The scripts are developed using Python 2.7 and OpenCV 3.2.0
- Run the script by
python FingersNumberDetector.py
- Place your hand on the 9 green squares and capture your skin color by pressing z.
- Move the ROI (blue square) if you want.
- Move your hand away (any moving objects) from the ROI.
- Capture the background by pressing b.
- Now you can start placing your hand in the ROI.
| Key | Description |
|---|---|
| j | Move ROI Down |
| k | Move ROI Up |
| h | Move ROI Left |
| l | Move ROI Right |
| q | Exit |
| b | Capture the background |
| r | Reset the background subtractor |
Basically, it is the same thing as FingersNumberDetector.py. The only difference is that CNN is used for counting the number of fingers.
Same as above with additional functionality to sample training and testing data. Remember to create the directories below before using.
\dataset\
|-- \train\
|-- \test\
Same as above with some additional keys below.
| Key | Description |
|---|---|
| u | Sample training data |
| i | Sample testing data |
| 0 | Sample "zero" image |
| 1 | Sample "one" image |
| 2 | Sample "two" image |
| 3 | Sample "three" image |
| 4 | Sample "four" image |
| 5 | Sample "five" image |
- lzane/Fingers-Detection-using-OpenCV-and-Python. https://github.com/lzane/Fingers-Detection-using-OpenCV-and-Python
- amarlearning/Finger-Detection-and-Tracking. https://github.com/amarlearning/Finger-Detection-and-Tracking