# HandGesturePy

**Repository Path**: jason921121/HandGesturePy

## Basic Information

- **Project Name**: HandGesturePy
- **Description**: Static Hand Gesture detection using opencv python with hog features and SVM .
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-04-17
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# HandGesturePy
Human Computer Interaction using hand gesutures using Opencv - Python .
Hand Gesture recognition is performed using HoG features and SVM as classifier.
This project is inspired from http://research.microsoft.com/pubs/220845/depth4free_SIGGRAPH.pdf

## Hardware Setup
![alt tag](https://raw.githubusercontent.com/arijitx/HandGesturePy/master/ScrenShots/hardware_setup.png)

## Difference after removing IR illuminator and using IR illuminators
![](https://raw.githubusercontent.com/arijitx/HandGesturePy/master/ScrenShots/cam_different.png)

## Final Setup
![](https://github.com/arijitx/HandGesturePy/tree/master/ScrenShots/final_setup.jpg)

## Project Modules
![](https://raw.githubusercontent.com/arijitx/HandGesturePy/master/ScrenShots/project_modules.png)

## TrainData
![alt tag](https://raw.githubusercontent.com/arijitx/HandGesturePy/master/TrainData2/1_1.jpg)
![alt tag](https://raw.githubusercontent.com/arijitx/HandGesturePy/master/TrainData2/2_1.jpg)
![alt tag](https://raw.githubusercontent.com/arijitx/HandGesturePy/master/TrainData2/3_1.jpg)
![alt tag](https://raw.githubusercontent.com/arijitx/HandGesturePy/master/TrainData2/4_1.jpg)
![alt tag](https://raw.githubusercontent.com/arijitx/HandGesturePy/master/TrainData2/5_1.jpg)
![alt tag](https://raw.githubusercontent.com/arijitx/HandGesturePy/master/TrainData2/6_1.jpg)
![alt tag](https://raw.githubusercontent.com/arijitx/HandGesturePy/master/TrainData2/7_1.jpg)
![alt tag](https://raw.githubusercontent.com/arijitx/HandGesturePy/master/TrainData2/8_1.jpg)
![alt tag](https://raw.githubusercontent.com/arijitx/HandGesturePy/master/TrainData2/9_1.jpg)

## Training Data Accuracy
<pre>
Number of Class : 9
Number of Item per Class : 20
Folder Name : TrainData2
Number of Cross validation Folds : 20

========================================================
+													   +
+				    MODEL EVALUATION				   +
+													   +
========================================================


----------------------- accuracy -----------------------
Mean    :    0.938888888889
Max     :    1.0
Min     :    0.666666666667
----------------------- f1_macro -----------------------
Mean    :    0.921296296296
Max     :    1.0
Min     :    0.611111111111
----------------------- f1_micro -----------------------
Mean    :    0.938888888889
Max     :    1.0
Min     :    0.666666666667
----------------------- precision_macro ----------------
Mean    :    0.912962962963
Max     :    1.0
Min     :    0.592592592593
----------------------- precision_micro ----------------
Mean    :    0.938888888889
Max     :    1.0
Min     :    0.666666666667
----------------------- precision_weighted -------------
Mean    :    0.912962962963
Max     :    1.0
Min     :    0.592592592593
----------------------- recall_macro -------------------
Mean    :    0.938888888889
Max     :    1.0
Min     :    0.666666666667
----------------------- recall_micro -------------------
Mean    :    0.938888888889
Max     :    1.0
Min     :    0.666666666667
----------------------- recall_weighted ----------------
Mean    :    0.938888888889
Max     :    1.0
Min     :    0.666666666667
</pre>
 
## FLOWChart
![](https://raw.githubusercontent.com/arijitx/HandGesturePy/master/ScrenShots/FLOWCHART.png)

## Steps
![](https://raw.githubusercontent.com/arijitx/HandGesturePy/master/ScrenShots/STEP1.png)
![](https://raw.githubusercontent.com/arijitx/HandGesturePy/master/ScrenShots/STEP2.png)
![](https://raw.githubusercontent.com/arijitx/HandGesturePy/master/ScrenShots/STEP3.png)

## Applications

[![IMAGE ALT TEXT HERE](https://img.youtube.com/vi/0f0RNrLPD8c/0.jpg)](https://www.youtube.com/watch?v=0f0RNrLPD8c)