Dynamic MLP for Fine-Grained Image Classification by Leveraging Geographical and Temporal Information
Dynamic MLP, which is parameterized by the learned embeddings of variable locations and dates to help fine-grained image classification. Requirements Experiment Environment python 3.6 pytorch 1.7.1+cu101 torchvision 0.8.2 Get pretrained models for SK-Res2Net following here.Get datasets following here. Train the model 1. Train image-only model Specify –image_only for training image-only models. ResNet-50 (67.924% Top-1 acc) CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 python3 train.py –name res50_image_only –
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