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Tracking via Colorization Tensorflow implementatin of Tracking Emerges by Colorizing Videos

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Tracking via Colorization

KakaoBrain tensorflow CodeFactor CircleCI

  • colorization sample tracking via colorization sample2

  • tracking segmentation sample tracking via colorization sample0 tracking via colorization sample1

Introduction

This TensorFlow implementation is designed with these goals:

How to Use

Clustering

python3 bin/clustering.py -k 16 -n 10000 -o datas/centroids/centroids_16k_cifar10_10000samples.npy

Train

  • colorizer
python3 bin/train_colorizer.py --model-dir models/colorizer
tensorboard --host 0.0.0.0 --port 6006 --logdir models
  • cifar10
python3 bin/train_estimator_cifar10.py --model-dir models/test

Predict

  • colorizer
python3 bin/test_colorizer.py --checkpoint models/test/model.ckpt-100000 --scale 1 --name davis -o results/davis/

Prerequisite

Should install below libraries.

  • Tensorflow >= 1.10
  • opencv >= 3.0

And install below dependencies.

apt install -y libsm6 libxext-dev libxrender-dev libcap-dev
apt install -y ffmpeg
pip install -r requirements.txt

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Tracking via Colorization Tensorflow implementatin of Tracking Emerges by Colorizing Videos

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