tensorflow-siamese-fc

A Python+Tensorflow implementation of siamese-fc

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This is the Python+Tensorflow implementation of Fully-Convolutional Siamese Networks for Object Tracking, including both training and tracking.

The original Matlab version can be found at siamese-fc.

The tracker borrows a lot of code from py-siamese_fc, many thanks.

ref: Fully-Convolutional Siamese Networks for Object Tracking

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Prerequisites:

python: 3.4; tensorflow: 1.0.1

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1. [ Tracking only ] For tracking, pretrained networks as ckpt file can be plugged into the tracker.py directly.

   1. Clone the repository.
   2. A pretrained networks with Imagenet VID dataset can be downloaded from baidu pan, unzip the file to ./models/.
   3. Execute tracker.py, the video sequence (./demo-sequences/vot15_bag) is processed as an example.

2. [ Training ] To train a model, following steps can be considered.

   1. Clone the reposistory.
   2. Follow the instructions from original version to generate the curated dataset for training.
   3. Open the created imageStats.mat with MATLAB, upzip x.mat and z.mat in the path ./ILSVRC15-curation/, run curation.py to get imdb.pkl and imageStats.pkl as python version of imdb_video.mat and imageStats.mat.
   4. Execute train.py to train your own model. Tensorboard can also be used during this phase to monitor variables in the network.
   5. Parameters of networks are saved as ckpt files in ./ckpt for tracking.