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This project showcases face recognition, animal class detection (YOLOv8), MNIST digit recognition, image processing, and hand gesture recognition in a Streamlit web interface.

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Digital Image Processing Final

Report Video: YOUTUBE

This project summarizes the various topics covered and incorporates them into a Streamlit web interface.

Content Description
1 Face Detection Face recognition, with a minimum of 5 individuals. Within a single frame, there must be multiple individuals with their names labeled.
2 Object Detection Recognition of 5 object classes using YOLOv8, trained on Google Colab. The 5 objects selected are capybara, hedgehog, raccoon, kangaroo, and penguin.
3 Handwritten Digit Detection Handwritten digit recognition using the MNIST dataset.
4 Image Processing Various chapters on image processing.
5 Hand Gesture Detection Additionally, we have implemented hand gesture recognition, including gestures such as open hand, closed hand, heart symbol, OK sign, and thumbs up.

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This project showcases face recognition, animal class detection (YOLOv8), MNIST digit recognition, image processing, and hand gesture recognition in a Streamlit web interface.

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