Code relaese for [MDF-Net:Multi-layer Feature Dynamic Interactive Fusion Network for Few-Shot Fine-Grained Image Classification).

• You can create a conda environment with the correct dependencies using the following command lines:

  conda env create -f environment.yml
  conda activate MDF

Datasets refer to the introduction in the paper. The preprocessing of the cropped CUB-200-2011 is the same as FRN.

• For example, to train MDF on CUB_fewshot_cropped with ResNet-12 backbone under the 1/5-shot setting, run the following command lines:

  cd experiments/CUB_fewshot_cropped/ResNet-12
  ./train.sh

    cd experiments/CUB_fewshot_cropped/ResNet-12
    python ./test.py

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