AI Edge Defect Detection

This project uses a YOLO-based model for edge AI defect detection on images, classifying them as OK or NOK.

Installation

1. Upgrade pip to ensure compatibility:

python3 -m pip install --upgrade pip

2. Install the Ultralytics YOLO library:

python3 -m pip install ultralytics

3. Verify installation:

python3 -c 'from ultralytics import YOLO; print("Ultralytics is installed!")'

Once installed, you can start using your trained YOLO classification model to predict defects in images.

Tools

This project includes several utility scripts for dataset preparation, training, and testing the model:

• create.py – Generate and prepare an acceptable dataset for training.
• train.py – Train the YOLO model using the prepared dataset.
• test1.py – Test a single image and generate a detailed report of predictions.
• test2.py – Test a single image and quickly check if the prediction matches expectations.
• test3.py – Test a batch or group of images and summarize results for all of them.