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DETR Pytorch

  • Dataset
    • Nested Tensor 분석 -> resize를 600x600로 구성
    • Loss에 들어가는 GT를 어떻게 변형하는지 확인 (공집합 등)
    • Data Augmentation (Random Crop)
  • Model
    • 구조 이해
    • Backbone (ResNet50 + Positional Encoding)
      • Positional Encoding 분석
    • Transformer Encoder
    • Transformer Decoder
    • TEST
  • Loss (Criterion)
    • Matcher (scipy.optimizer, Hungarian Algorithm)
    • Hungarian Loss (loss label, boxes loss, cardinality loss)
    • Check versus original loss
  • Training
    • Find training epoch, batch, lr
    • Compare optimizer for Transformer with Backbone
***** configuration *****
optimizer        : AdamW
lr               : 1e-4(Transformer) / 1e-5(Backbone)
weight decay     : 1e-4
initialzation    : Xavier(uniform)
lr scheduler     : StepLR(at 200 epoch) - gamma 0.1
batch size       : 64
batch size / GPU : 4 
num_GPU (paper)  : 16 V100
Traning epoch    : 300

epoch 3 일때 test 사진

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