[LEADERG AI ZOO] Jupyter-Image-Object-Detection-DETR-PyTorch

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繁體中文

 

[Introduction]

 

Using DETR for object detection can be applied to factory defect detection, medical image analysis, biological image analysis, industrial safety image analysis, and mask image analysis.

 

 

[Instruction]

 

The solution process is:

Annotate images -> convert to coco format -> training -> inference

 

1. 1_annotation_pascal_voc_xml.ipynb

After running, open the web page for image annotation.

parameter:

In # parameters, --port 8801 is the port occupied by the webpage. If user 8801 is occupied, please change the port value by yourself.

The training and verification images are in data/train and data/val2017.

 

2. 2_VOC_to_COCO.ipynb

Convert the annotation file from VOC format to COCO format.

The converted json annotation file is stored in data/annotations.

 

3. 3_train.ipynb

Start training images after running.

 

4. 4_inference.ipynb

Inferring a single image.

parameter:

--inference_file is the inference image path.

--num_classes is how many classes are trained.

 

DETR.png

 


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