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

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Deep Learning LF-YOLO
Overview

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.

Model size (pixels) mAP50test
 params (M) FLOPS (B)
Cascasde-RCNN (ResNet50) (1333, 800) 90.0 68.9 243.2
Cascasde-RCNN (ResNet101) (1333, 800) 90.7 87.9 323.1
Faster-RCNN (ResNet50) (1333, 800) 90.1 41.1 215.4
Faster-RCNN (ResNet101) (1333, 800) 92.2 60.1 295.3
Dynamic-RCNN (ResNet50) (1333, 800) 90.3 41.1 215.4
RetinaNet (ResNet50) (1333, 800) 80.0 36.2 205.2
VFNet (ResNet50) (1333, 800) 87.0 32.5 197.8
VFNet (ResNet101) (1333, 800) 87.2 51.5 277.7
Reppoints (ResNet101) (1333, 800) 82.7 36.6 199.0
SSD300 (VGGNet) 300 88.1 24.0 30.6
YOLOv3 (Darknet52) 416 91.0 62.0 33.1
SSD (MobileNet v2) 300 82.3 3.1 0.7
YOLOv3 (MobileNet v2) 416 90.2 3.7 1.6
LF-YOLO-0.5 640 90.7 1.8 1.1
LF-YOLO 640 92.9 7.4 17.1

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

Model size (pixels) mAP50test
 params (M) FLOPS (B)
YOLOv3-tiny 640 34.8 8.8 13.2
YOLOv3 320 51.5 39.0 61.9
SSD 300 41.2 35.2 34.3
SSD 512 46.5 99.5 34.3
Faster R-CNN (VGG16) shorter size: 800 43.9 - 278.0
R-FCN (ResNet50) shorter size: 800 49.0 - 133.0
R-FCN (ResNet101) shorter size: 800 52.9 - 206.0
LF-YOLO 640 47.8 7.4 17.1

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
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Comments
  • RuntimeError: The size of tensor a (80) must match the size of tensor b (44) at non-singleton dimension 3

    RuntimeError: The size of tensor a (80) must match the size of tensor b (44) at non-singleton dimension 3

    Hi, when I run python detect.py --source data/images --weights LF-YOLO.pt --conf 0.25, I find there is no LF-YOLO.pt and I use yolov3.pt instead, but I get an error: RuntimeError: The size of tensor a (80) must match the size of tensor b (44) at non-singleton dimension 3. Could you help me? Thank you!

    opened by lijunyu159 2
  • opencv-python>=4.1.2

    opencv-python>=4.1.2

    hello，When I was running your code, there was a problem with the version of OpenCV。My opencv is 4.5.2, but He reminded me opencv-python>=4.1.2

    requirements: opencv-python>=4.1.2 not found and is required by YOLOv3, attempting auto-update... ERROR: Invalid requirement: "'opencv-python" Traceback (most recent call last): File "d:\Studies\bhdx\CODE\LF-YOLO-master\utils\general.py", line 110, in check_requirements pkg.require(r) File "D:\Studies\Anaconda3\envs\pytorch\lib\site-packages\pkg_resources_init_.py", line 891, in require needed = self.resolve(parse_requirements(requirements)) File "D:\Studies\Anaconda3\envs\pytorch\lib\site-packages\pkg_resources_init_.py", line 777, in resolve raise DistributionNotFound(req, requirers) pkg_resources.DistributionNotFound: The 'opencv-python>=4.1.2' distribution was not found and is required by the application

    During handling of the above exception, another exception occurred:

    Traceback (most recent call last): File "d:/Studies/bhdx/CODE/LF-YOLO-master/train.py", line 511, in check_requirements() File "d:\Studies\bhdx\CODE\LF-YOLO-master\utils\general.py", line 114, in check_requirements print(subprocess.check_output(f"pip install '{e.req}'", shell=True).decode()) File "D:\Studies\Anaconda3\envs\pytorch\lib\subprocess.py", line 415, in check_output return run(*popenargs, stdout=PIPE, timeout=timeout, check=True, File "D:\Studies\Anaconda3\envs\pytorch\lib\subprocess.py", line 516, in run raise CalledProcessError(retcode, process.args, subprocess.CalledProcessError: Command 'pip install 'opencv-python>=4.1.2'' returned non-zero exit status 1.

    Do you have this problem？

    opened by 1311523821 1
  • RuntimeError: The size of tensor a (80) must match the size of tensor b (44) at naon-singleton dimension 3

    RuntimeError: The size of tensor a (80) must match the size of tensor b (44) at naon-singleton dimension 3

    Hi, when I run python detect.py --source data/images --weights LF-YOLO.pt --conf 0.25, I find there is no LF-YOLO.pt and I use yolov3.pt instead, but I get an error: RuntimeError: The size of tensor a (80) must match the size of tensor b (44) at naon-singleton dimension 3. Could you help me? Thank you!

    opened by lijunyu159 0
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