PyTorch-YOLO_Nano

A minimal PyTorch implementation of YOLO_Nano

• Yolo_Nano
• Bag of Freebies for Training Object Detection Neural Networks

  Trick here I have done

  Bag of Freebies for Training Object Detection Neural Networks tell us that fixup in object detection can increase the mAP, So I realize it and test in result.

• [x] Data Augmentation
• [x] Fixup
• [x] Cosine lr decay
• [x] Warm up
• [ ] multi-GPU

  Download COCO

  $ cd data/ $ bash get_coco_dataset.sh

  Module Pipeline

  

  training

  
  bash train.sh  

Better Para:
--epochs 120
--batch_size 8
--model_def ./config/yolo-nano_person.cfg
--lr 2.5e-4
--fix_up True
--lr_policy cosine

## Testing
```bash
python test.py --data_config ./config/coco_person.data --model_def ./config/yolo-nano_person.cfg --weights_path [checkpoint path]

Result

In this engineer we only train our model using coco-train person class
we compare with yolov-3，yolo-tiny. We got competitive results.

Baidu WebDisk Key: p2j3

Ablation Result

Inference Result