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dl-gesture-recognition

★ 92 Open GitHub ↗

A real time hand gesture recognition system based on deep learning

// repository documentation

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## Overview

This project uses front-end separation, and the client has the following three forms of implementation:

- Manual gesture recognition, which means that the user determines the segmentation of continuous gestures
- Dynamic gesture recognition based on frame difference method
- Dynamic gesture recognition based on object tracking

The server encapsulates Temporal Relation Networks.

## Server

Test on **Ubuntu16.04 + Python3.6 + cuda9.0 + cudnn7.0.5 + Pytorch0.3.1 + opencv3.4**（[aliyun](https://www.aliyun.com) NVIDIA P100）, make sure you have installed the above environment.

### Dependencies

```
$ pip install flask
$ pip install pillow
$ pip install moviepy
$ sudo apt-get install ffmpeg
$ pip install -U scikit-learn
$ pip install scipy
$ pip install flask_uploads
```

and then download the [weight file](https://drive.google.com/open?id=16oON6bvVWLgFG0dSG5WH8a95E-adiHpg) and [configuration file](https://drive.google.com/open?id=1Xw4hW_EG10W9pqNzMVCOeodn0Bl34f0W), and place them in the `server/model` folder. Finally, run `server.py`

> `.placeholder` under empty folder can be deleted

## Client

Test on **Ubuntu16.04/Mac OS + Python3.6 + OpenCV3.4 + opencv_contrib**

### Dependencies

```
$ pip install pillow
$ pip install requests
```

### Manual

- server-address: gesture recognition server address

```
$ python run_manual.py -s [server-address]
```

Interactive mode: press the keyboard `s` key before each action, and press the `s` key again after the action is complete to complete the recognition

### Frame difference

you can choose the Background Subtraction Methods

- method: knn or mog
- threshold: The sum of the length and width of the contour identified by the algorithm is greater than the threshold is considered to be the hand

```
$ python run_frameDifferent -s [server-address] --method [method] --threshold [threshold]
```

### Object detection

GPU support is required to run this version, we tested on Ubuntu 16.04 + cuda9.0 + cudnn7.0.5 +  tensorflow1.6. You need to install [tensorflow1.6-gpu](https://www.tensorflow.org/install/) extra and [darkflow](https://github.com/thtrieu/darkflow), You can download darkflow from [here](https://drive.google.com/open?id=1khaq-aWudYW_b4GC7R_tyzWiWL3AzJE9).

```
$ pip install tensorflow-gpu
$ pip install Cython
$ cd darkflow
$ pip install .

# Check whether the installation is complete
$ flow --h
```

and then download the [weight file](https://drive.google.com/open?id=1Z2y3_ghDFBQqgN9ULudAiG4hcjOKkegH) and [configuration file](https://drive.google.com/open?id=1ygKOGGvLsjC-Dw-CIN9530947z9PpQGJ), and place them in the `model` folder and `cfg` folder respectively. Finally, run

```
$ python run_objectDetection.py -s [server-address]
```

dl-gesture-recognition

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