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README.md

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-license: apache-2.0
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+# RepNet PyTorch
+A PyTorch port with pre-trained weights of **RepNet**, from *Counting Out Time: Class Agnostic Video Repetition Counting in the Wild* (CVPR 2020) [[paper]](https://arxiv.org/abs/2006.15418) [[project]](https://sites.google.com/view/repnet) [[notebook]](https://colab.research.google.com/github/google-research/google-research/blob/master/repnet/repnet_colab.ipynb#scrollTo=FUg2vSYhmsT0).
+
+This repo provides an implementation of RepNet written in PyTorch and a script to convert the pre-trained TensorFlow weights provided by the authors. The outputs of the two implementations are almost identical, with a small deviation (less than $10^{-6}$ at most) probably caused by the [limited precision of floating point operations](https://pytorch.org/docs/stable/notes/numerical_accuracy.html).
+
+<div align="center">
+  <img src="img/example1.gif" height="160" />
+  <img src="img/example2.gif" height="160" />
+  <img src="img/example3.gif" height="160" />
+  <img src="img/example4.gif" height="160" />
+</div>
+
+## Get Started
+- Clone this repo and install dependencies:
+```bash
+git clone https://github.com/materight/RepNet-pytorch
+cd RepNet-pytorch
+pip install -r requirements.txt
+```
+
+- To download the TensorFlow pre-trained weights and convert them to PyTorch, run:
+```bash
+python convert_weights.py
+```
+
+## Run inference
+Simply run:
+```bash
+python run.py
+```
+The script will download a sample video, run inference on it and save the count visualization. You can also specify a video path as argument (either a local path or a YouTube/HTTP URL):
+```bash
+python run.py --video_path [video_path]
+```
+If the model does not produce good results, try to run the script with more stride values using `--strides`.
+
+Example of generated videos showing the repetition count, with the periodicity score and the temporal self-similarity matrix:
+<div align="center">
+  <img src="img/example5_score.gif" height="200" />
+  <img src="img/example5_tsm.png" height="200" />
+</div>