LF-YOLO (Lighter and Faster YOLO) is used to detect defect of X-ray weld image.

This project is based on ultralytics/yolov3.

LF-YOLO (Lighter and Faster YOLO) is used to detect defect of X-ray weld image. The related paper is available here.

Download

$ git clone https://github.com/lmomoy/LF-YOLO

Train

We provide multiple versions of LF-YOLO with different widths.

$ python train.py --data coco.yaml --cfg LF-YOLO.yaml      --weights '' --batch-size 1
                                         LF-YOLO-1.25.yaml                           1
                                         LF-YOLO-0.75.yaml                           1
                                         LF-YOLO-0.5.yaml                            1

Results

We test LF-YOLO on our weld defect image dataset. Other methods are trained and tested based on MMDetection.

We test our model on public dataset MS COCO, and it also achieves competitive results.

Requirements

Python 3.8 or later with all requirements.txt dependencies installed, including torch>=1.7. To install run:

$ pip install -r requirements.txt

Inference

$ python detect.py --source data/images --weights LF-YOLO.pt --conf 0.25