, 2602, 2604, 2605, 2605, 2606, 2607, 2608, 2608, 2609, 2610, 2612, 2613, 2613, 2615, 2616, 2616, 2617, 2618, 2619, 2619, 2620, 2621, 2622, 2622, 2623, 2624, 2625, 2625, 2626, 2627, 2629, 2630, 2630, 2632, 2633, 2633, 2634, 2635, 2636, 2636, 2637, 2638, 2639, 2639, 2640, 2641, 2642, 2642, 2643, 2645, 2646, 2646, 2647, 2648, 2649, 2649, 2650, 2651, 2653, 2653, 2654, 2655, 2656, 2656, 2657, 2658, 2659, 2659, 2660, 2661, 2662, 2662, 2663, 2665, 2666, 2666, 2667, 2668, 2669, 2669, 2670, 2671, 2672, 2672, 2673, 2674, 2675, 2675, 2676, 2677, 2679, 2679, 2680, 2681, 2682, 2682, 2683, 2684, 2685, 2685, 2686, 2687, 2688, 2688, 2689, 2690, 2691, 2691, 2692, 2693, 2695, 2695, 2696, 2697, 2698, 2698, 2699, 2700, 2701, 2701, 2702, 2703, 2704, 2704, 2705, 2706, 2707, 2707, 2708, 2709, 2711, 2711, 2712, 2713, 2714, 2714, 2714, 2715, 2716, 2716, 2717, 2718, 2720, 2720, 2721, 2722, 2723, 2723, 2724, 2725, 2726, 2726, 2727, 2728, 2729, 2729, 2730, 2731, 2732, 2732, 2733, 2734, 2735, 2735, 2736, 2737, 2738, 2738, 2739, 2740, 2741, 2741, 2742, 2743, 2744, 2744, 2745, 2746, 2747, 2747, 2748, 2749, 2750, 2750, 2751, 2752, 2753, 2753, 2754, 2755, 2756, 2756, 2757, 2758, 2759, 2759, 2760, 2761, 2762, 2762, 2763, 2764, 2765, 2765, 2766, 2767, 2768, 2768, 2769, 2770, 2771, 2771, 2772, 2773, 2774, 2774, 2775, 2776, 2777, 2777, 2778, 2779, 2780, 2780, 2780, 2781, 2782, 2782, 2782, 2783, 2785, 2785, 2786, 2788, 2789, 2789, 2789, 2790, 2791, 2791, 2792, 2793, 2794, 2794, 2795, 2796, 2797, 2797, 2798, 2799, 2800, 2800, 2801, 2802, 2803, 2803, 2804, 2805, 2806, 2806, 2807, 2808, 2809, 2809, 2810, 2811, 2812, 2812, 2812, 2813, 2814, 2814, 2814, 2815, 2817, 2817, 2818, 2820, 2821, 2821, 2821, 2822, 2823, 2823, 2824, 2825, 2826, 2826, 2827, 2828, 2829, 2829, 2830, 2831, 2832, 2832, 2833, 2834, 2835, 2835, 2835, 2836, 2837, 2837, 2838, 2839, 2841, 2841, 2841, 2842, 2843, 2843, 2843, 2845, 2846, 2846, 2847, 2848, 2849, 2849, 2850, 2851, 2852, 2852, 2853, 2854, 2855, 2855, 2855, 2856, 2857, 2857, 2858, 2859, 2860, 2860, 2861, 2862, 2863, 2863, 2864, 2865, 2866, 2866, 2866, 2867, 2868, 2868, 2869, 2870, 2871, 2871, 2872, 2873, 2874, 2874, 2875, 2876, 2877, 2877, 2877, 2878, 2879, 2879, 2880, 2881, 2883, 2883, 2883, 2884, 2885, 2885, 2885, 2887, 2888, 2888, 2889, 2890, 2891, 2891, 2892, 2893, 2894, 2894, 2894, 2895, 2896, 2896, 2897, 2898, 2899, 2899, 2900, 2901, 2902, 2902, 2903, 2904, 2905, 2905, 2905, 2906, 2907, 2907, 2907, 2908, 2910, 2910, 2911, 2912, 2913, 2913, 2913, 2914, 2915, 2915, 2915, 2917, 2918, 2918, 2919, 2920, 2921, 2921, 2922, 2923, 2924, 2924, 2924, 2925, 2926, 2926, 2926, 2927, 2928, 2928, 2929, 2930, 2932, 2932, 2932, 2933, 2934, 2934, 2934, 2935, 2936, 2936, 2937, 2938, 2939, 2939, 2940, 2941, 2942, 2942, 2943, 2944, 2945, 2945, 2945, 2946, 2947, 2947, 2947, 2948, 2950, 2950, 2951, 2952, 2953, 2953, 2953, 2954, 2955, 2955, 2956, 2957, 2958, 2958, 2958, 2959, 2960, 2960, 2961, 2962, 2963, 2963, 2963, 2964, 2965, 2965, 2965, 2966, 2968, 2968, 2969, 2970, 2971, 2971, 2971, 2972, 2973, 2973, 2973, 2974, 2976, 2976, 2977, 2978, 2979, 2979, 2979, 2980, 2981, 2981, 2981, 2982, 2983, 2983, 2983, 2984, 2986, 2986, 2987, 2988, 2989, 2989, 2989, 2990, 2991, 2991, 2992, 2993, 2994, 2994, 2994, 2995, 2996, 2996, 2997, 2998, 2999, 2999, 2999, 3000, 3001, 3001, 3002, 3003, 3004, 3004, 3004, 3005, 3006, 3006, 3006, 3007, 3009, 3009, 3010, 3011, 3012, 3012, 3012, 3013, 3014, 3014, 3014, 3015, 3016, 3016, 3017, 3018, 3019, 3019, 3019, 3020, 3021, 3021, 3022, 3023, 3024, 3024, 3024, 3025, 3026, 3026, 3027, 3028, 3029, 3029, 3029, 3030, 3031, 3031, 3031, 3033, 3034, 3034, 3034, 3035, 3036, 3036, 3036, 3037, 3038, 3038, 3038, 3039, 3041, 3041, 3042, 3043, 3044, 3044, 3044, 3045, 3046, 3046, 3046, 3047, 3048, 3048, 3049, 3050, 3051, 3051, 3051, 3052, 3053, 3053, 3053, 3054, 3055, 3055, 3056, 3057, 3058, 3058, 3058, 3059, 3060, 3060, 3060, 3061, 3062, 3062, 3063, 3064, 3065, 3065, 3065, 3066, 3067, 3067, 3067, 3068, 3069, 3069, 3070, 3071, 3072, 3072, 3072, 3073, 3074, 3074, 3074, 3076, 3077, 3077, 3077, 3078, 3079, 3079, 3079, 3080, 3082, 3082, 3082, 3083, 3084, 3084, 3084, 3085, 3086, 3086, 3086, 3088, 3089, 3089, 3089, 3090, 3091, 3091, 3091, 3092, 3093, 3093, 3093, 3095, 3096, 3096, 3096, 3097, 3098, 3098, 3098, 3099, 3100, 3100, 3100, 3102, 3103, 3103, 3103, 3104, 3105, 3105, 3105, 3106, 3107, 3107, 3107, 3108, 3109, 3109, 3109, 3110, 3111, 3111, 3111, 3112, 3114, 3114, 3114, 3115, 3116, 3116, 3116, 3117, 3118, 3118, 3118, 3119, 3121, 3121, 3121, 3122, 3123, 3123, 3123, 3124, 3125, 3125, 3125, 3126, 3128, 3128, 3128, 3129, 3130, 3130, 3130, 3131, 3132, 3132, 3132, 3133, 3134, 3134, 3134, 3135, 3137, 3137, 3137, 3138, 3139, 3139, 3139, 3140, 3141, 3141, 3141, 3142, 3143, 3143, 3143, 3144, 3145, 3145, 3145, 3146, 3148, 3148, 3148, 3149, 3150, 3150, 3150, 3151, 3152, 3152, 3152, 3153, 3155, 3155, 3155, 3156, 3157, 3157, 3157, 3158, 3159, 3159, 3159, 3160, 3161, 3161, 3162, 3163, 3164, 3163, 3163, 3164, 3165, 3165, 3165, 3166, 3168, 3168, 3168, 3169, 3170, 3170, 3170, 3171, 3172, 3172, 3172, 3173, 3175, 3175, 3175, 3176, 3177, 3177, 3177, 3178, 3179, 3179, 3179, 3180, 3181, 3181, 3181, 3182, 3183, 3183, 3183, 3184, 3185, 3185, 3185, 3186, 3188, 3188, 3188, 3189, 3190, 3189, 3189, 3190, 3191, 3191, 3191, 3192, 3194, 3194, 3194, 3195, 3196, 3196, 3196, 3197, 3198, 3198, 3199, 3200, 3201, 3201, 3201, 3201, 3202, 3201, 3202, 3202, 3204, 3204, 3204, 3205, 3207, 3207, 3207, 3208, 3209, 3209, 3209, 3210, 3211, 3211, 3211, 3212, 3213, 3213, 3213, 3214, 3215, 3215, 3215, 3216, 3217, 3217, 3218, 3219, 3220, 3219, 3219, 3220, 3221, 3221, 3221, 3222, 3224, 3224, 3224, 3225, 3226, 3225, 3225, 3226, 3227, 3227, 3227, 3228, 3230, 3230, 3230, 3231, 3232, 3232, 3232, 3233, 3234, 3234, 3234, 3235, 3236, 3236, 3236, 3237, 3238, 3238, 3238, 3239, 3240, 3240, 3240, 3242, 3243, 3243, 3243, 3243, 3244, 3243, 3244, 3244, 3246, 3246, 3247, 3248, 3249, 3248, 3248, 3249, 3250, 3250, 3250, 3251, 3253, 3253, 3253, 3254, 3255, 3255, 3255, 3256, 3257, 3257, 3257, 3258, 3259, 3259, 3259, 3260, 3261, 3261, 3261, 3262, 3263, 3263, 3263, 3264, 3265, 3265, 3265, 3266, 3267, 3267, 3267, 3268, 3269, 3269, 3269, 3270, 3271, 3271, 3271, 3272, 3273, 3273, 3273, 3274, 3275, 3275, 3275, 3276, 3278, 3278, 3278, 3278, 3279, 3278, 3279, 3279, 3281, 3281, 3281, 3282, 3284, 3284, 3284, 3285, 3286, 3285, 3285, 3286, 3287, 3287, 3287, 3288, 3290, 3290, 3290, 3291, 3292, 3291, 3291, 3292, 3293, 3293, 3293, 3294, 3296, 3296, 3296, 3297, 3298, 3298, 3298, 3299, 3300, 3300, 3300, 3301, 3302, 3302, 3302, 3303, 3304, 3304, 3304, 3305, 3306, 3306, 3306, 3307, 3308, 3308, 3308, 3309, 3310, 3310, 3310, 3311, 3312, 3312, 3312, 3313, 3314, 3314, 3314, 3315, 3316, 3316, 3316, 3317, 3318, 3318, 3318, 3319, 3320, 3320, 3320, 3321, 3322, 3322, 3322, 3323, 3324, 3324, 3324, 3325, 3326, 3326, 3326, 3327, 3328, 3328, 3328, 3329, 3330, 3330, 3330, 3331, 3332, 3332, 3332, 3333, 3334, 3334, 3334, 3335, 3336, 3336, 3336, 3337, 3338, 3338, 3338, 3339, 3340, 3340, 3340, 3341, 3342, 3342, 3342, 3343, 3344, 3344, 3344, 3345, 3346, 3346, 3346, 3347, 3348, 3348, 3348, 3349, 3350, 3350, 3350, 3351, 3352, 3352, 3352, 3353, 3354, 3354, 3354, 3355, 3356, 3356, 3356, 3357, 3358, 3357, 3357, 3358, 3359, 3359, 3359, 3360, 3362, 3362, 3362, 3363, 3364, 3363, 3363, 3364, 3365, 3365, 3365, 3366, 3368, 3368, 3368, 3369, 3370, 3369, 3369, 3370, 3371, 3371, 3371, 3372, 3374, 3373, 3373, 3374, 3375, 3374, 3375, 3375, 3377, 3377, 3377, 3378, 3380, 3379, 3379, 3380, 3381, 3380, 3381, 3381, 3383, 3383, 3383, 3384, 3385, 3385, 3385, 3386, 3387, 3387, 3387, 3388, 3389, 3389, 3389, 3390, 3391, 3391, 3391, 3392, 3393, 3393, 3393, 3394, 3395, 3395, 3395, 3396, 3397, 3397, 3397, 3398, 3399, 3399, 3399, 3400, 3401, 3401, 3401, 3402, 3403, 3403, 3403, 3404, 3405, 3405, 3405, 3406, 3407, 3406, 3406, 3407, 3408, 3408, 3408, 3409, 3411, 3411, 3411, 3412, 3413, 3412, 3412, 3413, 3414, 3414, 3414, 3415, 3417, 3417, 3417, 3418, 3419, 3418, 3418, 3419, 3420, 3419, 3420, 3420, 3422, 3422, 3422, 3423, 3425, 3424, 3424, 3425, 3426, 3425, 3425, 3426, 3428, 3428, 3428, 3429, 3431, 3430, 3430, 3431, 3432, 3431, 3432, 3432, 3434, 3434, 3434, 3435, 3436, 3436, 3436, 3437, 3438, 3438, 3438, 3439, 3440, 3440, 3440, 3441, 3442, 3442, 3442, 3443, 3444, 3444, 3444, 3445, 3446, 3446, 3446, 3447, 3448, 3448, 3448, 3449, 3450, 3450, 3450, 3451, 3452, 3452, 3452, 3453, 3454, 3454, 3454, 3455, 3456, 3456, 3456, 3457, 3458, 3458, 3458, 3459, 3460, 3460, 3460, 3461, 3462, 3462, 3462, 3463, 3464, 3463, 3464, 3464, 3466, 3466, 3466, 3467, 3468, 3467, 3467, 3468, 3469, 3469, 3469, 3470, 3472, 3472, 3472, 3473, 3474, 3473, 3473, 3474, 3475, 3474, 3474, 3475, 3477, 3477, 3477, 3478, 3480, 3479, 3479, 3480, 3481, 3480, 3481, 3481, 3483, 3483, 3483, 3484, 3485, 3485, 3485, 3486, 3487, 3487, 3487, 3488, 3489, 3489, 3489, 3490, 3491, 3491, 3491, 3492, 3493, 3492, 3493, 3493, 3495, 3495, 3495, 3496, 3497, 3496, 3496, 3497, 3498, 3498, 3498, 3499, 3501, 3501, 3501, 3502, 3503, 3502, 3502, 3503, 3504, 3503, 3503, 3504, 3506, 3506, 3506, 3507, 3509, 3508, 3508, 3509, 3510, 3509, 3510, 3510, 3512, 3512, 3512, 3513, 3514, 3513, 3514, 3514, 3516, 3515, 3516, 3516, 3518, 3517, 3518, 3518, 3520, 3519, 3520, 3520, 3522, 3522, 3522, 3523, 3524, 3523, 3523, 3524, 3525, 3524, 3524, 3525, 3527, 3527, 3527, 3528, 3530, 3529, 3529, 3530, 3531, 3530, 3531, 3531, 3533, 3532, 3533, 3533, 3535, 3535, 3535, 3536, 3537, 3536, 3536, 3537, 3538, 3537, 3537, 3538, 3540, 3540, 3540, 3541, 3543, 3542, 3542, 3543, 3544, 3543, 3544, 3544, 3546, 3545, 3546, 3546, 3548, 3548, 3548, 3549, 3550, 3549, 3549, 3550, 3551, 3550, 3551, 3551, 3553, 3552, 3553, 3553, 3555, 3554, 3555, 3555, 3557, 3556, 3557, 3557, 3559, 3559, 3559, 3560, 3561, 3560, 3560, 3561, 3562, 3561, 3562, 3562, 3564, 3563, 3564, 3564, 3566, 3566, 3566, 3567, 3568, 3567, 3567, 3568, 3569, 3568, 3569, 3569, 3571, 3570, 3571, 3571, 3573, 3572, 3573, 3573, 3575, 3574, 3575, 3575, 3577, 3577, 3577, 3578, 3579, 3578, 3578, 3579, 3580, 3579, 3580, 3580, 3582, 3581, 3582, 3582, 3584, 3584, 3584, 3585, 3586, 3585, 3585, 3586, 3587, 3586, 3587, 3587, 3589, 3588, 3589, 3589, 3591, 3590, 3591, 3591, 3593, 3593, 3593, 3594, 3595, 3594, 3594, 3595, 3596, 3595, 3596, 3596, 3598, 3597, 3598, 3598, 3600, 3600, 3600, 3601, 3602, 3601, 3601, 3602, 3603, 3602, 3603, 3603, 3605, 3604, 3605, 3605, 3607, 3606, 3607, 3608, 3609, 3608, 3608, 3609, 3610, 3609, 3610, 3610, 3612, 3612, 3612, 3613, 3614, 3613, 3613, 3614, 3615, 3614, 3615, 3615, 3617, 3616, 3617, 3617, 3619, 3619, 3619, 3620, 3621, 3620, 3620, 3621, 3622, 3622, 3622, 3623, 3625, 3624, 3624, 3625, 3626, 3625, 3625, 3625, 3627, 3627, 3627, 3628, 3630, 3629, 3629, 3630, 3631, 3630, 3630, 3631, 3633, 3632, 3633, 3633, 3635, 3634, 3635, 3636, 3637, 3636, 3636, 3637, 3638, 3637, 3637, 3638, 3640, 3640, 3640, 3641, 3642, 3641, 3641, 3642, 3643, 3642, 3643, 3643, 3645, 3644, 3645, 3645, 3647, 3646, 3647, 3648, 3649, 3648, 3648, 3649, 3650, 3649, 3649, 3650, 3652, 3652, 3652, 3653, 3654, 3653, 3653, 3654, 3655, 3654, 3655, 3655, 3657, 3656, 3657, 3657, 3659, 3658, 3659, 3659, 3661, 3660, 3660, 3661, 3662, 3661, 3661, 3662, 3664, 3663, 3664, 3665, 3666, 3665, 3665, 3666, 3667, 3666, 3667, 3667, 3669, 3668, 3669, 3669, 3671, 3670, 3671, 3671, 3673, 3672, 3672, 3673, 3674, 3673, 3673, 3674, 3676, 3675, 3676, 3677, 3678, 3677, 3677, 3678, 3679, 3678, 3678, 3679, 3681, 3680, 3681, 3682, 3683, 3682, 3682, 3683, 3684, 3683, 3683, 3684, 3686, 3685, 3686, 3686, 3688, 3687, 3688, 3688, 3690, 3689, 3689, 3690, 3691, 3690, 3690, 3691, 3693, 3692, 3693, 3694, 3695, 3694, 3694, 3695, 3696, 3695, 3695, 3696, 3698, 3697, 3698, 3699, 3700, 3699, 3699, 3700, 3701, 3700, 3700, 3701, 3703, 3702, 3703, 3703, 3705, 3704, 3705, 3705, 3707, 3706, 3706, 3707, 3708, 3707, 3707, 3708, 3710, 3709, 3710, 3710, 3712, 3711, 3711, 3712, 3713, 3712, 3712, 3713, 3715, 3714, 3715, 3715, 3717, 3716, 3716, 3717, 3718, 3717, 3717, 3718, 3720, 3719, 3720, 3720, 3722, 3721, 3722, 3722, 3724, 3723, 3723, 3724, 3725, 3724, 3724, 3724, 3726, 3726, 3726, 3727, 3729, 3728, 3728, 3729, 3730, 3729, 3730, 3730, 3732, 3731, 3731, 3731, 3733, 3733, 3733, 3734, 3736, 3735, 3735, 3736, 3737, 3736, 3736, 3736, 3738, 3737, 3737, 3738, 3740, 3739, 3740, 3740, 3742, 3741, 3742, 3742, 3744, 3743, 3743, 3744, 3745, 3744, 3744, 3745, 3747, 3746, 3747, 3747, 3749, 3748, 3749, 3749, 3751, 3750, 3750, 3751, 3752, 3751, 3751, 3752, 3754, 3753, 3754, 3754, 3756, 3755, 3756, 3756, 3758, 3757, 3757, 3758, 3759, 3758, 3758, 3759, 3761, 3760, 3761, 3761, 3763, 3762, 3763, 3763, 3765, 3764, 3764, 3765, 3766, 3765, 3765, 3766, 3768, 3767, 3768, 3768, 3770, 3769, 3770, 3770, 3772, 3771, 3771, 3772, 3773, 3772, 3772, 3773, 3775, 3774, 3775, 3775, 3777, 3776, 3777, 3777, 3779, 3778, 3778, 3779, 3780, 3779, 3779, 3780, 3782, 3781, 3782, 3782, 3784, 3783, 3783, 3784, 3786, 3785, 3786, 3786, 3788, 3787, 3787, 3788, 3789, 3788, 3788, 3789, 3791, 3790, 3791, 3791, 3793, 3792, 3792, 3793, 3795, 3794, 3795, 3795, 3797, 3796, 3796, 3797, 3798, 3797, 3797, 3798, 3800, 3799, 3800, 3800, 3802, 3801, 3801, 3802, 3804, 3803, 3804, 3804, 3806, 3805, 3805, 3806, 3807, 3806, 3806, 3807, 3809, 3808, 3809, 3809, 3811, 3810, 3810, 3811, 3813, 3812, 3813, 3813, 3815, 3814, 3814, 3815, 3816, 3815, 3815, 3816, 3818, 3817, 3818, 3818, 3820, 3819, 3820, 3820, 3822, 3821, 3821, 3822, 3824, 3823, 3824, 3824, 3826, 3825, 3825, 3826, 3827, 3826, 3826, 3827, 3829, 3828, 3829, 3829, 3831, 3830, 3830, 3831, 3833, 3832, 3833, 3833, 3835, 3834, 3834, 3835, 3836, 3835, 3835, 3836, 3838, 3837, 3838, 3838, 3840, 3839, 3839, 3840, 3842, 3841, 3842, 3842, 3844, 3843, 3843, 3844, 3845, 3844, 3844, 3845, 3847, 3846, 3847, 3847, 3849, 3848, 3848, 3849, 3850, 3849, 3849, 3850, 3852, 3851, 3852, 3852, 3854, 3853, 3853, 3854, 3856, 3855, 3856, 3856, 3858, 3857, 3857, 3858, 3859, 3858, 3858, 3859, 3861, 3860, 3861, 3861, 3863, 3862, 3862, 3863, 3865, 3864, 3865, 3865, 3867, 3866, 3866, 3867, 3868, 3867, 3867, 3868, 3870, 3869, 3869, 3870, 3872, 3871, 3872, 3872, 3874, 3873, 3873, 3874, 3875, 3874, 3874, 3875, 3877, 3876, 3877, 3877, 3879, 3878, 3878, 3879, 3881, 3880, 3881, 3881, 3883, 3882, 3882, 3882, 3884, 3883, 3883, 3884, 3886, 3885, 3885, 3886, 3887, 3886, 3886, 3887, 3889, 3888, 3888, 3889, 3891, 3890, 3891, 3891, 3893, 3892, 3892, 3892, 3894, 3893, 3893, 3894, 3896, 3895, 3895, 3896, 3898, 3897, 3898, 3898, 3900, 3899, 3899, 3899, 3901, 3900, 3900, 3901, 3903, 3902, 3902, 3903, 3904, 3903, 3903, 3904, 3906, 3905, 3905, 3906, 3908, 3907, 3908, 3908, 3910, 3909, 3909, 3909, 3911, 3910, 3910, 3911, 3913, 3912, 3912, 3913, 3915, 3914, 3915, 3915, 3917, 3916, 3916, 3916, 3918, 3917, 3917, 3918, 3920, 3919, 3919, 3920, 3921, 3920, 3920, 3921, 3923, 3922, 3922, 3923, 3925, 3924, 3925, 3925, 3927, 3926, 3926, 3926, 3928, 3927, 3927, 3928, 3930, 3929, 3929, 3930, 3932, 3931, 3932, 3932, 3934, 3933, 3933, 3933, 3935, 3934, 3934, 3935, 3937, 3936, 3936, 3936, 3938, 3937, 3937, 3938, 3940, 3939, 3939, 3940, 3942, 3941, 3942, 3942, 3944, 3943, 3943, 3943, 3945, 3944, 3944, 3945, 3947, 3946, 3946, 3947, 3949, 3948, 3949, 3949, 3951, 3950, 3950, 3950, 3952, 3951, 3951, 3952, 3954, 3953, 3953, 3953, 3955, 3954, 3954, 3955, 3957, 3956, 3957, 3957, 3959, 3958, 3958, 3958, 3960, 3959, 3959, 3960, 3962, 3961, 3961, 3961, 3963, 3962, 3962, 3963, 3965, 3964, 3964, 3965, 3967, 3966, 3967, 3967, 3969, 3968, 3968, 3968, 3970, 3969, 3969, 3970, 3972, 3971, 3971, 3972, 3974, 3973, 3974, 3974, 3976, 3975, 3975, 3975, 3977, 3976, 3976, 3977, 3979, 3978, 3978, 3978, 3980, 3979, 3979, 3980, 3982, 3981, 3981, 3982, 3984, 3983, 3983, 3984, 3986, 3985, 3986, 3986, 3988, 3987, 3987, 3987, 3989, 3988, 3988, 3989, 3991, 3990, 3990, 3990, 3992, 3991, 3991, 3992, 3994, 3993, 3993, 3994, 3996, 3995, 3995, 3996, 3998, 3997, 3997, 3997, 3999, 3998, 3998, 3999, 4001, 4000, 4000, 4001, 4003, 4002, 4002, 4003, 4005, 4004, 4004, 4004, 4006, 4005, 4005, 4006, 4008, 4007, 4007, 4007, 4009, 4008, 4008, 4009, 4011, 4010, 4010, 4011, 4013, 4012, 4012, 4013, 4015, 4014, 4014, 4014, 4016, 4015, 4015, 4016, 4018, 4017, 4017, 4017, 4019, 4018, 4018, 4019, 4021, 4020, 4020, 4021, 4023, 4022, 4022, 4023, 4025, 4024, 4024, 4025, 4027, 4026, 4026, 4026, 4028, 4027, 4027, 4028, 4030, 4029, 4029, 4029, 4031, 4030, 4030, 4031, 4033, 4032, 4032, 4033, 4035, 4034, 4034, 4035, 4037, 4036, 4036, 4036, 4038, 4037, 4037, 4038, 4040, 4039, 4039, 4039, 4041, 4040, 4040, 4041, 4043, 4042, 4042, 4043, 4045, 4044, 4044, 4045, 4047, 4046, 4046, 4047, 4049, 4048, 4048, 4048, 4050, 4049, 4049, 4050, 4052, 4051, 4051, 4051, 4053, 4052, 4052, 4053, 4055, 4054, 4054, 4055, 4057, 4056, 4056, 4057, 4059, 4058, 4058, 4058, 4060, 4059, 4059, 4060, 4062, 4061, 4061, 4061, 4062, 4062, 4062, 4063, 4064, 4064, 4064, 4065, 4066, 4066, 4066, 4067, 4068, 4068, 4068, 4069, 4070, 4070, 4070, 4070, 4071, 4071, 4071, 4072, 4073, 4073, 4073, 4073, 4074, 4074, 4074, 4075, 4076, 4076, 4076, 4077, 4078, 4078, 4078, 4079, 4080, 4080, 4080, 4080, 4081, 4081, 4081, 4082, 4083, 4083, 4083, 4083, 4084, 4084, 4084, 4085, 4086, 4086, 4086, 4087, 4088, 4088, 4088, 4089, 4090, 4090, 4091, 4092, 4093, 4093, 4094, 4095] + # 14-bit + gamma_lut_14: [0, 11, 22, 32, 43, 53, 64, 74, 83, 93, 102, 110, 119, 127, 134, 141, 148, 154, 160, 165, 170, 174, 178, 182, 186, 190, 193, 196, 199, 202, 205, 209, 212, 215, 219, 223, 227, 231, 235, 239, 244, 248, 252, 257, 262, 266, 271, 275, 280, 284, 288, 293, 297, 301, 305, 309, 313, 317, 321, 325, 329, 332, 336, 340, 344, 348, 352, 356, 360, 364, 368, 372, 376, 380, 384, 388, 392, 396, 400, 404, 408, 412, 416, 420, 424, 427, 431, 435, 439, 443, 447, 451, 455, 459, 464, 468, 472, 476, 480, 484, 489, 493, 497, 501, 506, 510, 514, 519, 523, 527, 531, 536, 540, 544, 548, 552, 556, 560, 564, 568, 572, 576, 580, 584, 588, 592, 596, 600, 604, 608, 612, 616, 620, 623, 627, 631, 636, 639, 643, 647, 652, 656, 660, 664, 668, 672, 676, 680, 684, 688, 692, 696, 700, 704, 708, 712, 716, 720, 724, 728, 732, 736, 739, 743, 747, 751, 755, 759, 763, 767, 771, 775, 779, 783, 787, 792, 796, 800, 804, 808, 813, 817, 821, 825, 830, 834, 838, 842, 847, 851, 855, 860, 864, 868, 872, 876, 880, 884, 887, 891, 896, 899, 903, 907, 912, 915, 919, 924, 928, 932, 936, 940, 944, 948, 953, 957, 961, 966, 970, 974, 979, 983, 987, 991, 996, 1000, 1004, 1008, 1012, 1016, 1020, 1024, 1028, 1032, 1036, 1040, 1044, 1048, 1052, 1056, 1060, 1064, 1067, 1071, 1075, 1079, 1083, 1087, 1091, 1095, 1099, 1103, 1107, 1111, 1115, 1120, 1124, 1128, 1131, 1135, 1140, 1143, 1147, 1151, 1156, 1159, 1163, 1167, 1172, 1175, 1179, 1184, 1188, 1191, 1195, 1199, 1203, 1207, 1211, 1215, 1219, 1223, 1227, 1231, 1235, 1239, 1243, 1247, 1252, 1256, 1260, 1264, 1268, 1272, 1277, 1281, 1285, 1289, 1294, 1298, 1303, 1307, 1311, 1315, 1320, 1324, 1327, 1332, 1336, 1339, 1343, 1347, 1352, 1355, 1359, 1363, 1368, 1371, 1375, 1379, 1384, 1387, 1391, 1395, 1400, 1403, 1407, 1411, 1416, 1420, 1423, 1428, 1432, 1436, 1440, 1444, 1448, 1451, 1455, 1458, 1462, 1465, 1469, 1473, 1477, 1480, 1484, 1488, 1492, 1495, 1499, 1503, 1508, 1511, 1515, 1520, 1524, 1528, 1532, 1537, 1541, 1545, 1549, 1554, 1559, 1563, 1567, 1571, 1576, 1579, 1583, 1587, 1591, 1594, 1598, 1602, 1606, 1609, 1613, 1616, 1621, 1624, 1628, 1632, 1636, 1639, 1643, 1647, 1651, 1655, 1658, 1663, 1667, 1671, 1675, 1679, 1683, 1687, 1691, 1695, 1700, 1703, 1707, 1711, 1715, 1718, 1722, 1726, 1730, 1733, 1737, 1741, 1745, 1748, 1752, 1756, 1760, 1763, 1766, 1770, 1774, 1778, 1781, 1785, 1789, 1792, 1796, 1800, 1804, 1808, 1811, 1815, 1820, 1823, 1827, 1830, 1834, 1838, 1841, 1845, 1849, 1853, 1856, 1860, 1864, 1868, 1871, 1875, 1880, 1883, 1886, 1890, 1894, 1898, 1901, 1905, 1909, 1912, 1916, 1920, 1924, 1928, 1931, 1935, 1940, 1943, 1946, 1950, 1954, 1958, 1961, 1965, 1969, 1972, 1976, 1980, 1984, 1988, 1991, 1995, 2000, 2003, 2006, 2010, 2014, 2017, 2021, 2025, 2029, 2032, 2036, 2040, 2044, 2048, 2051, 2055, 2060, 2063, 2067, 2070, 2074, 2078, 2081, 2085, 2089, 2093, 2096, 2100, 2105, 2108, 2112, 2116, 2120, 2123, 2126, 2129, 2133, 2136, 2139, 2143, 2147, 2150, 2153, 2157, 2161, 2164, 2168, 2171, 2176, 2179, 2182, 2186, 2190, 2193, 2197, 2201, 2205, 2208, 2212, 2216, 2220, 2224, 2227, 2231, 2236, 2239, 2242, 2245, 2249, 2252, 2255, 2259, 2263, 2266, 2269, 2273, 2277, 2280, 2284, 2287, 2292, 2295, 2298, 2302, 2306, 2309, 2313, 2317, 2321, 2324, 2328, 2332, 2336, 2340, 2343, 2347, 2352, 2355, 2358, 2362, 2365, 2368, 2372, 2375, 2379, 2382, 2386, 2389, 2393, 2396, 2400, 2404, 2408, 2410, 2414, 2417, 2421, 2424, 2427, 2431, 2435, 2438, 2441, 2445, 2449, 2452, 2456, 2460, 2464, 2466, 2470, 2473, 2477, 2480, 2483, 2486, 2490, 2493, 2497, 2501, 2505, 2508, 2511, 2515, 2520, 2523, 2526, 2530, 2534, 2537, 2541, 2545, 2549, 2552, 2556, 2560, 2564, 2568, 2571, 2575, 2580, 2583, 2586, 2589, 2593, 2596, 2600, 2603, 2607, 2610, 2613, 2617, 2621, 2624, 2628, 2631, 2636, 2638, 2641, 2645, 2649, 2652, 2655, 2658, 2662, 2665, 2669, 2673, 2677, 2680, 2683, 2687, 2691, 2694, 2698, 2701, 2705, 2708, 2712, 2715, 2719, 2722, 2726, 2729, 2733, 2737, 2740, 2744, 2747, 2750, 2753, 2756, 2760, 2762, 2765, 2768, 2772, 2775, 2778, 2781, 2785, 2788, 2792, 2795, 2799, 2802, 2806, 2810, 2814, 2817, 2820, 2824, 2829, 2832, 2836, 2840, 2844, 2847, 2851, 2855, 2859, 2862, 2865, 2869, 2872, 2875, 2878, 2881, 2885, 2888, 2891, 2894, 2898, 2901, 2904, 2908, 2911, 2914, 2917, 2920, 2924, 2927, 2930, 2934, 2938, 2941, 2944, 2948, 2952, 2956, 2959, 2963, 2967, 2970, 2974, 2977, 2981, 2984, 2987, 2991, 2995, 2998, 3001, 3005, 3009, 3012, 3016, 3019, 3023, 3026, 3029, 3032, 3036, 3038, 3041, 3045, 3048, 3051, 3054, 3058, 3062, 3064, 3068, 3071, 3075, 3078, 3081, 3085, 3089, 3091, 3095, 3098, 3102, 3105, 3109, 3113, 3117, 3120, 3123, 3127, 3131, 3134, 3137, 3140, 3144, 3147, 3150, 3153, 3157, 3160, 3163, 3166, 3170, 3173, 3176, 3179, 3183, 3186, 3189, 3192, 3196, 3198, 3201, 3205, 3208, 3211, 3214, 3218, 3222, 3225, 3228, 3231, 3235, 3238, 3241, 3244, 3247, 3250, 3253, 3256, 3260, 3263, 3266, 3269, 3273, 3276, 3279, 3283, 3287, 3290, 3293, 3297, 3301, 3303, 3306, 3310, 3314, 3317, 3321, 3324, 3329, 3332, 3335, 3339, 3343, 3346, 3349, 3352, 3356, 3359, 3361, 3365, 3369, 3371, 3374, 3378, 3382, 3385, 3388, 3391, 3395, 3398, 3401, 3404, 3408, 3410, 3413, 3416, 3420, 3423, 3426, 3429, 3434, 3436, 3440, 3443, 3447, 3450, 3453, 3456, 3460, 3462, 3465, 3468, 3472, 3475, 3478, 3481, 3486, 3488, 3492, 3495, 3499, 3502, 3505, 3508, 3512, 3514, 3517, 3521, 3525, 3527, 3530, 3534, 3538, 3541, 3544, 3547, 3551, 3554, 3556, 3559, 3562, 3564, 3567, 3570, 3574, 3576, 3579, 3582, 3586, 3589, 3592, 3595, 3599, 3602, 3605, 3608, 3612, 3615, 3618, 3622, 3626, 3629, 3632, 3636, 3641, 3644, 3647, 3651, 3655, 3658, 3660, 3664, 3667, 3669, 3672, 3675, 3679, 3681, 3684, 3687, 3691, 3693, 3696, 3699, 3703, 3706, 3708, 3711, 3715, 3717, 3720, 3724, 3728, 3730, 3733, 3737, 3741, 3744, 3747, 3751, 3755, 3758, 3761, 3764, 3768, 3770, 3773, 3777, 3781, 3783, 3786, 3790, 3794, 3797, 3800, 3803, 3807, 3809, 3812, 3815, 3819, 3821, 3823, 3826, 3830, 3832, 3835, 3838, 3842, 3845, 3848, 3851, 3855, 3858, 3860, 3864, 3867, 3870, 3873, 3876, 3880, 3883, 3886, 3889, 3894, 3896, 3900, 3903, 3907, 3909, 3912, 3915, 3919, 3921, 3923, 3926, 3930, 3932, 3935, 3938, 3942, 3945, 3948, 3951, 3955, 3958, 3960, 3963, 3967, 3970, 3972, 3976, 3980, 3982, 3985, 3989, 3993, 3996, 3999, 4003, 4007, 4010, 4012, 4015, 4019, 4021, 4023, 4027, 4031, 4033, 4035, 4039, 4043, 4045, 4048, 4051, 4055, 4057, 4060, 4063, 4066, 4068, 4071, 4074, 4078, 4080, 4083, 4086, 4090, 4093, 4096, 4099, 4103, 4105, 4108, 4111, 4114, 4116, 4119, 4122, 4126, 4128, 4131, 4134, 4138, 4141, 4144, 4147, 4151, 4153, 4156, 4159, 4162, 4164, 4167, 4170, 4174, 4176, 4179, 4182, 4186, 4189, 4192, 4195, 4199, 4201, 4204, 4207, 4210, 4212, 4215, 4218, 4222, 4224, 4227, 4230, 4234, 4237, 4240, 4243, 4247, 4249, 4252, 4255, 4258, 4260, 4263, 4266, 4270, 4272, 4275, 4278, 4282, 4285, 4288, 4291, 4295, 4297, 4300, 4303, 4306, 4308, 4311, 4314, 4318, 4320, 4323, 4326, 4330, 4333, 4336, 4339, 4343, 4345, 4348, 4351, 4354, 4356, 4359, 4362, 4366, 4368, 4371, 4374, 4378, 4381, 4384, 4387, 4391, 4393, 4396, 4399, 4403, 4405, 4407, 4410, 4414, 4416, 4419, 4423, 4427, 4429, 4432, 4435, 4439, 4441, 4443, 4446, 4449, 4451, 4453, 4456, 4460, 4462, 4464, 4467, 4471, 4473, 4476, 4479, 4483, 4485, 4487, 4490, 4494, 4496, 4498, 4501, 4505, 4507, 4510, 4514, 4518, 4520, 4523, 4527, 4531, 4533, 4536, 4539, 4543, 4544, 4547, 4550, 4554, 4556, 4559, 4563, 4567, 4569, 4572, 4575, 4579, 4581, 4583, 4586, 4590, 4591, 4594, 4597, 4600, 4602, 4604, 4608, 4611, 4614, 4616, 4619, 4623, 4625, 4627, 4630, 4633, 4634, 4637, 4640, 4643, 4645, 4648, 4651, 4655, 4657, 4660, 4663, 4667, 4669, 4671, 4674, 4678, 4680, 4682, 4686, 4690, 4692, 4695, 4698, 4702, 4705, 4708, 4711, 4715, 4717, 4719, 4722, 4726, 4727, 4729, 4733, 4736, 4738, 4740, 4744, 4747, 4749, 4752, 4755, 4759, 4761, 4763, 4766, 4769, 4771, 4773, 4776, 4780, 4781, 4784, 4787, 4791, 4793, 4796, 4799, 4803, 4805, 4807, 4810, 4813, 4815, 4817, 4820, 4824, 4826, 4828, 4831, 4835, 4837, 4840, 4843, 4847, 4849, 4851, 4854, 4857, 4859, 4861, 4864, 4868, 4869, 4872, 4875, 4879, 4881, 4884, 4887, 4891, 4893, 4895, 4898, 4901, 4903, 4905, 4908, 4912, 4913, 4916, 4919, 4923, 4925, 4928, 4931, 4935, 4937, 4939, 4942, 4945, 4947, 4949, 4952, 4956, 4957, 4960, 4963, 4967, 4969, 4972, 4975, 4979, 4981, 4983, 4986, 4989, 4990, 4993, 4996, 5000, 5001, 5004, 5007, 5011, 5013, 5016, 5019, 5023, 5025, 5027, 5030, 5033, 5035, 5037, 5040, 5044, 5046, 5048, 5051, 5055, 5057, 5060, 5063, 5067, 5068, 5070, 5073, 5076, 5077, 5079, 5082, 5086, 5087, 5089, 5092, 5096, 5098, 5100, 5103, 5107, 5108, 5110, 5113, 5117, 5118, 5120, 5123, 5127, 5129, 5131, 5135, 5139, 5141, 5144, 5147, 5151, 5153, 5155, 5158, 5161, 5163, 5165, 5168, 5172, 5174, 5176, 5180, 5183, 5185, 5188, 5191, 5195, 5196, 5198, 5201, 5204, 5205, 5207, 5210, 5213, 5215, 5217, 5220, 5224, 5226, 5228, 5231, 5235, 5237, 5239, 5241, 5245, 5246, 5249, 5252, 5256, 5257, 5260, 5263, 5267, 5269, 5272, 5275, 5279, 5280, 5282, 5285, 5288, 5289, 5291, 5294, 5297, 5299, 5301, 5304, 5308, 5309, 5312, 5315, 5319, 5321, 5323, 5326, 5329, 5331, 5333, 5336, 5340, 5342, 5344, 5347, 5351, 5353, 5356, 5359, 5363, 5364, 5366, 5368, 5371, 5372, 5374, 5376, 5379, 5380, 5382, 5385, 5389, 5390, 5392, 5395, 5399, 5400, 5402, 5405, 5409, 5410, 5412, 5416, 5419, 5421, 5424, 5427, 5431, 5433, 5436, 5439, 5443, 5444, 5446, 5448, 5451, 5452, 5454, 5456, 5459, 5461, 5462, 5465, 5469, 5470, 5472, 5475, 5479, 5480, 5482, 5485, 5489, 5490, 5492, 5495, 5499, 5501, 5504, 5507, 5511, 5513, 5516, 5519, 5523, 5524, 5526, 5528, 5531, 5532, 5534, 5536, 5539, 5540, 5542, 5545, 5549, 5550, 5552, 5555, 5559, 5560, 5562, 5565, 5568, 5570, 5572, 5575, 5579, 5581, 5583, 5587, 5591, 5593, 5596, 5599, 5603, 5604, 5606, 5608, 5611, 5612, 5614, 5617, 5620, 5621, 5623, 5626, 5629, 5630, 5633, 5635, 5639, 5640, 5642, 5644, 5647, 5648, 5650, 5653, 5657, 5658, 5660, 5663, 5667, 5669, 5672, 5675, 5679, 5680, 5682, 5685, 5688, 5689, 5691, 5694, 5698, 5699, 5701, 5704, 5708, 5710, 5712, 5715, 5719, 5720, 5721, 5724, 5727, 5728, 5729, 5732, 5735, 5736, 5738, 5741, 5745, 5746, 5748, 5751, 5755, 5756, 5758, 5760, 5763, 5764, 5766, 5769, 5773, 5774, 5776, 5779, 5783, 5785, 5788, 5791, 5795, 5796, 5798, 5801, 5804, 5805, 5807, 5810, 5814, 5815, 5817, 5820, 5824, 5826, 5828, 5831, 5835, 5836, 5838, 5840, 5843, 5844, 5846, 5848, 5852, 5853, 5855, 5857, 5861, 5862, 5864, 5867, 5871, 5872, 5873, 5875, 5878, 5879, 5881, 5883, 5887, 5888, 5890, 5893, 5896, 5898, 5900, 5903, 5907, 5908, 5910, 5912, 5916, 5917, 5919, 5922, 5925, 5927, 5929, 5932, 5936, 5938, 5940, 5943, 5947, 5948, 5950, 5952, 5955, 5956, 5958, 5960, 5964, 5965, 5966, 5969, 5973, 5974, 5976, 5979, 5983, 5984, 5985, 5988, 5991, 5991, 5993, 5996, 5999, 6000, 6002, 6005, 6009, 6010, 6012, 6015, 6019, 6020, 6021, 6024, 6027, 6027, 6029, 6032, 6035, 6036, 6038, 6041, 6045, 6046, 6048, 6051, 6055, 6056, 6057, 6060, 6063, 6063, 6065, 6068, 6071, 6072, 6074, 6077, 6081, 6082, 6084, 6087, 6091, 6092, 6093, 6096, 6099, 6099, 6101, 6104, 6107, 6108, 6110, 6113, 6117, 6118, 6120, 6123, 6127, 6128, 6129, 6132, 6135, 6135, 6137, 6140, 6143, 6144, 6146, 6149, 6153, 6154, 6156, 6159, 6163, 6164, 6165, 6168, 6171, 6171, 6173, 6176, 6179, 6180, 6182, 6185, 6189, 6190, 6192, 6195, 6199, 6200, 6201, 6203, 6207, 6207, 6209, 6211, 6215, 6216, 6218, 6221, 6224, 6226, 6228, 6231, 6235, 6236, 6237, 6240, 6243, 6244, 6245, 6248, 6252, 6253, 6254, 6257, 6261, 6262, 6264, 6267, 6271, 6271, 6273, 6275, 6278, 6278, 6279, 6282, 6285, 6286, 6287, 6290, 6293, 6294, 6296, 6299, 6303, 6304, 6305, 6307, 6310, 6311, 6313, 6315, 6319, 6320, 6322, 6325, 6329, 6330, 6332, 6335, 6339, 6339, 6341, 6343, 6346, 6346, 6347, 6350, 6353, 6354, 6355, 6358, 6361, 6363, 6364, 6367, 6371, 6372, 6373, 6375, 6378, 6379, 6381, 6383, 6387, 6388, 6390, 6393, 6397, 6398, 6400, 6403, 6407, 6407, 6409, 6411, 6414, 6414, 6415, 6418, 6421, 6422, 6423, 6426, 6429, 6430, 6432, 6435, 6439, 6440, 6441, 6443, 6446, 6447, 6449, 6451, 6455, 6456, 6458, 6461, 6465, 6466, 6468, 6471, 6475, 6475, 6477, 6479, 6482, 6482, 6483, 6486, 6489, 6490, 6491, 6494, 6497, 6498, 6500, 6503, 6507, 6507, 6509, 6511, 6514, 6515, 6517, 6519, 6523, 6524, 6526, 6529, 6533, 6534, 6536, 6539, 6543, 6543, 6545, 6547, 6550, 6550, 6551, 6554, 6557, 6558, 6559, 6562, 6565, 6566, 6568, 6571, 6575, 6575, 6577, 6579, 6582, 6583, 6584, 6587, 6591, 6592, 6594, 6597, 6600, 6602, 6604, 6607, 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16335, 16335, 16337, 16341, 16338, 16336, 16337, 16339, 16336, 16334, 16336, 16340, 16337, 16336, 16339, 16343, 16342, 16342, 16345, 16349, 16346, 16344, 16345, 16348, 16344, 16343, 16345, 16349, 16346, 16345, 16347, 16352, 16350, 16350, 16353, 16357, 16354, 16352, 16353, 16355, 16352, 16351, 16352, 16356, 16353, 16353, 16355, 16359, 16358, 16358, 16361, 16365, 16362, 16360, 16361, 16364, 16361, 16360, 16362, 16366, 16363, 16363, 16366, 16370, 16369, 16369, 16372, 16377, 16374, 16373, 16374, 16377, 16374, 16373, 16375, 16379, 16376, 16376, 16379, 16383, 16381, 16381, 16383] + is_save: False + +auto_exposure: + is_enable: True + is_debug: True + stats_window_offset: [4, 4, 4, 4] + center_illuminance: 90 + histogram_skewness: 1 + is_save: False + +color_space_conversion: + conv_standard: 2 + is_save: False + +2d_noise_reduction: + is_enable: True + window_size: 5 + wts: 5 + is_save: False + +rgb_conversion: + is_enable: True + is_save: False + +invalid_region_crop: + # 1: 1920x1080, 2: 1920x1440 + is_enable: False + crop_to_size: 2 + height_start_idx: 5 + width_start_idx: 6 + is_debug: True + is_save: False + +on_screen_display: + is_enable: True + is_debug: False + height: 64 + width: 128 + x_offset: 50 + y_offset: 50 + fg_color: [0, 90, 160] + bg_color: [255, 255, 255] + alpha: 50 + is_save: False + +scale: + is_enable: False + is_debug: True + new_width: 1920 + new_height: 1080 + is_save: False + +yuv_conversion_format: + is_enable: False + conv_type: '444' + is_save: False + diff --git a/tests/test_data/Indoor1_2592x1536_10bit_GRBG.raw b/tests/test_data/Indoor1_2592x1536_10bit_GRBG.raw new file mode 100644 index 0000000000000000000000000000000000000000..203932b50cc66b412eef023a892e038efd403c28 GIT binary patch literal 7962624 zcmXt>Wq1}x7lvmBcZx%cON+a^ySuv;EpAB&B!Q412^OSKN~yQBv_;xNvEuIT?(Xv4 z&%FJ9%r(0+$L7rL?C#lT&+aty%w`i~Hkr@OZWCwroB3?V(H3X6n#E?jnL}HgIcUD7 z{>Gey?zs8N9D(k*S!xcLg=U9YV2+wE%_+)G^M%<5?QZI0loMu&IS#r%qlRpy5I!Q3%F(!RpnrR@s+ 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to run unittests +1. Install pytest using pip install pytest +2. Run command “python -m pytest ” in terminal diff --git a/tests/test_data/default_configs.yml b/tests/test_data/default_configs.yml new file mode 100644 index 0000000..4feb6ce --- /dev/null +++ b/tests/test_data/default_configs.yml @@ -0,0 +1,164 @@ +platform: + filename: ColorChecker_2592x1536_10bit_GRBG.raw + disable_progress_bar: False + leave_pbar_string: False + save_lut: False + save_format: npy + # png # npy # both + render_3a: False + +sensor_info: + bayer_pattern: grbg + range: 1023 + bit_depth: 10 + width: 2592 + height: 1536 + +crop: + is_enable: True + is_debug: False + new_width: 2592 + new_height: 1536 + is_save: False + +dead_pixel_correction: + is_enable: True + dp_threshold: 20 + is_debug: True + is_save: False + +black_level_correction: + is_enable: True + is_debug: True + r_offset: 50 + gr_offset: 50 + gb_offset: 50 + b_offset: 50 + is_linear: True + r_sat: 1023 + gr_sat: 1023 + gb_sat: 1023 + b_sat: 1023 + is_save: False + +oecf: + is_enable: True + # Make sure the LUT has the right bit range i.e. if image is of 10 bit LUT should be from [0 - (2^10)-1] + # LUT here does nothing to the sensor response i.e. a value of 800 maps to 800 and 2000 maps to 2000 + r_lut: 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,3222,3223,3224,3225,3226,3227,3228,3229,3230,3231,3232,3233,3234,3235,3236,3237,3238,3239,3240,3241,3242,3243,3244,3245,3246,3247,3248,3249,3250,3251,3252,3253,3254,3255,3256,3257,3258,3259,3260,3261,3262,3263,3264,3265,3266,3267,3268,3269,3270,3271,3272,3273,3274,3275,3276,3277,3278,3279,3280,3281,3282,3283,3284,3285,3286,3287,3288,3289,3290,3291,3292,3293,3294,3295,3296,3297,3298,3299,3300,3301,3302,3303,3304,3305,3306,3307,3308,3309,3310,3311,3312,3313,3314,3315,3316,3317,3318,3319,3320,3321,3322,3323,3324,3325,3326,3327,3328,3329,3330,3331,3332,3333,3334,3335,3336,3337,3338,3339,3340,3341,3342,3343,3344,3345,3346,3347,3348,3349,3350,3351,3352,3353,3354,3355,3356,3357,3358,3359,3360,3361,3362,3363,3364,3365,3366,3367,3368,3369,3370,3371,3372,3373,3374,3375,3376,3377,3378,3379,3380,3381,3382,3383,3384,3385,3386,3387,3388,3389,3390,3391,3392,3393,3394,3395,3396,3397,3398,3399,3400,3401,3402,3403,3404,3405,3406,3407,3408,3409,3410,3411,3412,3413,3414,3415,3416,3417,3418,3419,3420,3421,3422,3423,3424,3425,3426,3427,3428,3429,3430,3431,3432,3433,3434,3435,3436,3437,3438,3439,3440,3441,3442,3443,3444,3445,3446,3447,3448,3449,3450,3451,3452,3453,3454,3455,3456,3457,3458,3459,3460,3461,3462,3463,3464,3465,3466,3467,3468,3469,3470,3471,3472,3473,3474,3475,3476,3477,3478,3479,3480,3481,3482,3483,3484,3485,3486,3487,3488,3489,3490,3491,3492,3493,3494,3495,3496,3497,3498,3499,3500,3501,3502,3503,3504,3505,3506,3507,3508,3509,3510,3511,3512,3513,3514,3515,3516,3517,3518,3519,3520,3521,3522,3523,3524,3525,3526,3527,3528,3529,3530,3531,3532,3533,3534,3535,3536,3537,3538,3539,3540,3541,3542,3543,3544,3545,3546,3547,3548,3549,3550,3551,3552,3553,3554,3555,3556,3557,3558,3559,3560,3561,3562,3563,3564,3565,3566,3567,3568,3569,3570,3571,3572,3573,3574,3575,3576,3577,3578,3579,3580,3581,3582,3583,3584,3585,3586,3587,3588,3589,3590,3591,3592,3593,3594,3595,3596,3597,3598,3599,3600,3601,3602,3603,3604,3605,3606,3607,3608,3609,3610,3611,3612,3613,3614,3615,3616,3617,3618,3619,3620,3621,3622,3623,3624,3625,3626,3627,3628,3629,3630,3631,3632,3633,3634,3635,3636,3637,3638,3639,3640,3641,3642,3643,3644,3645,3646,3647,3648,3649,3650,3651,3652,3653,3654,3655,3656,3657,3658,3659,3660,3661,3662,3663,3664,3665,3666,3667,3668,3669,3670,3671,3672,3673,3674,3675,3676,3677,3678,3679,3680,3681,3682,3683,3684,3685,3686,3687,3688,3689,3690,3691,3692,3693,3694,3695,3696,3697,3698,3699,3700,3701,3702,3703,3704,3705,3706,3707,3708,3709,3710,3711,3712,3713,3714,3715,3716,3717,3718,3719,3720,3721,3722,3723,3724,3725,3726,3727,3728,3729,3730,3731,3732,3733,3734,3735,3736,3737,3738,3739,3740,3741,3742,3743,3744,3745,3746,3747,3748,3749,3750,3751,3752,3753,3754,3755,3756,3757,3758,3759,3760,3761,3762,3763,3764,3765,3766,3767,3768,3769,3770,3771,3772,3773,3774,3775,3776,3777,3778,3779,3780,3781,3782,3783,3784,3785,3786,3787,3788,3789,3790,3791,3792,3793,3794,3795,3796,3797,3798,3799,3800,3801,3802,3803,3804,3805,3806,3807,3808,3809,3810,3811,3812,3813,3814,3815,3816,3817,3818,3819,3820,3821,3822,3823,3824,3825,3826,3827,3828,3829,3830,3831,3832,3833,3834,3835,3836,3837,3838,3839,3840,3841,3842,3843,3844,3845,3846,3847,3848,3849,3850,3851,3852,3853,3854,3855,3856,3857,3858,3859,3860,3861,3862,3863,3864,3865,3866,3867,3868,3869,3870,3871,3872,3873,3874,3875,3876,3877,3878,3879,3880,3881,3882,3883,3884,3885,3886,3887,3888,3889,3890,3891,3892,3893,3894,3895,3896,3897,3898,3899,3900,3901,3902,3903,3904,3905,3906,3907,3908,3909,3910,3911,3912,3913,3914,3915,3916,3917,3918,3919,3920,3921,3922,3923,3924,3925,3926,3927,3928,3929,3930,3931,3932,3933,3934,3935,3936,3937,3938,3939,3940,3941,3942,3943,3944,3945,3946,3947,3948,3949,3950,3951,3952,3953,3954,3955,3956,3957,3958,3959,3960,3961,3962,3963,3964,3965,3966,3967,3968,3969,3970,3971,3972,3973,3974,3975,3976,3977,3978,3979,3980,3981,3982,3983,3984,3985,3986,3987,3988,3989,3990,3991,3992,3993,3994,3995,3996,3997,3998,3999,4000,4001,4002,4003,4004,4005,4006,4007,4008,4009,4010,4011,4012,4013,4014,4015,4016,4017,4018,4019,4020,4021,4022,4023,4024,4025,4026,4027,4028,4029,4030,4031,4032,4033,4034,4035,4036,4037,4038,4039,4040,4041,4042,4043,4044,4045,4046,4047,4048,4049,4050,4051,4052,4053,4054,4055,4056,4057,4058,4059,4060,4061,4062,4063,4064,4065,4066,4067,4068,4069,4070,4071,4072,4073,4074,4075,4076,4077,4078,4079,4080,4081,4082,4083,4084,4085,4086,4087,4088,4089,4090,4091,4092,4093,4094,4095] + is_save: False + +digital_gain: + is_debug: True + is_auto: True + # Array of pre-define Gains + gain_array: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, + 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, + 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, + 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, + 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100] + # Index of default gain + current_gain: 0 + ae_feedback: 0 + is_save: False + +bayer_noise_reduction: + is_enable: True + filter_window: 9 + r_std_dev_s: 1 + r_std_dev_r: 0.1 + g_std_dev_s: 1 + g_std_dev_r: 0.1 + b_std_dev_s: 1 + b_std_dev_r: 0.1 + is_save: False + +auto_white_balance: + is_enable: True + is_debug: True + stats_window_offset: [16, 16, 16, 16] + underexposed_percentage: 5 + overexposed_percentage: 5 + +white_balance: + is_enable: True + is_debug: True + is_auto: True + r_gain: 1.24609375 + b_gain: 2.80859375 + is_save: False + +demosaic: + is_save: False + +color_correction_matrix: + is_enable: True + corrected_red: [2053, -37,-991] + corrected_green: [-390, 1700,-287] + corrected_blue: [30,-1353,2338] + is_save: False + +gamma_correction: + is_enable: True + gamma_lut_8: [0,5,9,13,17,22,25,29,33,37,40,44,47,50,54,57,60,63,66,69,72,75,78,80,83,85,88,90,93,95,97,99,101,103,105,107,109,111,113,115,117,118,120,122,123,125,126,128,129,131,132,134,135,136,138,139,140,141,142,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,162,163,164,165,166,167,167,168,169,170,171,171,172,173,173,174,175,176,176,177,178,179,179,180,181,181,182,183,183,184,185,185,186,187,187,188,188,189,190,190,191,191,192,193,193,194,194,195,195,196,197,197,198,198,199,199,200,200,201,201,202,202,203,203,204,204,205,205,206,206,207,207,208,208,209,209,210,210,211,211,212,212,213,213,214,214,215,215,216,216,217,217,218,218,219,219,220,220,221,221,221,222,222,223,223,224,224,225,225,225,226,226,227,227,228,228,228,229,229,230,230,231,231,231,232,232,233,233,234,234,234,235,235,236,236,237,237,238,238,238,239,239,240,240,241,241,241,242,242,243,243,244,244,244,245,245,246,246,247,247,247,248,248,249,249,250,250,250,251,251,252,252,252,253,253,254,254,255] + # 10-bit + gamma_lut_10: [0, 9, 13, 17, 21, 25, 29, 34, 38, 42, 46, 50, 54, 58, 62, 66, 70, 74, 78, 82, 86, 90, 94, 98, 102, 106, 110, 114, 117, 121, 125, 129, 132, 136, 140, 143, 147, 150, 154, 157, 161, 165, 168, 172, 175, 179, 182, 185, 189, 192, 196, 199, 202, 205, 209, 212, 215, 219, 222, 225, 228, 231, 235, 238, 241, 244, 247, 250, 253, 256, 259, 262, 265, 268, 271, 274, 277, 280, 283, 286, 289, 292, 295, 297, 300, 303, 306, 308, 311, 314, 317, 319, 322, 325, 327, 330, 332, 335, 337, 340, 342, 345, 347, 350, 352, 355, 357, 359, 362, 364, 367, 369, 371, 374, 376, 378, 380, 383, 385, 387, 389, 392, 394, 396, 398, 400, 402, 404, 406, 409, 411, 413, 415, 417, 419, 421, 423, 425, 427, 429, 431, 433, 435, 437, 439, 441, 443, 444, 446, 448, 450, 452, 454, 455, 457, 459, 461, 463, 464, 466, 468, 469, 471, 473, 474, 476, 478, 479, 481, 483, 484, 486, 488, 489, 491, 492, 494, 495, 497, 499, 500, 502, 503, 505, 506, 508, 509, 511, 513, 514, 516, 517, 519, 520, 521, 523, 524, 526, 527, 529, 530, 532, 533, 534, 536, 537, 539, 540, 541, 543, 544, 545, 547, 548, 549, 550, 552, 553, 554, 555, 557, 558, 559, 560, 562, 563, 564, 565, 567, 568, 569, 570, 571, 573, 574, 575, 576, 577, 578, 580, 581, 582, 583, 584, 585, 586, 588, 589, 590, 591, 592, 593, 594, 595, 596, 598, 599, 600, 601, 602, 603, 604, 605, 606, 607, 608, 609, 610, 611, 612, 613, 614, 615, 616, 617, 618, 619, 620, 621, 622, 623, 624, 625, 626, 627, 628, 629, 630, 631, 632, 633, 633, 634, 635, 636, 637, 638, 639, 640, 641, 641, 642, 643, 644, 645, 646, 647, 648, 649, 649, 650, 651, 652, 653, 654, 655, 655, 656, 657, 658, 659, 660, 660, 661, 662, 663, 664, 665, 665, 666, 667, 668, 669, 670, 670, 671, 672, 673, 674, 674, 675, 676, 677, 678, 678, 679, 680, 681, 681, 682, 683, 683, 684, 685, 686, 686, 687, 688, 689, 689, 690, 691, 692, 692, 693, 694, 695, 695, 696, 697, 697, 698, 699, 700, 700, 701, 702, 703, 703, 704, 705, 705, 706, 707, 708, 708, 709, 710, 710, 711, 712, 713, 713, 714, 715, 715, 716, 717, 717, 718, 719, 719, 720, 721, 722, 722, 723, 724, 724, 725, 726, 726, 727, 728, 728, 729, 730, 731, 731, 732, 733, 733, 734, 734, 735, 736, 736, 737, 738, 738, 739, 740, 740, 741, 742, 742, 743, 744, 744, 745, 745, 746, 747, 747, 748, 749, 749, 750, 751, 751, 752, 753, 753, 754, 754, 755, 756, 756, 757, 757, 758, 759, 759, 760, 761, 761, 762, 762, 763, 763, 764, 765, 765, 766, 766, 767, 768, 768, 769, 769, 770, 771, 771, 772, 772, 773, 774, 774, 775, 775, 776, 776, 777, 777, 778, 779, 779, 780, 780, 781, 782, 782, 783, 783, 784, 784, 785, 785, 786, 787, 787, 788, 788, 789, 789, 790, 791, 791, 792, 792, 793, 793, 794, 794, 795, 795, 796, 797, 797, 797, 798, 799, 799, 800, 800, 801, 801, 802, 802, 803, 803, 804, 805, 805, 806, 806, 806, 807, 808, 808, 809, 809, 810, 810, 811, 811, 812, 812, 813, 813, 814, 814, 815, 815, 816, 816, 817, 817, 818, 818, 819, 819, 820, 821, 821, 821, 822, 823, 823, 824, 824, 825, 825, 826, 826, 827, 827, 828, 828, 829, 829, 830, 830, 831, 831, 832, 832, 833, 833, 834, 834, 835, 835, 836, 836, 837, 837, 838, 838, 839, 839, 839, 840, 841, 841, 842, 842, 842, 843, 843, 844, 845, 845, 845, 846, 846, 847, 847, 848, 848, 849, 849, 850, 850, 851, 851, 852, 852, 853, 853, 854, 854, 855, 855, 856, 856, 857, 857, 858, 858, 859, 859, 860, 860, 861, 861, 862, 862, 863, 863, 864, 864, 865, 865, 866, 866, 867, 867, 868, 868, 868, 869, 870, 870, 870, 871, 871, 872, 872, 873, 873, 874, 874, 875, 875, 876, 876, 877, 877, 878, 878, 879, 879, 880, 880, 881, 881, 881, 882, 882, 883, 883, 884, 884, 885, 885, 886, 886, 887, 887, 887, 888, 888, 889, 889, 890, 890, 891, 891, 892, 892, 892, 893, 893, 894, 894, 895, 895, 896, 896, 896, 897, 897, 898, 898, 899, 899, 900, 900, 900, 901, 901, 902, 902, 903, 903, 903, 904, 904, 905, 905, 906, 906, 906, 907, 907, 908, 908, 909, 909, 910, 910, 910, 911, 911, 912, 912, 913, 913, 913, 914, 914, 915, 915, 916, 916, 916, 917, 917, 918, 918, 919, 919, 919, 920, 920, 921, 921, 922, 922, 922, 923, 923, 924, 924, 925, 925, 925, 926, 926, 927, 927, 928, 928, 928, 929, 929, 930, 930, 931, 931, 931, 932, 932, 933, 933, 934, 934, 934, 935, 935, 936, 936, 936, 937, 937, 938, 938, 939, 939, 939, 940, 940, 941, 941, 942, 942, 943, 943, 943, 944, 944, 945, 945, 946, 946, 947, 947, 947, 948, 948, 949, 949, 950, 950, 951, 951, 951, 952, 952, 953, 953, 954, 954, 955, 955, 956, 956, 956, 957, 957, 958, 958, 959, 959, 960, 960, 961, 961, 961, 962, 962, 963, 963, 964, 964, 964, 965, 965, 966, 966, 967, 967, 968, 968, 968, 969, 969, 970, 970, 971, 971, 971, 972, 972, 973, 973, 974, 974, 975, 975, 975, 976, 976, 977, 977, 977, 978, 978, 979, 979, 980, 980, 980, 981, 981, 982, 982, 983, 983, 983, 984, 984, 985, 985, 986, 986, 986, 987, 987, 988, 988, 988, 989, 989, 990, 990, 990, 991, 991, 992, 992, 993, 993, 994, 994, 994, 995, 995, 996, 996, 997, 997, 997, 998, 998, 999, 999, 999, 1000, 1000, 1001, 1001, 1002, 1002, 1002, 1003, 1003, 1004, 1004, 1004, 1005, 1005, 1006, 1006, 1007, 1007, 1007, 1008, 1008, 1009, 1009, 1010, 1010, 1010, 1011, 1011, 1012, 1012, 1013, 1013, 1013, 1014, 1014, 1015, 1015, 1015, 1016, 1016, 1017, 1017, 1018, 1018, 1018, 1019, 1019, 1020, 1020, 1021, 1021, 1021, 1022, 1022, 1023, 1023] + # 12-bit + gamma_lut_12: [0, 11, 21, 30, 37, 42, 46, 50, 53, 57, 61, 65, 70, 74, 78, 82, 86, 90, 94, 98, 102, 106, 110, 114, 118, 122, 126, 131, 135, 139, 143, 147, 151, 155, 159, 163, 167, 171, 175, 179, 183, 187, 191, 195, 199, 203, 207, 212, 216, 220, 224, 228, 232, 236, 240, 245, 249, 253, 257, 261, 265, 269, 273, 277, 281, 285, 289, 293, 297, 301, 305, 309, 313, 317, 321, 326, 330, 334, 338, 342, 346, 350, 354, 358, 362, 365, 369, 373, 377, 381, 385, 390, 394, 398, 401, 405, 409, 413, 417, 421, 425, 429, 432, 436, 440, 443, 447, 451, 455, 458, 462, 466, 470, 473, 477, 481, 485, 488, 492, 496, 500, 503, 507, 511, 515, 519, 522, 526, 530, 533, 537, 540, 544, 547, 551, 555, 559, 562, 566, 569, 573, 576, 580, 584, 588, 591, 595, 598, 602, 605, 609, 612, 616, 619, 622, 626, 630, 633, 637, 641, 645, 648, 652, 655, 659, 662, 665, 669, 673, 676, 680, 683, 687, 690, 693, 696, 700, 703, 707, 711, 715, 718, 721, 724, 728, 731, 734, 738, 742, 745, 749, 752, 756, 759, 762, 765, 769, 772, 775, 779, 783, 786, 789, 792, 796, 799, 802, 805, 809, 812, 815, 818, 822, 825, 828, 832, 836, 839, 842, 845, 849, 852, 855, 858, 862, 865, 868, 871, 875, 878, 881, 884, 888, 890, 893, 896, 900, 903, 906, 910, 914, 917, 920, 923, 926, 929, 932, 935, 939, 942, 945, 948, 952, 954, 957, 960, 964, 967, 970, 973, 977, 979, 982, 985, 989, 992, 995, 998, 1002, 1005, 1007, 1010, 1014, 1016, 1019, 1022, 1026, 1028, 1031, 1034, 1038, 1040, 1043, 1046, 1050, 1052, 1055, 1058, 1062, 1064, 1067, 1070, 1074, 1076, 1079, 1082, 1086, 1088, 1091, 1094, 1098, 1100, 1103, 1106, 1110, 1112, 1115, 1118, 1121, 1123, 1126, 1129, 1133, 1135, 1138, 1141, 1145, 1147, 1150, 1153, 1156, 1158, 1161, 1163, 1167, 1169, 1172, 1175, 1179, 1181, 1184, 1187, 1190, 1192, 1195, 1198, 1201, 1203, 1206, 1209, 1212, 1214, 1217, 1220, 1223, 1225, 1228, 1231, 1234, 1236, 1239, 1242, 1245, 1247, 1250, 1253, 1256, 1258, 1261, 1264, 1267, 1269, 1271, 1274, 1277, 1279, 1282, 1284, 1288, 1290, 1293, 1296, 1299, 1301, 1303, 1306, 1309, 1311, 1314, 1317, 1320, 1322, 1324, 1327, 1330, 1332, 1335, 1338, 1341, 1343, 1345, 1347, 1350, 1352, 1355, 1358, 1360, 1363, 1365, 1367, 1369, 1372, 1375, 1378, 1380, 1383, 1385, 1387, 1389, 1392, 1395, 1397, 1400, 1403, 1405, 1407, 1409, 1412, 1414, 1417, 1419, 1422, 1424, 1427, 1429, 1431, 1434, 1436, 1438, 1441, 1443, 1446, 1448, 1451, 1453, 1456, 1458, 1461, 1463, 1465, 1467, 1469, 1471, 1474, 1476, 1479, 1481, 1484, 1486, 1488, 1491, 1493, 1495, 1497, 1499, 1502, 1504, 1506, 1509, 1511, 1513, 1515, 1518, 1520, 1522, 1524, 1527, 1529, 1531, 1533, 1535, 1538, 1540, 1542, 1544, 1547, 1549, 1551, 1553, 1556, 1558, 1560, 1563, 1565, 1567, 1569, 1571, 1573, 1575, 1577, 1579, 1582, 1584, 1586, 1588, 1590, 1592, 1594, 1596, 1599, 1601, 1603, 1605, 1607, 1609, 1611, 1613, 1616, 1618, 1620, 1622, 1624, 1626, 1628, 1630, 1633, 1635, 1637, 1639, 1641, 1643, 1645, 1647, 1650, 1652, 1654, 1656, 1658, 1660, 1662, 1664, 1666, 1668, 1670, 1672, 1674, 1676, 1678, 1680, 1682, 1684, 1686, 1688, 1691, 1693, 1695, 1697, 1699, 1701, 1703, 1705, 1707, 1709, 1711, 1713, 1715, 1717, 1719, 1721, 1723, 1725, 1727, 1728, 1730, 1732, 1734, 1736, 1738, 1740, 1742, 1744, 1746, 1748, 1750, 1751, 1753, 1755, 1757, 1759, 1761, 1763, 1765, 1767, 1769, 1771, 1773, 1774, 1776, 1778, 1780, 1782, 1784, 1786, 1788, 1789, 1791, 1793, 1795, 1796, 1798, 1800, 1802, 1803, 1805, 1807, 1809, 1811, 1813, 1815, 1817, 1818, 1820, 1822, 1824, 1825, 1827, 1829, 1831, 1832, 1834, 1836, 1838, 1839, 1841, 1843, 1845, 1847, 1849, 1851, 1853, 1854, 1856, 1857, 1858, 1860, 1862, 1864, 1866, 1868, 1870, 1872, 1874, 1875, 1876, 1878, 1880, 1881, 1883, 1885, 1887, 1888, 1890, 1892, 1893, 1895, 1896, 1898, 1900, 1901, 1903, 1905, 1907, 1908, 1910, 1912, 1913, 1915, 1916, 1918, 1920, 1921, 1923, 1925, 1927, 1928, 1930, 1932, 1933, 1935, 1936, 1938, 1940, 1941, 1943, 1945, 1947, 1948, 1949, 1951, 1952, 1954, 1955, 1957, 1959, 1960, 1962, 1964, 1965, 1967, 1968, 1970, 1972, 1973, 1975, 1977, 1978, 1979, 1981, 1982, 1983, 1985, 1987, 1989, 1990, 1992, 1993, 1995, 1997, 1998, 2000, 2002, 2003, 2005, 2006, 2008, 2009, 2011, 2012, 2014, 2015, 2017, 2018, 2020, 2021, 2023, 2024, 2026, 2027, 2029, 2030, 2032, 2033, 2035, 2036, 2038, 2039, 2041, 2042, 2044, 2046, 2047, 2049, 2051, 2052, 2053, 2055, 2056, 2057, 2059, 2061, 2063, 2064, 2066, 2067, 2069, 2070, 2072, 2073, 2075, 2076, 2077, 2079, 2080, 2081, 2083, 2084, 2086, 2087, 2089, 2090, 2092, 2093, 2095, 2096, 2098, 2099, 2101, 2102, 2104, 2105, 2107, 2108, 2110, 2111, 2112, 2114, 2115, 2116, 2117, 2119, 2121, 2122, 2124, 2125, 2127, 2128, 2129, 2130, 2132, 2133, 2135, 2136, 2138, 2139, 2140, 2142, 2143, 2144, 2145, 2147, 2149, 2150, 2152, 2153, 2155, 2156, 2157, 2159, 2160, 2161, 2162, 2163, 2165, 2166, 2168, 2169, 2171, 2172, 2173, 2175, 2176, 2177, 2178, 2179, 2181, 2182, 2184, 2185, 2187, 2188, 2189, 2191, 2192, 2193, 2194, 2195, 2197, 2198, 2199, 2200, 2202, 2203, 2205, 2206, 2208, 2209, 2210, 2212, 2213, 2214, 2215, 2216, 2217, 2218, 2219, 2220, 2222, 2223, 2225, 2226, 2228, 2229, 2230, 2232, 2233, 2234, 2235, 2237, 2238, 2239, 2240, 2241, 2242, 2243, 2244, 2245, 2247, 2248, 2249, 2250, 2252, 2253, 2255, 2256, 2258, 2259, 2260, 2261, 2262, 2263, 2264, 2265, 2267, 2268, 2269, 2270, 2271, 2272, 2273, 2274, 2276, 2277, 2278, 2279, 2281, 2282, 2283, 2284, 2286, 2287, 2288, 2289, 2291, 2292, 2293, 2295, 2296, 2297, 2297, 2299, 2300, 2301, 2302, 2303, 2305, 2306, 2307, 2308, 2309, 2310, 2311, 2312, 2314, 2315, 2316, 2318, 2319, 2320, 2320, 2322, 2323, 2324, 2325, 2326, 2328, 2329, 2330, 2332, 2333, 2334, 2334, 2336, 2337, 2338, 2339, 2340, 2342, 2343, 2343, 2345, 2346, 2347, 2348, 2349, 2351, 2352, 2353, 2354, 2355, 2356, 2356, 2358, 2359, 2360, 2361, 2362, 2364, 2365, 2365, 2367, 2368, 2369, 2370, 2371, 2373, 2374, 2374, 2376, 2377, 2378, 2379, 2380, 2382, 2383, 2383, 2385, 2386, 2387, 2388, 2389, 2391, 2392, 2393, 2394, 2395, 2396, 2396, 2398, 2399, 2400, 2401, 2402, 2404, 2405, 2406, 2407, 2408, 2409, 2409, 2411, 2412, 2413, 2414, 2415, 2417, 2418, 2419, 2420, 2421, 2422, 2422, 2424, 2425, 2426, 2426, 2428, 2429, 2430, 2430, 2432, 2433, 2434, 2434, 2436, 2437, 2438, 2439, 2440, 2442, 2443, 2444, 2445, 2446, 2447, 2447, 2449, 2450, 2451, 2451, 2453, 2454, 2455, 2455, 2457, 2458, 2459, 2459, 2461, 2462, 2463, 2463, 2465, 2466, 2467, 2468, 2469, 2470, 2470, 2471, 2472, 2473, 2473, 2474, 2476, 2477, 2478, 2478, 2480, 2481, 2482, 2482, 2484, 2485, 2486, 2486, 2488, 2489, 2490, 2490, 2492, 2493, 2494, 2494, 2496, 2497, 2498, 2498, 2500, 2501, 2502, 2502, 2504, 2505, 2505, 2506, 2507, 2508, 2509, 2509, 2511, 2512, 2512, 2513, 2514, 2515, 2515, 2516, 2517, 2519, 2520, 2520, 2522, 2523, 2524, 2524, 2526, 2527, 2528, 2528, 2530, 2531, 2531, 2532, 2533, 2534, 2535, 2535, 2537, 2538, 2538, 2539, 2540, 2541, 2542, 2542, 2544, 2545, 2545, 2546, 2547, 2548, 2548, 2549, 2550, 2552, 2553, 2553, 2555, 2556, 2556, 2557, 2558, 2559, 2560, 2560, 2562, 2563, 2563, 2564, 2565, 2566, 2566, 2567, 2568, 2570, 2571, 2571, 2573, 2574, 2574, 2575, 2576, 2577, 2577, 2578, 2580, 2581, 2581, 2582, 2583, 2584, 2584, 2585, 2586, 2587, 2587, 2588, 2589, 2591, 2592, 2592, 2594, 2595, 2595, 2596, 2597, 2598, 2598, 2599, 2600, 2601, 2602, 2602, 2604, 2605, 2605, 2606, 2607, 2608, 2608, 2609, 2610, 2612, 2613, 2613, 2615, 2616, 2616, 2617, 2618, 2619, 2619, 2620, 2621, 2622, 2622, 2623, 2624, 2625, 2625, 2626, 2627, 2629, 2630, 2630, 2632, 2633, 2633, 2634, 2635, 2636, 2636, 2637, 2638, 2639, 2639, 2640, 2641, 2642, 2642, 2643, 2645, 2646, 2646, 2647, 2648, 2649, 2649, 2650, 2651, 2653, 2653, 2654, 2655, 2656, 2656, 2657, 2658, 2659, 2659, 2660, 2661, 2662, 2662, 2663, 2665, 2666, 2666, 2667, 2668, 2669, 2669, 2670, 2671, 2672, 2672, 2673, 2674, 2675, 2675, 2676, 2677, 2679, 2679, 2680, 2681, 2682, 2682, 2683, 2684, 2685, 2685, 2686, 2687, 2688, 2688, 2689, 2690, 2691, 2691, 2692, 2693, 2695, 2695, 2696, 2697, 2698, 2698, 2699, 2700, 2701, 2701, 2702, 2703, 2704, 2704, 2705, 2706, 2707, 2707, 2708, 2709, 2711, 2711, 2712, 2713, 2714, 2714, 2714, 2715, 2716, 2716, 2717, 2718, 2720, 2720, 2721, 2722, 2723, 2723, 2724, 2725, 2726, 2726, 2727, 2728, 2729, 2729, 2730, 2731, 2732, 2732, 2733, 2734, 2735, 2735, 2736, 2737, 2738, 2738, 2739, 2740, 2741, 2741, 2742, 2743, 2744, 2744, 2745, 2746, 2747, 2747, 2748, 2749, 2750, 2750, 2751, 2752, 2753, 2753, 2754, 2755, 2756, 2756, 2757, 2758, 2759, 2759, 2760, 2761, 2762, 2762, 2763, 2764, 2765, 2765, 2766, 2767, 2768, 2768, 2769, 2770, 2771, 2771, 2772, 2773, 2774, 2774, 2775, 2776, 2777, 2777, 2778, 2779, 2780, 2780, 2780, 2781, 2782, 2782, 2782, 2783, 2785, 2785, 2786, 2788, 2789, 2789, 2789, 2790, 2791, 2791, 2792, 2793, 2794, 2794, 2795, 2796, 2797, 2797, 2798, 2799, 2800, 2800, 2801, 2802, 2803, 2803, 2804, 2805, 2806, 2806, 2807, 2808, 2809, 2809, 2810, 2811, 2812, 2812, 2812, 2813, 2814, 2814, 2814, 2815, 2817, 2817, 2818, 2820, 2821, 2821, 2821, 2822, 2823, 2823, 2824, 2825, 2826, 2826, 2827, 2828, 2829, 2829, 2830, 2831, 2832, 2832, 2833, 2834, 2835, 2835, 2835, 2836, 2837, 2837, 2838, 2839, 2841, 2841, 2841, 2842, 2843, 2843, 2843, 2845, 2846, 2846, 2847, 2848, 2849, 2849, 2850, 2851, 2852, 2852, 2853, 2854, 2855, 2855, 2855, 2856, 2857, 2857, 2858, 2859, 2860, 2860, 2861, 2862, 2863, 2863, 2864, 2865, 2866, 2866, 2866, 2867, 2868, 2868, 2869, 2870, 2871, 2871, 2872, 2873, 2874, 2874, 2875, 2876, 2877, 2877, 2877, 2878, 2879, 2879, 2880, 2881, 2883, 2883, 2883, 2884, 2885, 2885, 2885, 2887, 2888, 2888, 2889, 2890, 2891, 2891, 2892, 2893, 2894, 2894, 2894, 2895, 2896, 2896, 2897, 2898, 2899, 2899, 2900, 2901, 2902, 2902, 2903, 2904, 2905, 2905, 2905, 2906, 2907, 2907, 2907, 2908, 2910, 2910, 2911, 2912, 2913, 2913, 2913, 2914, 2915, 2915, 2915, 2917, 2918, 2918, 2919, 2920, 2921, 2921, 2922, 2923, 2924, 2924, 2924, 2925, 2926, 2926, 2926, 2927, 2928, 2928, 2929, 2930, 2932, 2932, 2932, 2933, 2934, 2934, 2934, 2935, 2936, 2936, 2937, 2938, 2939, 2939, 2940, 2941, 2942, 2942, 2943, 2944, 2945, 2945, 2945, 2946, 2947, 2947, 2947, 2948, 2950, 2950, 2951, 2952, 2953, 2953, 2953, 2954, 2955, 2955, 2956, 2957, 2958, 2958, 2958, 2959, 2960, 2960, 2961, 2962, 2963, 2963, 2963, 2964, 2965, 2965, 2965, 2966, 2968, 2968, 2969, 2970, 2971, 2971, 2971, 2972, 2973, 2973, 2973, 2974, 2976, 2976, 2977, 2978, 2979, 2979, 2979, 2980, 2981, 2981, 2981, 2982, 2983, 2983, 2983, 2984, 2986, 2986, 2987, 2988, 2989, 2989, 2989, 2990, 2991, 2991, 2992, 2993, 2994, 2994, 2994, 2995, 2996, 2996, 2997, 2998, 2999, 2999, 2999, 3000, 3001, 3001, 3002, 3003, 3004, 3004, 3004, 3005, 3006, 3006, 3006, 3007, 3009, 3009, 3010, 3011, 3012, 3012, 3012, 3013, 3014, 3014, 3014, 3015, 3016, 3016, 3017, 3018, 3019, 3019, 3019, 3020, 3021, 3021, 3022, 3023, 3024, 3024, 3024, 3025, 3026, 3026, 3027, 3028, 3029, 3029, 3029, 3030, 3031, 3031, 3031, 3033, 3034, 3034, 3034, 3035, 3036, 3036, 3036, 3037, 3038, 3038, 3038, 3039, 3041, 3041, 3042, 3043, 3044, 3044, 3044, 3045, 3046, 3046, 3046, 3047, 3048, 3048, 3049, 3050, 3051, 3051, 3051, 3052, 3053, 3053, 3053, 3054, 3055, 3055, 3056, 3057, 3058, 3058, 3058, 3059, 3060, 3060, 3060, 3061, 3062, 3062, 3063, 3064, 3065, 3065, 3065, 3066, 3067, 3067, 3067, 3068, 3069, 3069, 3070, 3071, 3072, 3072, 3072, 3073, 3074, 3074, 3074, 3076, 3077, 3077, 3077, 3078, 3079, 3079, 3079, 3080, 3082, 3082, 3082, 3083, 3084, 3084, 3084, 3085, 3086, 3086, 3086, 3088, 3089, 3089, 3089, 3090, 3091, 3091, 3091, 3092, 3093, 3093, 3093, 3095, 3096, 3096, 3096, 3097, 3098, 3098, 3098, 3099, 3100, 3100, 3100, 3102, 3103, 3103, 3103, 3104, 3105, 3105, 3105, 3106, 3107, 3107, 3107, 3108, 3109, 3109, 3109, 3110, 3111, 3111, 3111, 3112, 3114, 3114, 3114, 3115, 3116, 3116, 3116, 3117, 3118, 3118, 3118, 3119, 3121, 3121, 3121, 3122, 3123, 3123, 3123, 3124, 3125, 3125, 3125, 3126, 3128, 3128, 3128, 3129, 3130, 3130, 3130, 3131, 3132, 3132, 3132, 3133, 3134, 3134, 3134, 3135, 3137, 3137, 3137, 3138, 3139, 3139, 3139, 3140, 3141, 3141, 3141, 3142, 3143, 3143, 3143, 3144, 3145, 3145, 3145, 3146, 3148, 3148, 3148, 3149, 3150, 3150, 3150, 3151, 3152, 3152, 3152, 3153, 3155, 3155, 3155, 3156, 3157, 3157, 3157, 3158, 3159, 3159, 3159, 3160, 3161, 3161, 3162, 3163, 3164, 3163, 3163, 3164, 3165, 3165, 3165, 3166, 3168, 3168, 3168, 3169, 3170, 3170, 3170, 3171, 3172, 3172, 3172, 3173, 3175, 3175, 3175, 3176, 3177, 3177, 3177, 3178, 3179, 3179, 3179, 3180, 3181, 3181, 3181, 3182, 3183, 3183, 3183, 3184, 3185, 3185, 3185, 3186, 3188, 3188, 3188, 3189, 3190, 3189, 3189, 3190, 3191, 3191, 3191, 3192, 3194, 3194, 3194, 3195, 3196, 3196, 3196, 3197, 3198, 3198, 3199, 3200, 3201, 3201, 3201, 3201, 3202, 3201, 3202, 3202, 3204, 3204, 3204, 3205, 3207, 3207, 3207, 3208, 3209, 3209, 3209, 3210, 3211, 3211, 3211, 3212, 3213, 3213, 3213, 3214, 3215, 3215, 3215, 3216, 3217, 3217, 3218, 3219, 3220, 3219, 3219, 3220, 3221, 3221, 3221, 3222, 3224, 3224, 3224, 3225, 3226, 3225, 3225, 3226, 3227, 3227, 3227, 3228, 3230, 3230, 3230, 3231, 3232, 3232, 3232, 3233, 3234, 3234, 3234, 3235, 3236, 3236, 3236, 3237, 3238, 3238, 3238, 3239, 3240, 3240, 3240, 3242, 3243, 3243, 3243, 3243, 3244, 3243, 3244, 3244, 3246, 3246, 3247, 3248, 3249, 3248, 3248, 3249, 3250, 3250, 3250, 3251, 3253, 3253, 3253, 3254, 3255, 3255, 3255, 3256, 3257, 3257, 3257, 3258, 3259, 3259, 3259, 3260, 3261, 3261, 3261, 3262, 3263, 3263, 3263, 3264, 3265, 3265, 3265, 3266, 3267, 3267, 3267, 3268, 3269, 3269, 3269, 3270, 3271, 3271, 3271, 3272, 3273, 3273, 3273, 3274, 3275, 3275, 3275, 3276, 3278, 3278, 3278, 3278, 3279, 3278, 3279, 3279, 3281, 3281, 3281, 3282, 3284, 3284, 3284, 3285, 3286, 3285, 3285, 3286, 3287, 3287, 3287, 3288, 3290, 3290, 3290, 3291, 3292, 3291, 3291, 3292, 3293, 3293, 3293, 3294, 3296, 3296, 3296, 3297, 3298, 3298, 3298, 3299, 3300, 3300, 3300, 3301, 3302, 3302, 3302, 3303, 3304, 3304, 3304, 3305, 3306, 3306, 3306, 3307, 3308, 3308, 3308, 3309, 3310, 3310, 3310, 3311, 3312, 3312, 3312, 3313, 3314, 3314, 3314, 3315, 3316, 3316, 3316, 3317, 3318, 3318, 3318, 3319, 3320, 3320, 3320, 3321, 3322, 3322, 3322, 3323, 3324, 3324, 3324, 3325, 3326, 3326, 3326, 3327, 3328, 3328, 3328, 3329, 3330, 3330, 3330, 3331, 3332, 3332, 3332, 3333, 3334, 3334, 3334, 3335, 3336, 3336, 3336, 3337, 3338, 3338, 3338, 3339, 3340, 3340, 3340, 3341, 3342, 3342, 3342, 3343, 3344, 3344, 3344, 3345, 3346, 3346, 3346, 3347, 3348, 3348, 3348, 3349, 3350, 3350, 3350, 3351, 3352, 3352, 3352, 3353, 3354, 3354, 3354, 3355, 3356, 3356, 3356, 3357, 3358, 3357, 3357, 3358, 3359, 3359, 3359, 3360, 3362, 3362, 3362, 3363, 3364, 3363, 3363, 3364, 3365, 3365, 3365, 3366, 3368, 3368, 3368, 3369, 3370, 3369, 3369, 3370, 3371, 3371, 3371, 3372, 3374, 3373, 3373, 3374, 3375, 3374, 3375, 3375, 3377, 3377, 3377, 3378, 3380, 3379, 3379, 3380, 3381, 3380, 3381, 3381, 3383, 3383, 3383, 3384, 3385, 3385, 3385, 3386, 3387, 3387, 3387, 3388, 3389, 3389, 3389, 3390, 3391, 3391, 3391, 3392, 3393, 3393, 3393, 3394, 3395, 3395, 3395, 3396, 3397, 3397, 3397, 3398, 3399, 3399, 3399, 3400, 3401, 3401, 3401, 3402, 3403, 3403, 3403, 3404, 3405, 3405, 3405, 3406, 3407, 3406, 3406, 3407, 3408, 3408, 3408, 3409, 3411, 3411, 3411, 3412, 3413, 3412, 3412, 3413, 3414, 3414, 3414, 3415, 3417, 3417, 3417, 3418, 3419, 3418, 3418, 3419, 3420, 3419, 3420, 3420, 3422, 3422, 3422, 3423, 3425, 3424, 3424, 3425, 3426, 3425, 3425, 3426, 3428, 3428, 3428, 3429, 3431, 3430, 3430, 3431, 3432, 3431, 3432, 3432, 3434, 3434, 3434, 3435, 3436, 3436, 3436, 3437, 3438, 3438, 3438, 3439, 3440, 3440, 3440, 3441, 3442, 3442, 3442, 3443, 3444, 3444, 3444, 3445, 3446, 3446, 3446, 3447, 3448, 3448, 3448, 3449, 3450, 3450, 3450, 3451, 3452, 3452, 3452, 3453, 3454, 3454, 3454, 3455, 3456, 3456, 3456, 3457, 3458, 3458, 3458, 3459, 3460, 3460, 3460, 3461, 3462, 3462, 3462, 3463, 3464, 3463, 3464, 3464, 3466, 3466, 3466, 3467, 3468, 3467, 3467, 3468, 3469, 3469, 3469, 3470, 3472, 3472, 3472, 3473, 3474, 3473, 3473, 3474, 3475, 3474, 3474, 3475, 3477, 3477, 3477, 3478, 3480, 3479, 3479, 3480, 3481, 3480, 3481, 3481, 3483, 3483, 3483, 3484, 3485, 3485, 3485, 3486, 3487, 3487, 3487, 3488, 3489, 3489, 3489, 3490, 3491, 3491, 3491, 3492, 3493, 3492, 3493, 3493, 3495, 3495, 3495, 3496, 3497, 3496, 3496, 3497, 3498, 3498, 3498, 3499, 3501, 3501, 3501, 3502, 3503, 3502, 3502, 3503, 3504, 3503, 3503, 3504, 3506, 3506, 3506, 3507, 3509, 3508, 3508, 3509, 3510, 3509, 3510, 3510, 3512, 3512, 3512, 3513, 3514, 3513, 3514, 3514, 3516, 3515, 3516, 3516, 3518, 3517, 3518, 3518, 3520, 3519, 3520, 3520, 3522, 3522, 3522, 3523, 3524, 3523, 3523, 3524, 3525, 3524, 3524, 3525, 3527, 3527, 3527, 3528, 3530, 3529, 3529, 3530, 3531, 3530, 3531, 3531, 3533, 3532, 3533, 3533, 3535, 3535, 3535, 3536, 3537, 3536, 3536, 3537, 3538, 3537, 3537, 3538, 3540, 3540, 3540, 3541, 3543, 3542, 3542, 3543, 3544, 3543, 3544, 3544, 3546, 3545, 3546, 3546, 3548, 3548, 3548, 3549, 3550, 3549, 3549, 3550, 3551, 3550, 3551, 3551, 3553, 3552, 3553, 3553, 3555, 3554, 3555, 3555, 3557, 3556, 3557, 3557, 3559, 3559, 3559, 3560, 3561, 3560, 3560, 3561, 3562, 3561, 3562, 3562, 3564, 3563, 3564, 3564, 3566, 3566, 3566, 3567, 3568, 3567, 3567, 3568, 3569, 3568, 3569, 3569, 3571, 3570, 3571, 3571, 3573, 3572, 3573, 3573, 3575, 3574, 3575, 3575, 3577, 3577, 3577, 3578, 3579, 3578, 3578, 3579, 3580, 3579, 3580, 3580, 3582, 3581, 3582, 3582, 3584, 3584, 3584, 3585, 3586, 3585, 3585, 3586, 3587, 3586, 3587, 3587, 3589, 3588, 3589, 3589, 3591, 3590, 3591, 3591, 3593, 3593, 3593, 3594, 3595, 3594, 3594, 3595, 3596, 3595, 3596, 3596, 3598, 3597, 3598, 3598, 3600, 3600, 3600, 3601, 3602, 3601, 3601, 3602, 3603, 3602, 3603, 3603, 3605, 3604, 3605, 3605, 3607, 3606, 3607, 3608, 3609, 3608, 3608, 3609, 3610, 3609, 3610, 3610, 3612, 3612, 3612, 3613, 3614, 3613, 3613, 3614, 3615, 3614, 3615, 3615, 3617, 3616, 3617, 3617, 3619, 3619, 3619, 3620, 3621, 3620, 3620, 3621, 3622, 3622, 3622, 3623, 3625, 3624, 3624, 3625, 3626, 3625, 3625, 3625, 3627, 3627, 3627, 3628, 3630, 3629, 3629, 3630, 3631, 3630, 3630, 3631, 3633, 3632, 3633, 3633, 3635, 3634, 3635, 3636, 3637, 3636, 3636, 3637, 3638, 3637, 3637, 3638, 3640, 3640, 3640, 3641, 3642, 3641, 3641, 3642, 3643, 3642, 3643, 3643, 3645, 3644, 3645, 3645, 3647, 3646, 3647, 3648, 3649, 3648, 3648, 3649, 3650, 3649, 3649, 3650, 3652, 3652, 3652, 3653, 3654, 3653, 3653, 3654, 3655, 3654, 3655, 3655, 3657, 3656, 3657, 3657, 3659, 3658, 3659, 3659, 3661, 3660, 3660, 3661, 3662, 3661, 3661, 3662, 3664, 3663, 3664, 3665, 3666, 3665, 3665, 3666, 3667, 3666, 3667, 3667, 3669, 3668, 3669, 3669, 3671, 3670, 3671, 3671, 3673, 3672, 3672, 3673, 3674, 3673, 3673, 3674, 3676, 3675, 3676, 3677, 3678, 3677, 3677, 3678, 3679, 3678, 3678, 3679, 3681, 3680, 3681, 3682, 3683, 3682, 3682, 3683, 3684, 3683, 3683, 3684, 3686, 3685, 3686, 3686, 3688, 3687, 3688, 3688, 3690, 3689, 3689, 3690, 3691, 3690, 3690, 3691, 3693, 3692, 3693, 3694, 3695, 3694, 3694, 3695, 3696, 3695, 3695, 3696, 3698, 3697, 3698, 3699, 3700, 3699, 3699, 3700, 3701, 3700, 3700, 3701, 3703, 3702, 3703, 3703, 3705, 3704, 3705, 3705, 3707, 3706, 3706, 3707, 3708, 3707, 3707, 3708, 3710, 3709, 3710, 3710, 3712, 3711, 3711, 3712, 3713, 3712, 3712, 3713, 3715, 3714, 3715, 3715, 3717, 3716, 3716, 3717, 3718, 3717, 3717, 3718, 3720, 3719, 3720, 3720, 3722, 3721, 3722, 3722, 3724, 3723, 3723, 3724, 3725, 3724, 3724, 3724, 3726, 3726, 3726, 3727, 3729, 3728, 3728, 3729, 3730, 3729, 3730, 3730, 3732, 3731, 3731, 3731, 3733, 3733, 3733, 3734, 3736, 3735, 3735, 3736, 3737, 3736, 3736, 3736, 3738, 3737, 3737, 3738, 3740, 3739, 3740, 3740, 3742, 3741, 3742, 3742, 3744, 3743, 3743, 3744, 3745, 3744, 3744, 3745, 3747, 3746, 3747, 3747, 3749, 3748, 3749, 3749, 3751, 3750, 3750, 3751, 3752, 3751, 3751, 3752, 3754, 3753, 3754, 3754, 3756, 3755, 3756, 3756, 3758, 3757, 3757, 3758, 3759, 3758, 3758, 3759, 3761, 3760, 3761, 3761, 3763, 3762, 3763, 3763, 3765, 3764, 3764, 3765, 3766, 3765, 3765, 3766, 3768, 3767, 3768, 3768, 3770, 3769, 3770, 3770, 3772, 3771, 3771, 3772, 3773, 3772, 3772, 3773, 3775, 3774, 3775, 3775, 3777, 3776, 3777, 3777, 3779, 3778, 3778, 3779, 3780, 3779, 3779, 3780, 3782, 3781, 3782, 3782, 3784, 3783, 3783, 3784, 3786, 3785, 3786, 3786, 3788, 3787, 3787, 3788, 3789, 3788, 3788, 3789, 3791, 3790, 3791, 3791, 3793, 3792, 3792, 3793, 3795, 3794, 3795, 3795, 3797, 3796, 3796, 3797, 3798, 3797, 3797, 3798, 3800, 3799, 3800, 3800, 3802, 3801, 3801, 3802, 3804, 3803, 3804, 3804, 3806, 3805, 3805, 3806, 3807, 3806, 3806, 3807, 3809, 3808, 3809, 3809, 3811, 3810, 3810, 3811, 3813, 3812, 3813, 3813, 3815, 3814, 3814, 3815, 3816, 3815, 3815, 3816, 3818, 3817, 3818, 3818, 3820, 3819, 3820, 3820, 3822, 3821, 3821, 3822, 3824, 3823, 3824, 3824, 3826, 3825, 3825, 3826, 3827, 3826, 3826, 3827, 3829, 3828, 3829, 3829, 3831, 3830, 3830, 3831, 3833, 3832, 3833, 3833, 3835, 3834, 3834, 3835, 3836, 3835, 3835, 3836, 3838, 3837, 3838, 3838, 3840, 3839, 3839, 3840, 3842, 3841, 3842, 3842, 3844, 3843, 3843, 3844, 3845, 3844, 3844, 3845, 3847, 3846, 3847, 3847, 3849, 3848, 3848, 3849, 3850, 3849, 3849, 3850, 3852, 3851, 3852, 3852, 3854, 3853, 3853, 3854, 3856, 3855, 3856, 3856, 3858, 3857, 3857, 3858, 3859, 3858, 3858, 3859, 3861, 3860, 3861, 3861, 3863, 3862, 3862, 3863, 3865, 3864, 3865, 3865, 3867, 3866, 3866, 3867, 3868, 3867, 3867, 3868, 3870, 3869, 3869, 3870, 3872, 3871, 3872, 3872, 3874, 3873, 3873, 3874, 3875, 3874, 3874, 3875, 3877, 3876, 3877, 3877, 3879, 3878, 3878, 3879, 3881, 3880, 3881, 3881, 3883, 3882, 3882, 3882, 3884, 3883, 3883, 3884, 3886, 3885, 3885, 3886, 3887, 3886, 3886, 3887, 3889, 3888, 3888, 3889, 3891, 3890, 3891, 3891, 3893, 3892, 3892, 3892, 3894, 3893, 3893, 3894, 3896, 3895, 3895, 3896, 3898, 3897, 3898, 3898, 3900, 3899, 3899, 3899, 3901, 3900, 3900, 3901, 3903, 3902, 3902, 3903, 3904, 3903, 3903, 3904, 3906, 3905, 3905, 3906, 3908, 3907, 3908, 3908, 3910, 3909, 3909, 3909, 3911, 3910, 3910, 3911, 3913, 3912, 3912, 3913, 3915, 3914, 3915, 3915, 3917, 3916, 3916, 3916, 3918, 3917, 3917, 3918, 3920, 3919, 3919, 3920, 3921, 3920, 3920, 3921, 3923, 3922, 3922, 3923, 3925, 3924, 3925, 3925, 3927, 3926, 3926, 3926, 3928, 3927, 3927, 3928, 3930, 3929, 3929, 3930, 3932, 3931, 3932, 3932, 3934, 3933, 3933, 3933, 3935, 3934, 3934, 3935, 3937, 3936, 3936, 3936, 3938, 3937, 3937, 3938, 3940, 3939, 3939, 3940, 3942, 3941, 3942, 3942, 3944, 3943, 3943, 3943, 3945, 3944, 3944, 3945, 3947, 3946, 3946, 3947, 3949, 3948, 3949, 3949, 3951, 3950, 3950, 3950, 3952, 3951, 3951, 3952, 3954, 3953, 3953, 3953, 3955, 3954, 3954, 3955, 3957, 3956, 3957, 3957, 3959, 3958, 3958, 3958, 3960, 3959, 3959, 3960, 3962, 3961, 3961, 3961, 3963, 3962, 3962, 3963, 3965, 3964, 3964, 3965, 3967, 3966, 3967, 3967, 3969, 3968, 3968, 3968, 3970, 3969, 3969, 3970, 3972, 3971, 3971, 3972, 3974, 3973, 3974, 3974, 3976, 3975, 3975, 3975, 3977, 3976, 3976, 3977, 3979, 3978, 3978, 3978, 3980, 3979, 3979, 3980, 3982, 3981, 3981, 3982, 3984, 3983, 3983, 3984, 3986, 3985, 3986, 3986, 3988, 3987, 3987, 3987, 3989, 3988, 3988, 3989, 3991, 3990, 3990, 3990, 3992, 3991, 3991, 3992, 3994, 3993, 3993, 3994, 3996, 3995, 3995, 3996, 3998, 3997, 3997, 3997, 3999, 3998, 3998, 3999, 4001, 4000, 4000, 4001, 4003, 4002, 4002, 4003, 4005, 4004, 4004, 4004, 4006, 4005, 4005, 4006, 4008, 4007, 4007, 4007, 4009, 4008, 4008, 4009, 4011, 4010, 4010, 4011, 4013, 4012, 4012, 4013, 4015, 4014, 4014, 4014, 4016, 4015, 4015, 4016, 4018, 4017, 4017, 4017, 4019, 4018, 4018, 4019, 4021, 4020, 4020, 4021, 4023, 4022, 4022, 4023, 4025, 4024, 4024, 4025, 4027, 4026, 4026, 4026, 4028, 4027, 4027, 4028, 4030, 4029, 4029, 4029, 4031, 4030, 4030, 4031, 4033, 4032, 4032, 4033, 4035, 4034, 4034, 4035, 4037, 4036, 4036, 4036, 4038, 4037, 4037, 4038, 4040, 4039, 4039, 4039, 4041, 4040, 4040, 4041, 4043, 4042, 4042, 4043, 4045, 4044, 4044, 4045, 4047, 4046, 4046, 4047, 4049, 4048, 4048, 4048, 4050, 4049, 4049, 4050, 4052, 4051, 4051, 4051, 4053, 4052, 4052, 4053, 4055, 4054, 4054, 4055, 4057, 4056, 4056, 4057, 4059, 4058, 4058, 4058, 4060, 4059, 4059, 4060, 4062, 4061, 4061, 4061, 4062, 4062, 4062, 4063, 4064, 4064, 4064, 4065, 4066, 4066, 4066, 4067, 4068, 4068, 4068, 4069, 4070, 4070, 4070, 4070, 4071, 4071, 4071, 4072, 4073, 4073, 4073, 4073, 4074, 4074, 4074, 4075, 4076, 4076, 4076, 4077, 4078, 4078, 4078, 4079, 4080, 4080, 4080, 4080, 4081, 4081, 4081, 4082, 4083, 4083, 4083, 4083, 4084, 4084, 4084, 4085, 4086, 4086, 4086, 4087, 4088, 4088, 4088, 4089, 4090, 4090, 4091, 4092, 4093, 4093, 4094, 4095] + # 14-bit + gamma_lut_14: [0, 11, 22, 32, 43, 53, 64, 74, 83, 93, 102, 110, 119, 127, 134, 141, 148, 154, 160, 165, 170, 174, 178, 182, 186, 190, 193, 196, 199, 202, 205, 209, 212, 215, 219, 223, 227, 231, 235, 239, 244, 248, 252, 257, 262, 266, 271, 275, 280, 284, 288, 293, 297, 301, 305, 309, 313, 317, 321, 325, 329, 332, 336, 340, 344, 348, 352, 356, 360, 364, 368, 372, 376, 380, 384, 388, 392, 396, 400, 404, 408, 412, 416, 420, 424, 427, 431, 435, 439, 443, 447, 451, 455, 459, 464, 468, 472, 476, 480, 484, 489, 493, 497, 501, 506, 510, 514, 519, 523, 527, 531, 536, 540, 544, 548, 552, 556, 560, 564, 568, 572, 576, 580, 584, 588, 592, 596, 600, 604, 608, 612, 616, 620, 623, 627, 631, 636, 639, 643, 647, 652, 656, 660, 664, 668, 672, 676, 680, 684, 688, 692, 696, 700, 704, 708, 712, 716, 720, 724, 728, 732, 736, 739, 743, 747, 751, 755, 759, 763, 767, 771, 775, 779, 783, 787, 792, 796, 800, 804, 808, 813, 817, 821, 825, 830, 834, 838, 842, 847, 851, 855, 860, 864, 868, 872, 876, 880, 884, 887, 891, 896, 899, 903, 907, 912, 915, 919, 924, 928, 932, 936, 940, 944, 948, 953, 957, 961, 966, 970, 974, 979, 983, 987, 991, 996, 1000, 1004, 1008, 1012, 1016, 1020, 1024, 1028, 1032, 1036, 1040, 1044, 1048, 1052, 1056, 1060, 1064, 1067, 1071, 1075, 1079, 1083, 1087, 1091, 1095, 1099, 1103, 1107, 1111, 1115, 1120, 1124, 1128, 1131, 1135, 1140, 1143, 1147, 1151, 1156, 1159, 1163, 1167, 1172, 1175, 1179, 1184, 1188, 1191, 1195, 1199, 1203, 1207, 1211, 1215, 1219, 1223, 1227, 1231, 1235, 1239, 1243, 1247, 1252, 1256, 1260, 1264, 1268, 1272, 1277, 1281, 1285, 1289, 1294, 1298, 1303, 1307, 1311, 1315, 1320, 1324, 1327, 1332, 1336, 1339, 1343, 1347, 1352, 1355, 1359, 1363, 1368, 1371, 1375, 1379, 1384, 1387, 1391, 1395, 1400, 1403, 1407, 1411, 1416, 1420, 1423, 1428, 1432, 1436, 1440, 1444, 1448, 1451, 1455, 1458, 1462, 1465, 1469, 1473, 1477, 1480, 1484, 1488, 1492, 1495, 1499, 1503, 1508, 1511, 1515, 1520, 1524, 1528, 1532, 1537, 1541, 1545, 1549, 1554, 1559, 1563, 1567, 1571, 1576, 1579, 1583, 1587, 1591, 1594, 1598, 1602, 1606, 1609, 1613, 1616, 1621, 1624, 1628, 1632, 1636, 1639, 1643, 1647, 1651, 1655, 1658, 1663, 1667, 1671, 1675, 1679, 1683, 1687, 1691, 1695, 1700, 1703, 1707, 1711, 1715, 1718, 1722, 1726, 1730, 1733, 1737, 1741, 1745, 1748, 1752, 1756, 1760, 1763, 1766, 1770, 1774, 1778, 1781, 1785, 1789, 1792, 1796, 1800, 1804, 1808, 1811, 1815, 1820, 1823, 1827, 1830, 1834, 1838, 1841, 1845, 1849, 1853, 1856, 1860, 1864, 1868, 1871, 1875, 1880, 1883, 1886, 1890, 1894, 1898, 1901, 1905, 1909, 1912, 1916, 1920, 1924, 1928, 1931, 1935, 1940, 1943, 1946, 1950, 1954, 1958, 1961, 1965, 1969, 1972, 1976, 1980, 1984, 1988, 1991, 1995, 2000, 2003, 2006, 2010, 2014, 2017, 2021, 2025, 2029, 2032, 2036, 2040, 2044, 2048, 2051, 2055, 2060, 2063, 2067, 2070, 2074, 2078, 2081, 2085, 2089, 2093, 2096, 2100, 2105, 2108, 2112, 2116, 2120, 2123, 2126, 2129, 2133, 2136, 2139, 2143, 2147, 2150, 2153, 2157, 2161, 2164, 2168, 2171, 2176, 2179, 2182, 2186, 2190, 2193, 2197, 2201, 2205, 2208, 2212, 2216, 2220, 2224, 2227, 2231, 2236, 2239, 2242, 2245, 2249, 2252, 2255, 2259, 2263, 2266, 2269, 2273, 2277, 2280, 2284, 2287, 2292, 2295, 2298, 2302, 2306, 2309, 2313, 2317, 2321, 2324, 2328, 2332, 2336, 2340, 2343, 2347, 2352, 2355, 2358, 2362, 2365, 2368, 2372, 2375, 2379, 2382, 2386, 2389, 2393, 2396, 2400, 2404, 2408, 2410, 2414, 2417, 2421, 2424, 2427, 2431, 2435, 2438, 2441, 2445, 2449, 2452, 2456, 2460, 2464, 2466, 2470, 2473, 2477, 2480, 2483, 2486, 2490, 2493, 2497, 2501, 2505, 2508, 2511, 2515, 2520, 2523, 2526, 2530, 2534, 2537, 2541, 2545, 2549, 2552, 2556, 2560, 2564, 2568, 2571, 2575, 2580, 2583, 2586, 2589, 2593, 2596, 2600, 2603, 2607, 2610, 2613, 2617, 2621, 2624, 2628, 2631, 2636, 2638, 2641, 2645, 2649, 2652, 2655, 2658, 2662, 2665, 2669, 2673, 2677, 2680, 2683, 2687, 2691, 2694, 2698, 2701, 2705, 2708, 2712, 2715, 2719, 2722, 2726, 2729, 2733, 2737, 2740, 2744, 2747, 2750, 2753, 2756, 2760, 2762, 2765, 2768, 2772, 2775, 2778, 2781, 2785, 2788, 2792, 2795, 2799, 2802, 2806, 2810, 2814, 2817, 2820, 2824, 2829, 2832, 2836, 2840, 2844, 2847, 2851, 2855, 2859, 2862, 2865, 2869, 2872, 2875, 2878, 2881, 2885, 2888, 2891, 2894, 2898, 2901, 2904, 2908, 2911, 2914, 2917, 2920, 2924, 2927, 2930, 2934, 2938, 2941, 2944, 2948, 2952, 2956, 2959, 2963, 2967, 2970, 2974, 2977, 2981, 2984, 2987, 2991, 2995, 2998, 3001, 3005, 3009, 3012, 3016, 3019, 3023, 3026, 3029, 3032, 3036, 3038, 3041, 3045, 3048, 3051, 3054, 3058, 3062, 3064, 3068, 3071, 3075, 3078, 3081, 3085, 3089, 3091, 3095, 3098, 3102, 3105, 3109, 3113, 3117, 3120, 3123, 3127, 3131, 3134, 3137, 3140, 3144, 3147, 3150, 3153, 3157, 3160, 3163, 3166, 3170, 3173, 3176, 3179, 3183, 3186, 3189, 3192, 3196, 3198, 3201, 3205, 3208, 3211, 3214, 3218, 3222, 3225, 3228, 3231, 3235, 3238, 3241, 3244, 3247, 3250, 3253, 3256, 3260, 3263, 3266, 3269, 3273, 3276, 3279, 3283, 3287, 3290, 3293, 3297, 3301, 3303, 3306, 3310, 3314, 3317, 3321, 3324, 3329, 3332, 3335, 3339, 3343, 3346, 3349, 3352, 3356, 3359, 3361, 3365, 3369, 3371, 3374, 3378, 3382, 3385, 3388, 3391, 3395, 3398, 3401, 3404, 3408, 3410, 3413, 3416, 3420, 3423, 3426, 3429, 3434, 3436, 3440, 3443, 3447, 3450, 3453, 3456, 3460, 3462, 3465, 3468, 3472, 3475, 3478, 3481, 3486, 3488, 3492, 3495, 3499, 3502, 3505, 3508, 3512, 3514, 3517, 3521, 3525, 3527, 3530, 3534, 3538, 3541, 3544, 3547, 3551, 3554, 3556, 3559, 3562, 3564, 3567, 3570, 3574, 3576, 3579, 3582, 3586, 3589, 3592, 3595, 3599, 3602, 3605, 3608, 3612, 3615, 3618, 3622, 3626, 3629, 3632, 3636, 3641, 3644, 3647, 3651, 3655, 3658, 3660, 3664, 3667, 3669, 3672, 3675, 3679, 3681, 3684, 3687, 3691, 3693, 3696, 3699, 3703, 3706, 3708, 3711, 3715, 3717, 3720, 3724, 3728, 3730, 3733, 3737, 3741, 3744, 3747, 3751, 3755, 3758, 3761, 3764, 3768, 3770, 3773, 3777, 3781, 3783, 3786, 3790, 3794, 3797, 3800, 3803, 3807, 3809, 3812, 3815, 3819, 3821, 3823, 3826, 3830, 3832, 3835, 3838, 3842, 3845, 3848, 3851, 3855, 3858, 3860, 3864, 3867, 3870, 3873, 3876, 3880, 3883, 3886, 3889, 3894, 3896, 3900, 3903, 3907, 3909, 3912, 3915, 3919, 3921, 3923, 3926, 3930, 3932, 3935, 3938, 3942, 3945, 3948, 3951, 3955, 3958, 3960, 3963, 3967, 3970, 3972, 3976, 3980, 3982, 3985, 3989, 3993, 3996, 3999, 4003, 4007, 4010, 4012, 4015, 4019, 4021, 4023, 4027, 4031, 4033, 4035, 4039, 4043, 4045, 4048, 4051, 4055, 4057, 4060, 4063, 4066, 4068, 4071, 4074, 4078, 4080, 4083, 4086, 4090, 4093, 4096, 4099, 4103, 4105, 4108, 4111, 4114, 4116, 4119, 4122, 4126, 4128, 4131, 4134, 4138, 4141, 4144, 4147, 4151, 4153, 4156, 4159, 4162, 4164, 4167, 4170, 4174, 4176, 4179, 4182, 4186, 4189, 4192, 4195, 4199, 4201, 4204, 4207, 4210, 4212, 4215, 4218, 4222, 4224, 4227, 4230, 4234, 4237, 4240, 4243, 4247, 4249, 4252, 4255, 4258, 4260, 4263, 4266, 4270, 4272, 4275, 4278, 4282, 4285, 4288, 4291, 4295, 4297, 4300, 4303, 4306, 4308, 4311, 4314, 4318, 4320, 4323, 4326, 4330, 4333, 4336, 4339, 4343, 4345, 4348, 4351, 4354, 4356, 4359, 4362, 4366, 4368, 4371, 4374, 4378, 4381, 4384, 4387, 4391, 4393, 4396, 4399, 4403, 4405, 4407, 4410, 4414, 4416, 4419, 4423, 4427, 4429, 4432, 4435, 4439, 4441, 4443, 4446, 4449, 4451, 4453, 4456, 4460, 4462, 4464, 4467, 4471, 4473, 4476, 4479, 4483, 4485, 4487, 4490, 4494, 4496, 4498, 4501, 4505, 4507, 4510, 4514, 4518, 4520, 4523, 4527, 4531, 4533, 4536, 4539, 4543, 4544, 4547, 4550, 4554, 4556, 4559, 4563, 4567, 4569, 4572, 4575, 4579, 4581, 4583, 4586, 4590, 4591, 4594, 4597, 4600, 4602, 4604, 4608, 4611, 4614, 4616, 4619, 4623, 4625, 4627, 4630, 4633, 4634, 4637, 4640, 4643, 4645, 4648, 4651, 4655, 4657, 4660, 4663, 4667, 4669, 4671, 4674, 4678, 4680, 4682, 4686, 4690, 4692, 4695, 4698, 4702, 4705, 4708, 4711, 4715, 4717, 4719, 4722, 4726, 4727, 4729, 4733, 4736, 4738, 4740, 4744, 4747, 4749, 4752, 4755, 4759, 4761, 4763, 4766, 4769, 4771, 4773, 4776, 4780, 4781, 4784, 4787, 4791, 4793, 4796, 4799, 4803, 4805, 4807, 4810, 4813, 4815, 4817, 4820, 4824, 4826, 4828, 4831, 4835, 4837, 4840, 4843, 4847, 4849, 4851, 4854, 4857, 4859, 4861, 4864, 4868, 4869, 4872, 4875, 4879, 4881, 4884, 4887, 4891, 4893, 4895, 4898, 4901, 4903, 4905, 4908, 4912, 4913, 4916, 4919, 4923, 4925, 4928, 4931, 4935, 4937, 4939, 4942, 4945, 4947, 4949, 4952, 4956, 4957, 4960, 4963, 4967, 4969, 4972, 4975, 4979, 4981, 4983, 4986, 4989, 4990, 4993, 4996, 5000, 5001, 5004, 5007, 5011, 5013, 5016, 5019, 5023, 5025, 5027, 5030, 5033, 5035, 5037, 5040, 5044, 5046, 5048, 5051, 5055, 5057, 5060, 5063, 5067, 5068, 5070, 5073, 5076, 5077, 5079, 5082, 5086, 5087, 5089, 5092, 5096, 5098, 5100, 5103, 5107, 5108, 5110, 5113, 5117, 5118, 5120, 5123, 5127, 5129, 5131, 5135, 5139, 5141, 5144, 5147, 5151, 5153, 5155, 5158, 5161, 5163, 5165, 5168, 5172, 5174, 5176, 5180, 5183, 5185, 5188, 5191, 5195, 5196, 5198, 5201, 5204, 5205, 5207, 5210, 5213, 5215, 5217, 5220, 5224, 5226, 5228, 5231, 5235, 5237, 5239, 5241, 5245, 5246, 5249, 5252, 5256, 5257, 5260, 5263, 5267, 5269, 5272, 5275, 5279, 5280, 5282, 5285, 5288, 5289, 5291, 5294, 5297, 5299, 5301, 5304, 5308, 5309, 5312, 5315, 5319, 5321, 5323, 5326, 5329, 5331, 5333, 5336, 5340, 5342, 5344, 5347, 5351, 5353, 5356, 5359, 5363, 5364, 5366, 5368, 5371, 5372, 5374, 5376, 5379, 5380, 5382, 5385, 5389, 5390, 5392, 5395, 5399, 5400, 5402, 5405, 5409, 5410, 5412, 5416, 5419, 5421, 5424, 5427, 5431, 5433, 5436, 5439, 5443, 5444, 5446, 5448, 5451, 5452, 5454, 5456, 5459, 5461, 5462, 5465, 5469, 5470, 5472, 5475, 5479, 5480, 5482, 5485, 5489, 5490, 5492, 5495, 5499, 5501, 5504, 5507, 5511, 5513, 5516, 5519, 5523, 5524, 5526, 5528, 5531, 5532, 5534, 5536, 5539, 5540, 5542, 5545, 5549, 5550, 5552, 5555, 5559, 5560, 5562, 5565, 5568, 5570, 5572, 5575, 5579, 5581, 5583, 5587, 5591, 5593, 5596, 5599, 5603, 5604, 5606, 5608, 5611, 5612, 5614, 5617, 5620, 5621, 5623, 5626, 5629, 5630, 5633, 5635, 5639, 5640, 5642, 5644, 5647, 5648, 5650, 5653, 5657, 5658, 5660, 5663, 5667, 5669, 5672, 5675, 5679, 5680, 5682, 5685, 5688, 5689, 5691, 5694, 5698, 5699, 5701, 5704, 5708, 5710, 5712, 5715, 5719, 5720, 5721, 5724, 5727, 5728, 5729, 5732, 5735, 5736, 5738, 5741, 5745, 5746, 5748, 5751, 5755, 5756, 5758, 5760, 5763, 5764, 5766, 5769, 5773, 5774, 5776, 5779, 5783, 5785, 5788, 5791, 5795, 5796, 5798, 5801, 5804, 5805, 5807, 5810, 5814, 5815, 5817, 5820, 5824, 5826, 5828, 5831, 5835, 5836, 5838, 5840, 5843, 5844, 5846, 5848, 5852, 5853, 5855, 5857, 5861, 5862, 5864, 5867, 5871, 5872, 5873, 5875, 5878, 5879, 5881, 5883, 5887, 5888, 5890, 5893, 5896, 5898, 5900, 5903, 5907, 5908, 5910, 5912, 5916, 5917, 5919, 5922, 5925, 5927, 5929, 5932, 5936, 5938, 5940, 5943, 5947, 5948, 5950, 5952, 5955, 5956, 5958, 5960, 5964, 5965, 5966, 5969, 5973, 5974, 5976, 5979, 5983, 5984, 5985, 5988, 5991, 5991, 5993, 5996, 5999, 6000, 6002, 6005, 6009, 6010, 6012, 6015, 6019, 6020, 6021, 6024, 6027, 6027, 6029, 6032, 6035, 6036, 6038, 6041, 6045, 6046, 6048, 6051, 6055, 6056, 6057, 6060, 6063, 6063, 6065, 6068, 6071, 6072, 6074, 6077, 6081, 6082, 6084, 6087, 6091, 6092, 6093, 6096, 6099, 6099, 6101, 6104, 6107, 6108, 6110, 6113, 6117, 6118, 6120, 6123, 6127, 6128, 6129, 6132, 6135, 6135, 6137, 6140, 6143, 6144, 6146, 6149, 6153, 6154, 6156, 6159, 6163, 6164, 6165, 6168, 6171, 6171, 6173, 6176, 6179, 6180, 6182, 6185, 6189, 6190, 6192, 6195, 6199, 6200, 6201, 6203, 6207, 6207, 6209, 6211, 6215, 6216, 6218, 6221, 6224, 6226, 6228, 6231, 6235, 6236, 6237, 6240, 6243, 6244, 6245, 6248, 6252, 6253, 6254, 6257, 6261, 6262, 6264, 6267, 6271, 6271, 6273, 6275, 6278, 6278, 6279, 6282, 6285, 6286, 6287, 6290, 6293, 6294, 6296, 6299, 6303, 6304, 6305, 6307, 6310, 6311, 6313, 6315, 6319, 6320, 6322, 6325, 6329, 6330, 6332, 6335, 6339, 6339, 6341, 6343, 6346, 6346, 6347, 6350, 6353, 6354, 6355, 6358, 6361, 6363, 6364, 6367, 6371, 6372, 6373, 6375, 6378, 6379, 6381, 6383, 6387, 6388, 6390, 6393, 6397, 6398, 6400, 6403, 6407, 6407, 6409, 6411, 6414, 6414, 6415, 6418, 6421, 6422, 6423, 6426, 6429, 6430, 6432, 6435, 6439, 6440, 6441, 6443, 6446, 6447, 6449, 6451, 6455, 6456, 6458, 6461, 6465, 6466, 6468, 6471, 6475, 6475, 6477, 6479, 6482, 6482, 6483, 6486, 6489, 6490, 6491, 6494, 6497, 6498, 6500, 6503, 6507, 6507, 6509, 6511, 6514, 6515, 6517, 6519, 6523, 6524, 6526, 6529, 6533, 6534, 6536, 6539, 6543, 6543, 6545, 6547, 6550, 6550, 6551, 6554, 6557, 6558, 6559, 6562, 6565, 6566, 6568, 6571, 6575, 6575, 6577, 6579, 6582, 6583, 6584, 6587, 6591, 6592, 6594, 6597, 6600, 6602, 6604, 6607, 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16335, 16335, 16337, 16341, 16338, 16336, 16337, 16339, 16336, 16334, 16336, 16340, 16337, 16336, 16339, 16343, 16342, 16342, 16345, 16349, 16346, 16344, 16345, 16348, 16344, 16343, 16345, 16349, 16346, 16345, 16347, 16352, 16350, 16350, 16353, 16357, 16354, 16352, 16353, 16355, 16352, 16351, 16352, 16356, 16353, 16353, 16355, 16359, 16358, 16358, 16361, 16365, 16362, 16360, 16361, 16364, 16361, 16360, 16362, 16366, 16363, 16363, 16366, 16370, 16369, 16369, 16372, 16377, 16374, 16373, 16374, 16377, 16374, 16373, 16375, 16379, 16376, 16376, 16379, 16383, 16381, 16381, 16383] + is_save: False + +auto_exposure: + is_enable: True + is_debug: True + stats_window_offset: [4, 4, 4, 4] + center_illuminance: 90 + histogram_skewness: 0.9 + +color_space_conversion: + conv_standard: 2 + is_save: False + +2d_noise_reduction: + is_enable: True + window_size: 9 + wts: 5 + is_save: False + +rgb_conversion: + is_enable: True + is_save: False + +invalid_region_crop: + # 1: 1920x1080, 2: 1920x1440 + is_enable: False + crop_to_size: 2 + height_start_idx: 40 + width_start_idx: 40 + is_debug: True + is_save: False + +on_screen_display: + is_enable: True + is_debug: False + height: 64 + width: 128 + x_offset: 50 + y_offset: 50 + fg_color: [0, 90, 160] + bg_color: [255, 255, 255] + alpha: 50 + is_save: False + +scale: + is_enable: False + is_debug: True + new_width: 960 + new_height: 720 + is_save: False + +yuv_conversion_format: + is_enable: False + conv_type: '422' + is_save: False diff --git a/tests/test_pipleine_output.py b/tests/test_pipleine_output.py new file mode 100644 index 0000000..2ed55f4 --- /dev/null +++ b/tests/test_pipleine_output.py @@ -0,0 +1,82 @@ +""" +File: test_pipeline_output.py +Description: Basic tests to ensure the pipeline is functioning correctly. + All tests are executed using files in test_data folder. +Author: 10xEngineers Pvt Ltd +------------------------------------------------------------ +""" + +from pathlib import Path +import sys + +sys.path.append(".") +import shutil +import numpy as np +import matplotlib.pyplot as plt +import yaml +from infinite_isp import InfiniteISP + + +def test_output_not_blank(): + """Test to verify the pipeline output is not blank (zero frame).""" + + # + raw_path = Path("./tests/test_data") + config_path = raw_path / "Indoor1_2592x1536_10bit_GRBG-configs.yml" + filemane = "Indoor1_2592x1536_10bit_GRBG.raw" + + # run pipeline on test data + inf_isp = InfiniteISP(raw_path, config_path) + inf_isp.set_save_paths(Path("./tests")) + inf_isp.execute(img_path=filemane) + + # load output + out_path = Path("./tests/out_frames") + out_filename = list(out_path.glob(r"*Indoor1_2592x1536_10bit_GRBG*.png")) + + assert len(out_filename) == 1, "Output file not generated by infiniteISP pipeline!" + + out_png_path = out_filename[0] + out_img = plt.imread(str(out_png_path.resolve())) + + # Check if all pixel values in the image are zero + assert not np.all(out_img == 0), "The output frame has all zeros!" + + # restore directory state + shutil.rmtree("./tests/out_frames") + shutil.rmtree("./tests/config") + + +def test_default_config_state(): + """Test to check the default state of the config file. This configuration has + been tuned for the sample image ColorChecker_2592x1536_10bit_GRBG.""" + + # Load the default config from test_data + with open("./tests/test_data/default_configs.yml", "r", encoding="utf-8") as file: + def_config = yaml.safe_load(file) + + # load the config in RM directory + with open("./config/configs.yml", "r", encoding="utf-8") as file: + rm_config = yaml.safe_load(file) + + assert def_config["platform"] == rm_config["platform"] + assert def_config["sensor_info"] == rm_config["sensor_info"] + assert def_config["crop"] == rm_config["crop"] + assert def_config["dead_pixel_correction"] == rm_config["dead_pixel_correction"] + assert def_config["black_level_correction"] == rm_config["black_level_correction"] + assert def_config["oecf"] == rm_config["oecf"] + assert def_config["digital_gain"] == rm_config["digital_gain"] + assert def_config["bayer_noise_reduction"] == rm_config["bayer_noise_reduction"] + assert def_config["auto_white_balance"] == rm_config["auto_white_balance"] + assert def_config["white_balance"] == rm_config["white_balance"] + assert def_config["demosaic"] == rm_config["demosaic"] + assert def_config["color_correction_matrix"] == rm_config["color_correction_matrix"] + assert def_config["gamma_correction"] == rm_config["gamma_correction"] + assert def_config["auto_exposure"] == rm_config["auto_exposure"] + assert def_config["color_space_conversion"] == rm_config["color_space_conversion"] + assert def_config["2d_noise_reduction"] == rm_config["2d_noise_reduction"] + assert def_config["rgb_conversion"] == rm_config["rgb_conversion"] + assert def_config["invalid_region_crop"] == rm_config["invalid_region_crop"] + assert def_config["on_screen_display"] == rm_config["on_screen_display"] + assert def_config["scale"] == rm_config["scale"] + assert def_config["yuv_conversion_format"] == rm_config["yuv_conversion_format"] diff --git a/util/config_utils.py b/util/config_utils.py index 450b0c3..66657b8 100644 --- a/util/config_utils.py +++ b/util/config_utils.py @@ -27,7 +27,6 @@ def extract_raw_metadata(filename): Extract Exif/Metadata Information from Raw File """ with rawpy.imread(filename) as raw: - # Get the Bayer pattern # The pattern is returned as a 2D numpy array, where 0=red, 1=green, 2=blue bayer_array = raw.raw_pattern diff --git a/util/utils.py b/util/utils.py index dbba31d..c7195f6 100644 --- a/util/utils.py +++ b/util/utils.py @@ -5,7 +5,6 @@ Author: 10xEngineers Pvt Ltd ------------------------------------------------------------ """ -import os from datetime import datetime import random import warnings @@ -16,15 +15,8 @@ from scipy.signal import correlate2d import matplotlib.pyplot as plt -# Infinite-ISP output directory -OUTPUT_DIR = "out_frames/" - -# Output directory for Generated Test Vectors -OUTPUT_ARRAY_DIR = "./test_vectors/Results/" - def introduce_defect(img, total_defective_pixels, padding): - """ This function randomly replaces pixels values with extremely high or low pixel values to create dead pixels (Dps). @@ -121,7 +113,6 @@ def gauss_kern_raw(size, std_dev, stride): def crop(img, rows_to_crop=0, cols_to_crop=0): - """ Crop 2D array. Parameter: @@ -172,14 +163,14 @@ def approx_sqrt(number, num_iterations=5): Get Approximate Square_root of a Number """ # Initial estimate - sqrt = number / 2 + sqrt = np.uint64(number / 2) # Only five iterations are performed to get an approximate square-root for _ in range(num_iterations): - n_by_sqrt, _ = get_approximate(number / sqrt, 46, 16) - sqrt = (sqrt + n_by_sqrt) / 2 + n_by_sqrt = np.uint64(np.uint64(number) / sqrt) + sqrt = np.uint64((sqrt + n_by_sqrt) / 2) # print(sqrt) # Integer is returned to reduce algorithm complexity - return np.round(sqrt, 3).astype(np.int32) + return sqrt.astype(np.uint64) def display_ae_statistics(ae_feedback, awb_gains): @@ -254,114 +245,6 @@ def get_image_from_yuv_format_conversion(yuv_img, height, width, yuv_custom_form return yuv_img -def rev_yuv(arr): - """This function reverses the order of YUV channels in yuv image ARR.""" - if len(arr.shape) != 3: - print("Input array must be 3D. Input array not modified.") - return - - # Swaps U and V channel for YUV Image - out_arr = np.zeros(arr.shape, arr.dtype) - out_arr[:, :, 0] = arr[:, :, 2] - out_arr[:, :, 1] = arr[:, :, 1] - out_arr[:, :, 2] = arr[:, :, 0] - - return out_arr - - -def save_output_array(img_name, output_array, module_name, platform, bitdepth): - """ - Saves output array [raw/rgb] for pipline modules - """ - # if automation is not being executed, the output directory needs to be created - if not platform["generate_tv"]: - # create directory to save array - if not os.path.exists(OUTPUT_ARRAY_DIR): - Path(OUTPUT_ARRAY_DIR).mkdir(parents=True, exist_ok=False) - - # filename identifies input image and isp pipeline module for which testing - # vector is generated - filename = OUTPUT_ARRAY_DIR + module_name + img_name.split(".")[0] - - if platform["save_format"] == "npy" or platform["save_format"] == "both": - - # save image as npy array - np.save(filename, output_array.astype("uint16")) - - if platform["save_format"] == "png" or platform["save_format"] == "both": - - # convert image to 8-bit image if required - if output_array.dtype != np.uint8 and len(output_array.shape) > 2: - shift_by = bitdepth - 8 - output_array = (output_array >> shift_by).astype("uint8") - - # save Image as .png - plt.imsave(filename + ".png", output_array) - - -def save_output_array_yuv(img_name, output_array, module_name, platform): - """ - Saves output array [yuv] for pipline modules - """ - # if automation is not being executed, the output directory needs to be created - if not platform["generate_tv"]: - # create directory to save array - if not os.path.exists(OUTPUT_ARRAY_DIR): - Path(OUTPUT_ARRAY_DIR).mkdir(parents=True, exist_ok=False) - - # filename identifies input image and isp pipeline module for which testing - # vector is generated - filename = OUTPUT_ARRAY_DIR + module_name + img_name.split(".")[0] - - # save image as .nppy array - if platform["save_format"] == "npy" or platform["save_format"] == "both": - # sawp_on is used for scenarios in devices where YUV channels are stored as YVU - # so it swaps V and U for hardware compatibility - if platform["rev_yuv_channels"]: - swapped_array = rev_yuv(output_array) - np.save(filename, swapped_array.astype("uint16")) - else: - np.save(filename, output_array.astype("uint16")) - - # save image as .png - if platform["save_format"] == "png" or platform["save_format"] == "both": - plt.imsave(filename + ".png", output_array) - - -def save_pipeline_output(img_name, output_img, config_file, tv_flag): - """ - Saves the output image (png) and config file in OUTPUT_DIR - """ - - # Time Stamp for output filename - dt_string = datetime.now().strftime("_%Y%m%d_%H%M%S") - - # Set list format to flowstyle to dump yaml file - yaml.add_representer(list, represent_list) - - # Storing configuration file for output image - with open( - OUTPUT_DIR + img_name + dt_string + ".yaml", "w", encoding="utf-8" - ) as file: - yaml.dump( - config_file, - file, - sort_keys=False, - Dumper=CustomDumper, - width=17000, - ) - - # Save Image as .png - plt.imsave(OUTPUT_DIR + img_name + dt_string + ".png", output_img) - - # If tv_flag is true then one copy of out image is also stored in test_vectors folder - if tv_flag: - Path((OUTPUT_ARRAY_DIR + OUTPUT_DIR)[0:-1]).mkdir(parents=True, exist_ok=True) - plt.imsave( - OUTPUT_ARRAY_DIR + OUTPUT_DIR + img_name + dt_string + ".png", output_img - ) - - def create_coeff_file(numbers, filename, weight_bits): """ Creating file for coefficients @@ -419,3 +302,108 @@ def represent_list(self, data): """This function ensures that the lookup table are stored on flow style to keep the saved yaml file readable.""" return self.represent_sequence("tag:yaml.org,2002:seq", data, flow_style=True) + + +class SaveOutput: + """Class to save module or pipeline output""" + + def __init__(self): + self.pipleine_outpath = Path("./out_frames") + self.module_outpath = Path("./out_frames/module_output") + self.config_outpath = Path("./out_frames") + self.create_out_dirs() + + def create_out_dirs(self): + """Create directories if it does not exist.""" + for path in [self.pipleine_outpath, self.module_outpath, self.config_outpath]: + if not path.exists(): + path.mkdir(parents=True, exist_ok=True) + + def reset_outpaths(self, new_pipeline_path, new_mod_path, new_config_path): + """Reset outpaths""" + self.pipleine_outpath = Path(new_pipeline_path) + self.module_outpath = Path(new_mod_path) + self.config_outpath = Path(new_config_path) + self.create_out_dirs() + + def save_output_array( + self, img_name, output_array, module_name, platform, bitdepth + ): + """ + Saves output array [raw/rgb] for pipline modules + """ + + # filename identifies input image and isp pipeline module for which the output + # array is saved + filename = self.module_outpath / (module_name + img_name.split(".")[0]) + + if platform["save_format"] == "npy" or platform["save_format"] == "both": + # save image as npy array + np.save(filename, output_array.astype("uint16")) + + if platform["save_format"] == "png" or platform["save_format"] == "both": + # convert image to 8-bit image if required + if output_array.dtype != np.uint8 and len(output_array.shape) > 2: + shift_by = bitdepth - 8 + output_array = (output_array >> shift_by).astype("uint8") + + # save Image as .png + plt.imsave(filename.with_suffix(".png"), output_array) + + def save_output_array_yuv(self, img_name, output_array, module_name, platform): + """ + Saves output array [yuv] for pipline modules + """ + + # filename identifies input image and isp pipeline module for which the output + # array is saved + filename = self.module_outpath / (module_name + img_name.split(".")[0]) + + # save image as .npy array + if platform["save_format"] == "npy" or platform["save_format"] == "both": + np.save(filename, output_array.astype("uint16")) + + # save image as .png + if platform["save_format"] == "png" or platform["save_format"] == "both": + plt.imsave(filename.with_suffix(".png"), output_array) + + def save_output_3a(self, img_name, output_array, module_name): + """Save the stats returned by the 3A module in a txt file""" + + filename = self.module_outpath / (module_name + img_name.split(".")[0]) + + if output_array is not None: + with open(filename.with_suffix(".txt"), "w", encoding="utf-8") as txt_file: + if "auto_white_balance" in module_name: + print(f"RGain = {output_array[0]}", file=txt_file) + print(f"BGain = {output_array[1]}", file=txt_file) + elif "auto_exposure" in module_name: + pass + + def save_pipeline_output(self, img_name, output_img, config_file): + """ + Saves the output image (png) and config file at pipleine_outpath + """ + + # Time Stamp for output filename + dt_string = datetime.now().strftime("_%Y%m%d_%H%M%S") + + # Set list format to flowstyle to dump yaml file + yaml.add_representer(list, represent_list) + + # Storing configuration file for output image + with open( + self.config_outpath / (img_name + dt_string + ".yaml"), + "w", + encoding="utf-8", + ) as file: + yaml.dump( + config_file, + file, + sort_keys=False, + Dumper=CustomDumper, + width=17000, + ) + + # Save Image as .png + plt.imsave(self.pipleine_outpath / (img_name + dt_string + ".png"), output_img)

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