- ๐ท๏ธ Added Label for Every Track
- โก Runs on both CPU & GPU
- ๐ฅ Supports Video, Webcam, External Camera, and IP Stream
- ๐ ๏ธ Development of a Streamlit Dashboard for Object Tracking
Ready-to-Use Google Colab ๐ Launch Colab
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Clone the repository:
git clone https://github.com/RizwanMunawar/yolov7-object-tracking.git
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Navigate to the cloned folder:
cd yolov7-object-tracking
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Create a virtual environment (Recommended to avoid conflicts):
conda create -n yolov7objtracking python=3.10 conda activate yolov7objtracking
python3 -m venv yolov7objtracking source yolov7objtracking/bin/activate
python3 -m venv yolov7objtracking cd yolov7objtracking/Scripts activate
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Update pip and install dependencies:
pip install --upgrade pip pip install -r requirements.txt
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Run the script:
Select the appropriate command based on your requirements. Pretrained yolov7 weights will be downloaded automatically if needed.
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Detection only:
python detect.py --weights yolov7.pt --source "your video.mp4"
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Object tracking:
python detect_and_track.py --weights yolov7.pt --source "your video.mp4"
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Webcam:
python detect_and_track.py --weights yolov7.pt --source 0
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External Camera:
python detect_and_track.py --weights yolov7.pt --source 1
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IP Camera Stream:
python detect_and_track.py --source "your IP Camera Stream URL" --device 0
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Specific class tracking (e.g., person):
python detect_and_track.py --weights yolov7.pt --source "your video.mp4" --classes 0
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Colored tracks:
python detect_and_track.py --weights yolov7.pt --source "your video.mp4" --colored-trk
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Save track centroids, IDs, and bounding box coordinates:
python detect_and_track.py --weights yolov7.pt --source "your video.mp4" --save-txt --save-bbox-dim
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Output files will be saved in
working-dir/runs/detect/obj-tracking
with the original filename.
YOLOv7 Detection Only | YOLOv7 Object Tracking with ID | YOLOv7 Object Tracking with ID and Label |
Some of my articles/research papers | computer vision awesome resources for learning | How do I appear to the world? ๐
Ultralytics YOLO11: Object Detection and Instance Segmentation๐คฏ
Parking Management using Ultralytics YOLO11
My ๐๏ธComputer Vision Hobby Projects that Yielded Earnings
Best Resources to Learn Computer Vision
Roadmap for Computer Vision Engineer
How did I spend 2022 in the Computer Vision Field
Domain Feature Mapping with YOLOv7 for Automated Edge-Based Pallet Racking Inspections
Exudate Regeneration for Automated Exudate Detection in Retinal Fundus Images
Feature Mapping for Rice Leaf Defect Detection Based on a Custom Convolutional Architecture
Yolov5, Yolo-x, Yolo-r, Yolov7 Performance Comparison: A Survey
Explainable AI in Drug Sensitivity Prediction on Cancer Cell Lines