Table of contents

• General Information
• Problem Solving
• Technology

General Information

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

Problem Solving

🧑‍🤝‍🧑 Module 1: Face Recognition

• FACE RECOGNITION - RECOGNIZE 5 People in 1 frame

👨‍👩‍👧‍👦 Module 2: Object Detection

• Detection by different types of objects: person - bicycle - car - motorbike - aeroplane - bus - train - truck - boat
• Using Yolov4

✍️ Module 3: Mnist Hadwritten Alphanumeric Recognition

• Recognition of unclear handwritten digits - guessing base on the shape the handwritten digits

🍉 Module 4: ️Fruit Type Detection

• 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

✋ Module 5: Recognizing Letter Signs By Hand

• At the present, it only can recognize 3 English letters from hand signs, which are A, B and C
• Using Keras

Technology

• Environment: Python 3.9 or lower
• Web Framework: Streamlit
• Packages:
  • OpenCV
  • Numpy
  • Streamlit
  • Matplotlib