This project built a web page using Streamlit framework that providing functions for basic image detection, such as face regconition, object detection or hand detection. it have referenced OpenCV document and source code
- FACE RECOGNITION - RECOGNIZE 5 People in 1 frame
- Detection by different types of objects: person - bicycle - car - motorbike - aeroplane - bus - train - truck - boat
- Using Yolov4
- Recognition of unclear handwritten digits - guessing base on the shape the handwritten digits
- Regconition different types of fruits, including 15 types trained in the onnx file: 'Cucumber', 'Apple', 'Kiwi', 'Banana', 'Orange', 'Coconut', 'Peach', ' Cherry', 'Pear', 'Pomegranate', 'Pineapple', 'Watermelon', 'Grapes', 'Strawberry', 'Melon'
- Using Yolov5
- At the present, it only can recognize 3 English letters from hand signs, which are A, B and C
- Using Keras
- Environment: Python 3.9 or lower
- Web Framework: Streamlit
- Packages:
- OpenCV
- Numpy
- Streamlit
- Matplotlib