Video Tracking and Cropping Script

This project is a Python script that uses OpenCV to track a region of interest (ROI) in a video, crop the tracked region frame-by-frame, and save both the cropped images and the annotated video output. It also supports selecting the initial ROI interactively.

Features

• Select and track a region of interest (ROI) in a video.
• Save cropped frames of the tracked ROI as images.
• Save the annotated video with tracking information.
• Real-time display of tracking and FPS information.

Prerequisites

• Python 3.x
• OpenCV (Ensure the opencv-contrib-python package is installed for legacy tracker support)
• A valid video file (mp4 format recommended).

Installation

1. Clone this repository:

   git clone <repository_url>
   cd <repository_name>

2. Install the required dependencies:

   pip install opencv-contrib-python

3. Place the input video file in the vid1 folder. Ensure the file is named avng.mp4 or update the script with your video filename.

Usage

1. Run the script:

   python script.py

2. Select the ROI by dragging a rectangle over the desired region in the displayed frame. Press Enter or Space to confirm your selection.

3. The script will:

   • Track the selected ROI throughout the video.
   • Save cropped frames of the tracked region to the vid2 folder.
   • Save the annotated video output as output.mp4 in the root directory.

4. Press q during playback to exit the tracking loop early.

File Structure

project/
|
|-- script.py        # Main Python script
|-- vid1/            # Input video folder
|   |-- avng.mp4     # Input video file
|
|-- vid2/            # Folder for cropped frames
|
|-- output.mp4       # Annotated output video
|
|-- README.md        # Project documentation

Notes

• Ensure the input video is placed in the correct directory (vid1) before running the script.
• The TrackerMOSSE tracker is used for lightweight tracking. For more robust tracking, consider using other trackers like TrackerCSRT.

Troubleshooting

1. Error: Cannot open video file

   • Ensure the input video file exists and the path is correct.

2. Error: Cannot read video

   • Check the video format and compatibility with OpenCV.

3. Tracking issues

   • If the tracker loses track frequently, try selecting a clearer ROI or use a more robust tracker.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contribution

Contributions, issues, and feature requests are welcome! Feel free to fork the repository and submit pull requests.