diff --git a/proj5-video_stitching/Proj5.pdf b/proj5-video_stitching/Proj5.pdf new file mode 100644 index 0000000..40a570d Binary files /dev/null and b/proj5-video_stitching/Proj5.pdf differ diff --git a/proj5-video_stitching/Project_5.ipynb b/proj5-video_stitching/Project_5.ipynb new file mode 100644 index 0000000..0c33fdf --- /dev/null +++ b/proj5-video_stitching/Project_5.ipynb @@ -0,0 +1,901 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Programming Project #5: Video Stitching and Processing " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## CS445: Computational Photography - Fall 2019" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Part I: Stitch two key frames \"Drawing\"\n", + "\n", + "#### This involves:\n", + "1. compute homography H between two frames; \n", + "2. project each frame onto the same surface;\n", + "3. blend the surfaces.\n", + "\n", + "\n", + "\n", + "Check that your homography is correct by plotting four points that form a square in frame 270 and their projections in each image, like this:\n", + "

\n", + " \"Drawing\"/\n", + " \"Drawing\"/\n", + "

" + ] + }, + { + "cell_type": "code", + "execution_count": 78, + "metadata": {}, + "outputs": [], + "source": [ + "import cv2\n", + "import numpy as np\n", + "from numpy.linalg import svd, inv\n", + "\n", + "%matplotlib inline\n", + "from matplotlib import pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "metadata": {}, + "outputs": [], + "source": [ + "# images location\n", + "im1 = './images/input/frames/f0001.jpg'\n", + "im2 = './images/input/frames/f0270.jpg'\n", + "\n", + "# Load an color image in grayscale\n", + "im1 = cv2.imread(im1)\n", + "im1 = cv2.cvtColor(im1, cv2.COLOR_BGR2RGB)\n", + "im2 = cv2.imread(im2)\n", + "im2 = cv2.cvtColor(im2, cv2.COLOR_BGR2RGB)" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": {}, + "outputs": [], + "source": [ + "def auto_homography(Ia, Ib, homography_func=None, normalization_func=None):\n", + " '''\n", + " Computes a homography that maps points from Ia to Ib\n", + "\n", + " Input: Ia and Ib are images\n", + " Output: H is the homography\n", + "\n", + " '''\n", + " if Ia.dtype == 'float32' and Ib.dtype == 'float32':\n", + " Ia = (Ia*255).astype(np.uint8)\n", + " Ib = (Ib*255).astype(np.uint8)\n", + " \n", + " Ia_gray = cv2.cvtColor(Ia,cv2.COLOR_BGR2GRAY)\n", + " Ib_gray = cv2.cvtColor(Ib,cv2.COLOR_BGR2GRAY)\n", + "\n", + " # Initiate SIFT detector\n", + " sift = cv2.xfeatures2d.SIFT_create()\n", + " \n", + " # find the keypoints and descriptors with SIFT\n", + " kp_a, des_a = sift.detectAndCompute(Ia_gray,None)\n", + " kp_b, des_b = sift.detectAndCompute(Ib_gray,None) \n", + " \n", + " # BFMatcher with default params\n", + " bf = cv2.BFMatcher()\n", + " matches = bf.knnMatch(des_a,des_b, k=2)\n", + "\n", + " # Apply ratio test\n", + " good = []\n", + " for m,n in matches:\n", + " if m.distance < 0.85*n.distance:\n", + " good.append(m)\n", + " \n", + " numMatches = int(len(good))\n", + "\n", + " matches = good\n", + "\n", + " # Xa and Xb are 3xN matrices that contain homogeneous coordinates for the N\n", + " # matching points for each image\n", + " Xa = np.ones((3,numMatches))\n", + " Xb = np.ones((3,numMatches))\n", + " \n", + " for idx, match_i in enumerate(matches):\n", + " Xa[:,idx][0:2] = kp_a[match_i.queryIdx].pt\n", + " Xb[:,idx][0:2] = kp_b[match_i.trainIdx].pt\n", + "\n", + " ## RANSAC\n", + " niter = 1000\n", + " best_score = 0\n", + "\n", + " for t in range(niter):\n", + " # estimate homography\n", + " subset = np.random.choice(numMatches, 4, replace=False)\n", + " pts1 = Xa[:,subset]\n", + " pts2 = Xb[:,subset]\n", + " \n", + " H_t = homography_func(pts1, pts2) # , normalization_func) # edit helper code below (computeHomography)\n", + "\n", + " # score homography\n", + " Xb_ = np.dot(H_t, Xa) # project points from first image to second using H\n", + " du = Xb_[0,:]/Xb_[2,:] - Xb[0,:]/Xb[2,:]\n", + " dv = Xb_[1,:]/Xb_[2,:] - Xb[1,:]/Xb[2,:]\n", + "\n", + " ok_t = np.sqrt(du**2 + dv**2) < 1 # you may need to play with this threshold\n", + " score_t = sum(ok_t)\n", + "\n", + " if score_t > best_score:\n", + " best_score = score_t\n", + " H = H_t\n", + " in_idx = ok_t\n", + " \n", + "# print('best score: {:02f}'.format(best_score))\n", + "\n", + " # Optionally, you may want to re-estimate H based on inliers\n", + " return H" + ] + }, + { + "cell_type": "code", + "execution_count": 81, + "metadata": {}, + "outputs": [], + "source": [ + "def computeHomography(pts1, pts2):\n", + " '''\n", + " Compute homography that maps from pts1 to pts2 using least squares solver\n", + " \n", + " Input: pts1 and pts2 are 3xN matrices for N points in homogeneous\n", + " coordinates. \n", + " \n", + " Output: H is a 3x3 matrix, such that pts2~=H*pts1\n", + " '''\n", + " \n", + " A = np.zeros((8, 9))\n", + " for idx in range(pts1.shape[1]):\n", + " pt1 = pts1[:, idx]\n", + " pt2 = pts2[:, idx]\n", + " \n", + " A[idx*2, 0] = -pt1[0]\n", + " A[idx*2, 1] = -pt1[1]\n", + " A[idx*2, 2] = -1;\n", + " A[idx*2, 6] = pt1[0] * pt2[0]\n", + " A[idx*2, 7] = pt1[1] * pt2[0]\n", + " A[idx*2, 8] = pt2[0]\n", + " \n", + " A[idx*2+1, 3] = -pt1[0]\n", + " A[idx*2+1, 4] = -pt1[1]\n", + " A[idx*2+1, 5] = -1\n", + " A[idx*2+1, 6] = pt1[0] * pt2[1]\n", + " A[idx*2+1, 7] = pt1[1] * pt2[1]\n", + " A[idx*2+1, 8] = pt2[1]\n", + " \n", + " U, S, V = svd(A)\n", + " H = V[-1, :].reshape((3, 3))\n", + "\n", + " return H" + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "metadata": {}, + "outputs": [], + "source": [ + "H = auto_homography(im1,im2, homography_func=computeHomography)" + ] + }, + { + "cell_type": "code", + "execution_count": 83, + "metadata": {}, + "outputs": [], + "source": [ + "def get_translation(im1, im2, H):\n", + " height, width, _ = im1.shape\n", + " \n", + " border_pts = np.asarray([\n", + " [0, 0, width-1, width-1],\n", + " [0, height-1, 0, height-1],\n", + " [1, 1, 1, 1]])\n", + " border_pts = border_pts / border_pts[-1, :]\n", + " cvt_border_pts = np.dot(H, border_pts)\n", + " cvt_border_pts = cvt_border_pts / cvt_border_pts[-1, :]\n", + " \n", + " # Mapped coords w.r.t ref. image\n", + " x_min, x_max = np.min(cvt_border_pts[0, :]), np.max(cvt_border_pts[0, :])\n", + " y_min, y_max = np.min(cvt_border_pts[1, :]), np.max(cvt_border_pts[1, :])\n", + " \n", + " # im1 coords after translation\n", + " x_translate = max(0, -x_min); y_translate = max(0, -y_min)\n", + " im2_x_max = x_max + x_translate\n", + " im2_y_max = y_max + y_translate\n", + " \n", + " H_translate = np.eye(3)\n", + " H_translate[0, -1] = x_translate; H_translate[1, -1] = y_translate\n", + " \n", + " anchor_trans = np.dot(H_translate, border_pts)\n", + " anchor_trans = anchor_trans / anchor_trans[-1, :]\n", + " \n", + " im2_x_max = int(max(im2_x_max, anchor_trans[0, 3]))\n", + " im2_y_max = int(max(im2_y_max, anchor_trans[1, 3]))\n", + "\n", + " return H_translate, (x_min, im2_x_max, y_min, im2_y_max)" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "metadata": {}, + "outputs": [], + "source": [ + "def stitching(im1, im2, H_rotate, H_translate, width, height, stitch=True):\n", + " H_whole = np.dot(H_translate, H_rotate)\n", + " img_anchor = cv2.warpPerspective(im2, H_translate, (width+1, height+1))\n", + " img_wrapped = cv2.warpPerspective(im1, H_whole, (width+1, height+1))\n", + " \n", + " if stitch:\n", + " img_stitched = img_wrapped\n", + " occupied = np.sum(img_wrapped, axis=-1) > 0\n", + "\n", + " for h in range(img_stitched.shape[0]):\n", + " for w in range(img_stitched.shape[1]):\n", + " if not occupied[h, w]:\n", + " img_stitched[h, w] = img_anchor[h, w]\n", + " return img_stitched\n", + " else:\n", + " return img_wrapped" + ] + }, + { + "cell_type": "code", + "execution_count": 86, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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sd5/q998oHiii39zcnBP9HPcc6eExjdVlbCkojMFMvdy3+8ReBVophBAIcRJc0lojLQsz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0o/FwlyqIxNj9aUIsS4yxt5ShIIVIERMN8wTGKZfL0pnKNFA0layeHZf8BlEYoVrSycz3QwzT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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 86, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "H_trans, (x_min, x_max, y_min, y_max) = get_translation(im1, im2, H)\n", + "img = stitching(im1, im2, H, H_trans, x_max, y_max)\n", + "plt.imshow(img)\n", + "plt.show()\n", + "\n", + "img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)\n", + "cv2.imwrite(\"0_270_blended.jpg\", img)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Part II: Panorama using five key frames\n", + "\n", + "In this part you will produce a panorama using five key frames. Let's determine frames [90, 270, 450, 630, 810] as key frames. The goal is to map all the five frames onto the plane corresponding to frame 450 (that we also call the _reference frame_). For the frames 270 and 630 you can follow the instructions in part 1.\n", + "\n", + "\"Drawing\"\n", + "\n", + "Mapping frame 90 to frame 450 is difficult because they share very little area. Therefore you need to perform a two stage mapping by using frame 270 as a guide. Compute one projection from 90 to 270 and one from 270 to 450 and multiply the two matrices. This produces a projection from 90 to 450 even though these frames have very little area in common\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 87, + "metadata": {}, + "outputs": [], + "source": [ + "import cv2\n", + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": 88, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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WJUhksoaKJ0tkYqgVysiGxlse+XFOn7vIj771TdyYf4ytDYv3/90P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\nvby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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 88, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "master_frames =[90, 270, 450, 630, 810]\n", + "reference_frame = 450\n", + "reference_idx = master_frames.index(reference_frame)\n", + "\n", + "im_paths = ['./images/input/frames/f0090.jpg',\n", + " './images/input/frames/f0270.jpg',\n", + " './images/input/frames/f0450.jpg',\n", + " './images/input/frames/f0630.jpg',\n", + " './images/input/frames/f0810.jpg']\n", + "\n", + "imgs = [cv2.cvtColor(cv2.imread(p), cv2.COLOR_BGR2RGB) for p in im_paths]\n", + "im_height, im_width, _ = imgs[0].shape\n", + "\n", + "H_90_270 = auto_homography(imgs[0], imgs[1], homography_func=computeHomography)\n", + "H_270_450 = auto_homography(imgs[1], imgs[2], homography_func=computeHomography)\n", + "H_630_450 = auto_homography(imgs[3], imgs[2], homography_func=computeHomography)\n", + "H_810_630 = auto_homography(imgs[4], imgs[3], homography_func=computeHomography)\n", + "H_90_450 = np.dot(H_90_270, H_270_450)\n", + "H_810_450 = np.dot(H_630_450, H_810_630)\n", + "\n", + "H_trans_90_450, coords_90_450 = get_translation(imgs[0], imgs[2], H_90_450)\n", + "H_trans_270_450, coords_270_450 = get_translation(imgs[1], imgs[2], H_270_450)\n", + "H_trans_810_450, coords_810_450 = get_translation(imgs[4], imgs[2], H_810_450)\n", + "\n", + "width = int(coords_810_450[1] - coords_90_450[0])\n", + "height = int(coords_810_450[3] - coords_90_450[2])\n", + "\n", + "I_90_450 = stitching(imgs[0], imgs[2], H_90_450, H_trans_90_450, width, height, stitch=False)\n", + "I_270_450 = stitching(imgs[1], imgs[2], H_270_450, H_trans_90_450, width, height)\n", + "I_630_450 = stitching(imgs[3], imgs[2], H_630_450, H_trans_90_450, width, height, stitch=False)\n", + "I_810_450 = stitching(imgs[4], imgs[2], H_810_450, H_trans_90_450, width, height, stitch=False)\n", + "\n", + "img = I_90_450\n", + "for im in [I_270_450, I_630_450, I_810_450]:\n", + " filled = np.sum(img, axis=-1) > 0\n", + " for h in range(img.shape[0]):\n", + " for w in range(img.shape[1]):\n", + " if not filled[h, w]:\n", + " img[h, w] = im[h, w]\n", + " \n", + "plt.imshow(img)\n", + "plt.show()\n", + "cv2.imwrite(\"panorama.jpg\", cv2.cvtColor(img, cv2.COLOR_RGB2BGR))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Part 3: Map the video to the reference plane" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import cv2\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from math import floor\n", + "\n", + "import utils" + ] + }, + { + "cell_type": "code", + "execution_count": 426, + "metadata": {}, + "outputs": [], + "source": [ + "dir_frames = 'images/input/frames'\n", + "filesinfo = os.scandir(dir_frames)" + ] + }, + { + "cell_type": "code", + "execution_count": 427, + "metadata": {}, + "outputs": [], + "source": [ + "filenames = [f.path for f in filesinfo if f.name.endswith(\".jpg\")]\n", + "filenames.sort(key=lambda f: int(''.join(filter(str.isdigit, f))))" + ] + }, + { + "cell_type": "code", + "execution_count": 428, + "metadata": {}, + "outputs": [], + "source": [ + "frameCount = len(filenames)\n", + "frameHeight, frameWidth, frameChannels = cv2.imread(filenames[0]).shape\n", + "frames = np.zeros((frameCount, frameHeight, frameWidth, frameChannels),dtype=np.float32)" + ] + }, + { + "cell_type": "code", + "execution_count": 429, + "metadata": {}, + "outputs": [], + "source": [ + "for idx, file_i in enumerate(filenames):\n", + " frames[idx] = cv2.cvtColor(cv2.imread(file_i), cv2.COLOR_BGR2RGB) / 255.0" + ] + }, + { + "cell_type": "code", + "execution_count": 322, + "metadata": {}, + "outputs": [], + "source": [ + "## Example usage of utils.projectImage\n", + "\n", + "pastHomographies = np.zeros((len(filenames),len(filenames), 3, 3),dtype=np.float32)\n", + "originTranslations = np.zeros((len(filenames), 2), dtype=np.float32)\n", + "sourceFrameIndex = 630\n", + "referenceFrameIndex = 450" + ] + }, + { + "cell_type": "code", + "execution_count": 325, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Overlap:110924\n", + "Error:0.0003923808090779779\n" + ] + } + ], + "source": [ + "projectedSource, _, originTranslations = utils.projectImage(frames, sourceFrameIndex, referenceFrameIndex,\n", + " pastHomographies, originTranslations,\n", + " auto_H_func=auto_homography, homography_func=computeHomography)" + ] + }, + { + "cell_type": "code", + "execution_count": 326, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Overlap:169855\n", + "Error:0.0\n" + ] + } + ], + "source": [ + "projectedReference, _, originTranslations = utils.projectImage(frames, referenceFrameIndex, referenceFrameIndex,\n", + " pastHomographies, originTranslations,\n", + " auto_H_func=auto_homography, homography_func=computeHomography)" + ] + }, + { + "cell_type": "code", + "execution_count": 327, + "metadata": {}, + "outputs": [], + "source": [ + "blendedOutput = utils.blendImages(projectedSource, projectedReference)" + ] + }, + { + "cell_type": "code", + "execution_count": 328, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 328, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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v1wmHw9jtdnq7WrA4JZ47fJayEWhpQzRVyGQyVCS4pAi8ktUbjlQMdioGO5OG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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.imshow(blendedOutput)" + ] + }, + { + "cell_type": "code", + "execution_count": 447, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Done with image idx 899\r" + ] + } + ], + "source": [ + "ref_frame = frames[450-1]\n", + "frame_no = np.array([90, 270, 450, 630, 810])\n", + "H_to_450 = [H_90_450, H_270_450, np.eye(3), H_630_450, H_810_450]\n", + "\n", + "# saved_H = np.zeros((len(frames), 3, 3))\n", + "saved_H = np.load(\"H.npy\")\n", + "\n", + "H_trans_1st = None\n", + "for idx, frame in enumerate(frames):\n", + " \n", + " closest = np.argmin(np.abs(frame_no - idx - 1))\n", + " f_no = frame_no[closest]\n", + " \n", + " inter_ref = frames[f_no - 1]\n", + " H_inter = auto_homography(frame, inter_ref, homography_func=computeHomography)\n", + " H_450 = np.dot(H_inter, H_to_450[closest])\n", + " \n", + " H_trans_450, coords_450 = get_translation(frame, ref_frame, H_450)\n", + " \n", + " if H_trans_1st is None:\n", + " H_trans_1st = H_trans_450\n", + " \n", + " saved_H[idx] = np.dot(H_trans_1st, H_450)\n", + " \n", + " I = stitching(frame, ref_frame, H_450, H_trans_1st, width, height, stitch=False)\n", + " I = cv2.cvtColor(I, cv2.COLOR_RGB2BGR)\n", + " \n", + " cv2.imwrite('aligned_frames/a{:04d}.jpg'.format(idx+1), (I*255).astype(np.uint8))\n", + " print(f'Done with image idx {idx}', end='\\r')" + ] + }, + { + "cell_type": "code", + "execution_count": 448, + "metadata": {}, + "outputs": [], + "source": [ + "np.save(\"H.npy\", saved_H)" + ] + }, + { + "cell_type": "code", + "execution_count": 452, + "metadata": {}, + "outputs": [], + "source": [ + "for p in os.listdir(\"aligned_frames\"):\n", + " p = os.path.join(\"aligned_frames\", p)\n", + " img = cv2.imread(p)\n", + " img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\n", + " \n", + " cv2.imwrite(p, img)" + ] + }, + { + "cell_type": "code", + "execution_count": 464, + "metadata": {}, + "outputs": [], + "source": [ + "utils.imageFolder2mpeg('aligned_frames', fps=30)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Part 4: Create background panorama\n", + "\n", + "In this part you will remove moving objects from the video and create a background panorama that should incorporate pixels from all the frames.\n", + "\n", + "In the video you produced in __part 3__ each pixel appears in several frames. You need to estimate which of the many colors correspond to the background. We take advantage of the fact that the background color is fixed while the foreground color changes frequently (because foreground moves).\n", + "\n", + "\"Drawing\"\n", + "\n", + "\n", + "For each pixel in the sequence of __part 3__, determine all valid colors (colors that come from all frames that overlap that pixel). You can experiment with different methods for determining the background color of each pixel, as discussed in class. Perform the same procedure for all pixels and generate output. The output should be a completed panorama showing only pixels of background or non-moving objects." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import cv2\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Processing aligned_frames/a0900.jpg...\r" + ] + } + ], + "source": [ + "import time\n", + "\n", + "dir_frames = 'aligned_frames'\n", + "pano_filesinfo = os.scandir(dir_frames)\n", + "pano_filenames = [f.path for f in pano_filesinfo if f.name.endswith(\".jpg\")]\n", + "pano_filenames.sort(key=lambda f: int(''.join(filter(str.isdigit, f))))\n", + "\n", + "img = cv2.cvtColor(cv2.imread(pano_filenames[0]), cv2.COLOR_BGR2RGB)\n", + "pano_height, pano_width, _ = img.shape\n", + "\n", + "# # Mean pixel value\n", + "# px_sum = np.zeros_like(img, dtype=np.float64)\n", + "# mask_sum = np.zeros((height, width), dtype=np.float32)\n", + "\n", + "# for file_i in pano_filenames:\n", + "# print(f'Processing {file_i}...', end='\\r')\n", + "# img = cv2.cvtColor(cv2.imread(file_i), cv2.COLOR_BGR2RGB)\n", + "# mask = np.sum(img, axis=-1) > 0\n", + "# mask_sum += mask\n", + "# px_sum += img\n", + " \n", + "# mask_sum = np.repeat(mask_sum[:, :, np.newaxis], 3, axis=-1)\n", + "# px_sum /= mask_sum\n", + "# plt.imshow(px_sum.astype(np.uint8))\n", + "# plt.show()\n", + "\n", + "# Median\n", + "pixels = {}\n", + "masks = np.zeros((len(pano_filenames), pano_height, pano_width), dtype=np.bool)\n", + "for idx, file_i in enumerate(pano_filenames):\n", + " start = time.time()\n", + " \n", + " print(f'Processing {file_i}...', end='\\r')\n", + " img = cv2.imread(file_i)\n", + " masks[idx] = np.sum(img, axis=-1) > 0\n", + " \n", + " h_ind, w_ind = np.where(masks[idx] == 1)\n", + " for h, w in zip(h_ind, w_ind):\n", + " if pixels.get((h, w), None) is None:\n", + " pixels[(h, w)] = []\n", + " pixels[(h, w)].append(img[h, w])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "bg = np.zeros((pano_height, pano_width, 3), dtype=np.uint8) \n", + "for key, val_list in pixels.items():\n", + " h, w = key\n", + " bg[h, w] = np.median(val_list, axis=0)\n", + " \n", + "plt.imshow(cv2.cvtColor(bg, cv2.COLOR_BGR2RGB))\n", + "plt.show()\n", + "cv2.imwrite(\"bg_median.jpg\", bg)" + ] + }, + { + "cell_type": "code", + "execution_count": 90, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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U5nV33QW+YDwIr09KB+BXf/VX+eQnP8m//tf/Fx/65V/C98KBM+h7iStCvYbX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\nmcpUniAyNfhTmcpUpvIEkf8PcoIY2KteQqQAAAAASUVORK5CYII=\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "img = cv2.imread(\"bg_median.jpg\")\n", + "img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\n", + "plt.imshow(img)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Part 5: Create background movie\n", + "\n", + "Map the background panorama to the movie coordinates. For each frame of the movie, say frame 1, you need to estimate a projection from the panorama to frame 1. Note, you should be able to re-use the homographies that you estimated in __Part 3__. Perform this for all frames and generate a movie that looks like the input movie but shows only background pixels. All moving objects that belong to the foreground must be removed." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import cv2\n", + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [], + "source": [ + "pano = cv2.imread(\"bg_median.jpg\")\n", + "\n", + "os.makedirs(\"background_frames\", exist_ok=True)\n", + "H_saved = np.load(\"H.npy\")\n", + "for idx, H in enumerate(H_saved):\n", + " inv_H = inv(H)\n", + " inv_img = cv2.warpPerspective(pano, inv_H, (im_width, im_height))\n", + " cv2.imwrite('background_frames/a{:04d}.jpg'.format(idx+1), inv_img)" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [], + "source": [ + "utils.imageFolder2mpeg('background_frames', fps=30)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Part 6: Create foreground movie\n", + "\n", + "In the background video, moving objects are removed. In each frame, those pixels that are different enough than the background color are considered foreground. For each frame determine foreground pixels and generate a movie that only includes foreground pixels." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import cv2\n", + "import numpy as np\n", + "from scipy.ndimage.filters import convolve" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Processing a0900.jpg...\r" + ] + } + ], + "source": [ + "dir_background = 'background_frames'\n", + "dir_original = 'images/input/frames'\n", + "\n", + "ksize = 5\n", + "threshold = 75\n", + "for idx, p in enumerate(sorted(os.listdir(dir_background))):\n", + " print(f'Processing {p}...', end='\\r')\n", + " \n", + " num = ''.join(filter(str.isdigit, p))\n", + " bg_frame_p = os.path.join(dir_background, p)\n", + " ori_frame_p = os.path.join(dir_original, f'f{num}.jpg')\n", + " \n", + " bg_frame = cv2.cvtColor(cv2.imread(bg_frame_p), cv2.COLOR_BGR2RGB).astype(np.float32)\n", + " ori_frame = cv2.cvtColor(cv2.imread(ori_frame_p), cv2.COLOR_BGR2RGB).astype(np.float32)\n", + "\n", + " diff = np.sqrt(np.sum(np.power(bg_frame - ori_frame, 2), axis=-1))\n", + " mask = diff > threshold\n", + " mask = convolve(mask.astype(np.float32), np.ones((ksize,ksize))/(ksize*ksize))\n", + " mask = np.repeat(mask[:, :, np.newaxis], 3, axis=-1)\n", + " \n", + " fg_frame = np.array(ori_frame) * mask \n", + " fg_frame = cv2.cvtColor(fg_frame, cv2.COLOR_RGB2BGR)\n", + " cv2.imwrite('foreground_frames/a{:04d}.jpg'.format(idx+1), fg_frame)" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "metadata": {}, + "outputs": [], + "source": [ + "utils.imageFolder2mpeg('foreground_frames', fps=30)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Bells and whistles" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.4" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/proj5-video_stitching/images/input/.DS_Store b/proj5-video_stitching/images/input/.DS_Store new file mode 100644 index 0000000..c7ab75c Binary files /dev/null and b/proj5-video_stitching/images/input/.DS_Store differ diff --git a/proj5-video_stitching/images/input/frames/f0001.jpg b/proj5-video_stitching/images/input/frames/f0001.jpg new file mode 100755 index 0000000..691eb4f Binary files /dev/null and b/proj5-video_stitching/images/input/frames/f0001.jpg differ diff --git a/proj5-video_stitching/images/input/frames/f0002.jpg 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/dev/null and b/proj5-video_stitching/images/project_5/rectangle.png differ diff --git a/proj5-video_stitching/requirements.txt b/proj5-video_stitching/requirements.txt new file mode 100755 index 0000000..56d5d34 --- /dev/null +++ b/proj5-video_stitching/requirements.txt @@ -0,0 +1,4 @@ +matplotlib==3.1.1 +numpy==1.17.3 +opencv-contrib-python==3.4.2.16 +opencv-python==3.4.2.16 \ No newline at end of file diff --git a/proj5-video_stitching/utils.py b/proj5-video_stitching/utils.py new file mode 100755 index 0000000..f7da76d --- /dev/null +++ b/proj5-video_stitching/utils.py @@ -0,0 +1,310 @@ +import os +import cv2 + +import numpy as np +from math import floor +from numpy.linalg import svd, inv + + +def projectImage(frames, sourceFrameIndex, referenceFrameIndex, + pastHomographies, originTranslations, xrange=1632, + yrange=512, overlapThreshold=40000, errorThreshold=4e-4, + numKeyframes=3, checkAllKeyframes=0, auto_H_func=None, + homography_func=None, normalization_func=None): + ''' + Input: + - frames: 4D array of frames + - sourceFrameIndex: index of the frame to be projected + - referenceFrameIndex: index of the frame to be projected to + - pastHomographies: 2D cell array caching previously computed + homographies from every frame to every other frame + - xrange, yrange: dimensions of the output image + - overlapThreshold: sufficient number of pixels overlapping between + projected source and reference frames to ensure good homography + - errorThreshold: acceptable error for good homography + - numKeyframes: number of equidistant keyframes between source and + reference frame to be visited in search of better homography + - checkAllKeyframes: 0 if algorithms breaks after first better + homography is found, 1 if all keyframes are to be visited + + Output: + - bestProjectedImage: source frame optimally projected onto reference + frame using reestimation of homography based on closest-frame search + and using closest-frame homography as + ''' + numFrames = frames.shape[0] + + _, referenceTransform, ref_origin_coord = transformImage(frames, referenceFrameIndex, referenceFrameIndex, pastHomographies, xrange, yrange, auto_H_func, homography_func, normalization_func) + _, sourceTransform, src_origin_coord = transformImage(frames, sourceFrameIndex, referenceFrameIndex, pastHomographies, xrange, yrange, auto_H_func, homography_func, normalization_func) + _, err = computeOverlap(sourceTransform, src_origin_coord, referenceTransform, ref_origin_coord, overlapThreshold) + originTranslations[sourceFrameIndex] = src_origin_coord + + x_min, y_min = originTranslations[0] + # Translation matrix + t = [-x_min, -y_min] + H_t = np.array([[1, 0, t[0]], [0, 1, t[1]], [0, 0, 1]], dtype=np.float32) + + # Dot product of translation matrix and homography + pastHomographies[sourceFrameIndex, referenceFrameIndex] = H_t.dot(pastHomographies[sourceFrameIndex, referenceFrameIndex]) + + projectedImage = cv2.warpPerspective((frames[sourceFrameIndex]*255).astype(np.uint8), + pastHomographies[sourceFrameIndex, referenceFrameIndex], + (xrange, yrange)) + + if err > errorThreshold: + print('Finding better homography...') + increment = floor(((referenceFrameIndex - sourceFrameIndex) - 1) / (numKeyframes + 1)) + keyframeIndex = sourceFrameIndex + increment # frame being used to find better homography from source to reference + found = 0 + counter = 0 + bestHomography = np.eye(3) # initialize H as identity + + while counter < numKeyframes and keyframeIndex < numFrames and keyframeIndex > 0: + + # compute homography and projected image from keyframe to + # reference frame + H2, keyframeTransform, keyframe_origin_coord = transformImage(frames, keyframeIndex, referenceFrameIndex, pastHomographies, xrange, yrange, auto_H_func, homography_func, normalization_func) + a, error1 = computeOverlap(keyframeTransform, keyframe_origin_coord, referenceTransform, ref_origin_coord, overlapThreshold) + + # compute homography and projected image from source frame to + # keyframe (new reference = keyframe) + _, keyframeToKeyframeTransform, keyframeToKeyframe_origin_coord = transformImage(frames, keyframeIndex, keyframeIndex, pastHomographies, xrange, yrange, auto_H_func, homography_func, normalization_func) + H1, sourceToKeyframeTransform, srcToKeyframe_origin_coord = transformImage(frames, sourceFrameIndex, keyframeIndex, pastHomographies, xrange, yrange, auto_H_func, homography_func, normalization_func) + b, error2 = computeOverlap(sourceToKeyframeTransform, srcToKeyframe_origin_coord, keyframeToKeyframeTransform, keyframeToKeyframe_origin_coord, overlapThreshold) + + sufficientOverlap = (a and b) + + if (sufficientOverlap and max(error1, error2) < err): + found = 1 + bestHomography = np.dot(H1, H2) + src_origin_coord = keyframe_origin_coord + srcToKeyframe_origin_coord + if not checkAllKeyframes: + break + + keyframeIndex = keyframeIndex + increment + counter = counter + 1 + + if found: + print('Found better homography') + pastHomographies[sourceFrameIndex, referenceFrameIndex] = bestHomography + originTranslations[sourceFrameIndex] = src_origin_coord + min_origin_coord = np.amin(originTranslations, axis=0) + + x_min, y_min = originTranslations[0] + # Translation matrix + t = [-x_min, -y_min] + H_t = np.array([[1, 0, t[0]], [0, 1, t[1]], [0, 0, 1]], dtype=np.float32) + + # Dot product of translation matrix and homography + T = H_t.dot(bestHomography) + + projectedImage = cv2.warpPerspective((frames[sourceFrameIndex]*255).astype(np.uint8), T, (xrange, yrange)) + + pastHomographies[sourceFrameIndex, referenceFrameIndex] = T.astype(np.float32) + + return projectedImage, pastHomographies, originTranslations + + +def computeOverlap(sourceTransform, src_origin_coord, referenceTransform, + ref_origin_coord, overlapThreshold): + ''' + Input: + - sourceTransform: source frame projected onto reference frame plane + - referenceTransform: reference frame projected onto same space + - overlapThreshold: sufficient number of pixels overlapping between + projected source and reference frames to ensure good homography + + Output: + - sufficientOverlap: boolean indicating whether sufficient overlap is + found between projected source and reference frame + - error: raw pixel intensity error between projected source + and reference frames in the overlapping region + ''' + + img_origins = np.stack((ref_origin_coord, src_origin_coord)) + [x_min, y_min] = np.ceil(img_origins.min(axis=0)).astype(int) + + # Translation matrix + t = [-x_min, -y_min] + H_t = np.array([[1, 0, t[0]], [0, 1, t[1]], [0, 0, 1]], dtype=np.float32) + + canvas_dim = (sourceTransform.shape[1], sourceTransform.shape[0]) + referenceTransform = cv2.warpPerspective(referenceTransform, H_t, canvas_dim) + + referenceTransform = (referenceTransform / 255.0).astype(np.float32) + sourceTransform = (sourceTransform / 255.0).astype(np.float32) + + nnzReference = referenceTransform != 0 + nnzSource = sourceTransform != 0 + nnzCommon = nnzReference * nnzSource + + if not np.sum(nnzCommon): + error = np.finfo(np.float32).max + else: + error = np.sqrt(np.sum((sourceTransform[nnzCommon] - referenceTransform[nnzCommon])**2)) / np.sum(nnzCommon) + + print('Overlap:{}'.format(np.sum(np.prod(nnzCommon, axis=-1)))) + print('Error:{}'.format(error)) + + sufficientOverlap = np.sum(np.prod(nnzCommon, axis=-1)) > overlapThreshold + + return sufficientOverlap, error + + +def transformImage(frames, sourceFrameIndex, referenceFrameIndex, + pastHomographies, xrange, yrange, auto_H_func, + homography_func, normalization_func): + ''' + Input: + - frames: 4D array of frames + - sourceFrameIndex: index of the frame to be projected + - referenceFrameIndex: index of the frame to be projected to + - pastHomographies: 2D cell array caching previously computed + homographies from every frame to every other frame + - xrange, yrange: dimensions of the output image + + Output: + - homography: homography from source frame to reference frame + - imageTransform: projected source frame with dimensions (xrange, yrange) + ''' + + if pastHomographies[sourceFrameIndex, referenceFrameIndex].any(): + homography = pastHomographies[sourceFrameIndex, referenceFrameIndex] + else: + homography = auto_H_func(frames[sourceFrameIndex], frames[referenceFrameIndex], + homography_func, normalization_func) + pastHomographies[sourceFrameIndex, referenceFrameIndex] = homography.astype(np.float32) + + sourceFrame = frames[sourceFrameIndex] + + sourceFrame_corners = get_img_corners(sourceFrame) + sourceFrame_corners_tranform_corners = cv2.perspectiveTransform(sourceFrame_corners, homography) + canvas_corners = np.array([[0., 0.], [xrange, 0.], [yrange, xrange], [0., yrange]]) + + corners = np.concatenate((np.squeeze(sourceFrame_corners_tranform_corners, axis=1), canvas_corners)) + [x_min, y_min] = np.ceil(corners.min(axis=0)).astype(int) + [x_max, y_max] = np.ceil(corners.max(axis=0)).astype(int) + + # Translation matrix + t = [-x_min, -y_min] + H_t = np.array([[1, 0, t[0]], [0, 1, t[1]], [0, 0, 1]], dtype=np.float32) + + # Dot product of translation matrix and homography + T = H_t.dot(homography) + + projectedImage = cv2.warpPerspective((sourceFrame*255).astype(np.uint8), T, (xrange, yrange)) + + return homography, projectedImage, np.array([x_min, y_min]) + + +def blendImages(sourceTransform, referenceTransform): + ''' + Input: + - sourceTransform: source frame projected onto reference frame plane + - referenceTransform: reference frame projected onto same space + + Output: + - blendedOutput: naive blending result from frame stitching + ''' + + blendedOutput = referenceTransform + indices = referenceTransform == 0 + blendedOutput[indices] = sourceTransform[indices] + + return (blendedOutput / blendedOutput.max() * 255).astype(np.uint8) + + +def get_img_corners(img): + ''' + Returns the position of the corners of an color image + Input: + img: color image. + Output: + corners: image corners (np.array) + ''' + corners = np.zeros((4, 1, 2), dtype=np.float32) + + height, width, channels = img.shape + corners[0] = (0, 0) #top left + corners[1] = (width, 0) #top right + corners[2] = (width, height) #bottom right + corners[3] = (0, height) #bottom left + + return corners + + +def video2imageFolder(input_file, output_path): + ''' + Extracts the frames from an input video file + and saves them as separate frames in an output directory. + Input: + input_file: Input video file. + output_path: Output directorys. + Output: + None + ''' + + cap = cv2.VideoCapture() + cap.open(input_file) + + if not cap.isOpened(): + print("Failed to open input video") + + frame_count = cap.get(cv2.CAP_PROP_FRAME_COUNT) + + frame_idx = 0 + + while frame_idx < frame_count: + ret, frame = cap.read() + + if not ret: + print ("Failed to get the frame {}".format(frameId)) + continue + + out_name = os.path.join(output_path, 'f{:04d}.jpg'.format(frame_idx+1)) + ret = cv2.imwrite(out_name, frame) + if not ret: + print ("Failed to write the frame {}".format(frame_idx)) + continue + + frame_idx += 1 + cap.set(cv2.CAP_PROP_POS_FRAMES, frame_idx) + + +def imageFolder2mpeg(input_path, output_path='./output_video.mpeg', fps=30.0): + ''' + Extracts the frames from an input video file + and saves them as separate frames in an output directory. + Input: + input_path: Input video file. + output_path: Output directorys. + fps: frames per second (default: 30). + Output: + None + ''' + + dir_frames = input_path + files_info = os.scandir(dir_frames) + + file_names = [f.path for f in files_info if f.name.endswith(".jpg")] + file_names.sort(key=lambda f: int(''.join(filter(str.isdigit, f)))) + + frame_Height, frame_Width = cv2.imread(file_names[0]).shape[:2] + resolution = (frame_Width, frame_Height) + + # Define the codec and create VideoWriter object + fourcc = cv2.VideoWriter_fourcc(*'MPG1') + video_writer = cv2.VideoWriter(output_path, fourcc, fps, resolution) + + frame_count = len(file_names) + + frame_idx = 0 + + while frame_idx < frame_count: + + + frame_i = cv2.imread(file_names[frame_idx]) + video_writer.write(frame_i) + frame_idx += 1 + + video_writer.release() \ No newline at end of file