EmotiVision 🎭

EmotiVision is a facial emotion detection project built using YOLOv5.

The model analyzes facial expressions in images and classifies them into emotion categories such as:

• Happy
• Sad
• Neutral

Features

• Facial emotion detection using a trained YOLOv5 model
• Displays the detected emotion and confidence score
• Includes sample images for testing
• Allows users to select and analyze their own images

Project Structure

• emotion_detection.ipynb — Main notebook
• YOLO/yolov5/ — YOLOv5 files and trained model
• test_images/ — Sample images used for testing
• Emotion Detection.v1i.yolov5pytorch/ — Dataset used for training

How to Run

1. Open emotion_detection.ipynb.
2. Run the Import Libraries section.
3. Run the Load Trained YOLOv5 Model section.
4. Run the sample image test.
5. Use Try Your Own Image to select and analyze a new image.

Model

The trained weights are stored in:

YOLO/yolov5/runs/train/exp/weights/best.pt