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DOWNLOAD_WEIGHTS.md

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## Instructions to download pretrained neural-network weights.
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[Home](https://adipandas.github.io/multi-object-tracker/){: .btn .btn-green }
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[GitHub](https://github.com/adipandas/multi-object-tracker){: .btn .btn-blue}
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##### YOLOv3
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```
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cd ./examples/pretrained_models/yolo_weights

README.md

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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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```
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pip install numpy matplotlib scipy
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pip install opencv-contrib-python
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```
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Installation of `ipyfilechooser` is recommended if you want to use the jupyter notebooks available in the ```examples``` folder.
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```
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pip install ipyfilechooser
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```
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```
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git clone https://github.com/adipandas/multi-object-tracker
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cd multi-object-tracker

REFERENCES.md

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# References and Credits
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[Home](https://adipandas.github.io/multi-object-tracker/){: .btn .btn-green }
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[GitHub](https://github.com/adipandas/multi-object-tracker){: .btn .btn-blue}
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This work is based on the following literature:
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1. Bochinski, E., Eiselein, V., & Sikora, T. (2017, August). High-speed tracking-by-detection without using image information. In 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) (pp. 1-6). IEEE. [[pdf](http://elvera.nue.tu-berlin.de/files/1517Bochinski2017.pdf)]
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4. Kalman Filter. [[wiki](https://en.wikipedia.org/wiki/Kalman_filter)]
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5. TensorFlow Object Detection API [[github](https://github.com/tensorflow/models/tree/master/research/object_detection)]
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6. Caffe [[website](https://caffe.berkeleyvision.org/)][[github](https://github.com/BVLC/caffe)]
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#### Link to `multi-object-tracker` [[webpage](https://adipandas.github.io/multi-object-tracker/)][[GitHub Repo](https://github.com/adipandas/multi-object-tracker)]

examples/readme.md

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# multi-object-tracker examples
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[Home](https://adipandas.github.io/multi-object-tracker/){: .btn .btn-green }
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[GitHub](https://github.com/adipandas/multi-object-tracker){: .btn .btn-blue}
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This folder contains various examples.
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1. [Example jupyter-notebooks](example_notebooks)

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