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@@ -5,16 +5,6 @@ object detection using deep learning and multi-object tracking
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![Output Sample][output_video]
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The work here is based on the following literature available:
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1. http://elvera.nue.tu-berlin.de/files/1517Bochinski2017.pdf
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2. Pyimagesearch [1](https://www.pyimagesearch.com/2018/07/23/simple-object-tracking-with-opencv/), [2](https://www.pyimagesearch.com/2018/11/12/yolo-object-detection-with-opencv/)
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3. [correlationTracker](https://github.com/Wenuka/correlationTracker)
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4. [Caffemodel zoo](http://caffe.berkeleyvision.org/model_zoo.html)
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5. [Caffemodel zoo GitHub](https://github.com/BVLC/caffe/tree/master/models)
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6. [YOLO v3](https://pjreddie.com/media/files/papers/YOLOv3.pdf)
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Use the caffemodel zoo from the reference [4,5] mentioned above to vary the CNN models and Play around with the codes.
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### Install OpenCV
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Pip install for OpenCV (version 3.4.3 or later) is available [here](https://pypi.org/project/opencv-python/) and can be done with the following command:
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- The model for use is provided in the folder named `caffemodel_dir`.
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- The video input can be specified in the cell named `Initiate opencv video capture object` in the notebook.
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- To make the source as the webcam, use `video_src=0` else provide the path of the video file (example: `video_src="/path/of/videofile.mp4"`).
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### References
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The work here is based on the following literature available:
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1. http://elvera.nue.tu-berlin.de/files/1517Bochinski2017.pdf
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2. Pyimagesearch [1](https://www.pyimagesearch.com/2018/07/23/simple-object-tracking-with-opencv/), [2](https://www.pyimagesearch.com/2018/11/12/yolo-object-detection-with-opencv/)
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3. [correlationTracker](https://github.com/Wenuka/correlationTracker)
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4. [Caffemodel zoo](http://caffe.berkeleyvision.org/model_zoo.html)
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5. [Caffemodel zoo GitHub](https://github.com/BVLC/caffe/tree/master/models)
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6. [YOLO v3](https://pjreddie.com/media/files/papers/YOLOv3.pdf)
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Use the caffemodel zoo from the reference [4,5] mentioned above to vary the CNN models and Play around with the codes.

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