readme

README.md

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+# Visual Debugger for Image Processing
+
+The Visual Debugger module provides tools for visually debugging image processing workflows, allowing annotations like points, labels, rectangles, and more on images. It supports a variety of annotation types and includes functionality for merging multiple images into a composite image for comprehensive review.
+
+## Features
+
+- **Multiple Annotation Types**: Support for a variety of annotations such as points, labeled points, rectangles, circles, and orientation vectors based on pitch, yaw, and roll.
+- **Image Concatenation**: Capability to concatenate multiple debugged images into a single composite image, facilitating easier visualization of sequential image processing steps.
+- **Dynamic Image Handling**: Handles a wide range of image inputs including file paths, in-memory image arrays, base64 encoded images, and images from web links, integrating seamlessly with OpenCV.
+- **Customizable Debugging**: Debugging can be turned on or off, and the module supports generating merged debug images for a sequence of operations.
+- **Orientation Drawing**: Special functionality for visualizing orientation in 3D space, projecting pitch, yaw, and roll onto a 2D image plane.
+ **Automatic Naming**: Automatically handles the naming of output images based on a customizable tag, the sequence number of the operation, and specific conditions of the debugging process. This ensures a clear and organized structure for saved images, making it easy to track and review the progress of image processing.
+## Installation
+
+To use this module in your projects, install the pypi package by:
+
+```bash
+pip install visual_debugger
+```
+
+
+## Usage
+
+Here is a basic example of how to use the VisualDebugger class within your image processing workflow:
+
+```python
+from visual_debugger import VisualDebugger, Annotation, AnnotationType
+
+# Initialize the debugger
+
+vd = VisualDebugger(tag="Example", debug_folder_path="./visualdebug",  active=True)
+
+# Load your image (this should be replaced with your actual image path or np.array image)
+image_path = "path/to/your/image.jpg"
+
+# Create annotations you want to show on the image
+annotations = [
+    Annotation(type=AnnotationType.RECTANGLE, coordinates=(10, 10, 50, 50)),
+    Annotation(type=AnnotationType.POINT_AND_LABEL, coordinates=(100, 100), labels="Center Point")
+]
+
+# Process and debug the image.
+# This will use "tag" and "process_step" variables to create a file name 
+# And save the image into "debug_folder_path" 
+vd.visual_debug(image_path, annotations=annotations, process_step="initial_check")
+
+# Generate a merged image of all processed steps
+vd.cook_merged_img()
+```
+
+## Documentation
+
+For more details on the methods and their parameters, please refer to the inline documentation within the module files.
+
+## Contributing
+
+Contributions to enhance the functionality or improve the documentation are welcome. Please follow the standard GitHub pull request process to submit your contributions.
+
+## License
+
+Specify your licensing here, for example, MIT, GPL, etc.
+
+---