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YOLOv1-Pytorch implement

Detials

You can see more details about Yolo by clicking the link below:

https://zhuanlan.zhihu.com/p/64051698

Pretrained Model

You can download pretrained ResNet-Backbone YOLOv1 weight here:

https://pan.baidu.com/s/1YnPqOepzAbr9T_z4Ux-Ocg

Demo

Features

  • auto-save and load mechanism, default dir is './model'
  • base-net can be chose from pre-trained ResNet18、ResNet50 and ResNet101

Setup

the data set dir should be like this:

base_dir
   VOC2007
   	Annotations
   	ImageSets
   	JPEGImages
   	SegmentationClass
   	SegmentationObject
   VOC2012
   	Annotations
   	ImageSets
   	JPEGImages
   	SegmentationClass
   	SegmentationObject

you can setup the base_dir by this:

python train.py --voc_data_set_root /base_dir

usage

  • you can train model by this:

  • python train.py --voc_data_set_root /media/charles/750GB/VOC0712trainval --num_workers 12 --batch_size 16 --backbone resnet50 --save_step 500
    
  • assign the dir of pic in predict.py and run to see the demo

  • model weights will be uploaded afterwards

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YOLOv1 implementation of Pytorch with multi-backbone

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