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Abrupt-motion-tracking-siameseFC

Dependencies to be installed :

  1. Python – 3.7.3
  2. Tensorflow – 1.13.1
  3. Pillow – 6.1.0
  4. Numpy – 1.18.1
  5. Matplotlib – 3.1.3
  6. Scipy – 1.4.1
  7. H5py – 2.10.0
  8. Hdf5storage – 0.1.15
  9. Hdf5 – 1.10.4
  10. Opencv-python – 4.2.0.32

Repository folders description :

  1. ‘parameters’ : Contains different parameters which can be changed to configure the execution environment
  2. ‘pretrained’ : Contains pretrained cfnet network weights
  3. ‘src’ : Contains list of procedures for the Siamese FC implementation

Running the tracker :

  1. All the initial parameters regarding loading the data, enabling the visualization, loading the pretrained cfnet weights and the hyperparameters have been assigned in the code.
  2. Run the ‘run_tracker_evaluation_meanshift.py’ file to execute the SiameseFC tracker integrated with the Mean Shift filter.
  3. Run the ‘run_tracker_evaluation_lucaskanade.py’ file to execute the SiameseFC tracker integrated with the Lucas Kanade algorithm.

About

The aim of this project is to integrate the SiameseFC tracker with Lucas Kanade and Mean Shift filters to track the objects exhibiting abrupt motion.

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