@ptrblck, I am using the torchvision.datasets.ImageFolder, each subfolder is getting class index serially, but problem is …My batch_size =256(default),for input images >= batch_size my precision values are quite good,for input images<batch_size , my precision values are too bad.
but my prediction is predicting correctly, have a look into this…!
target|690x387 2
precision is getting the value by comparing the target and predicted values,for images>batch_size target starting index value is 0s,but for img<batchsize target is starting with 1s …so although prediction is correct for img<256 because of prediction is compared with target my precision is very bad
Can you please tell why this is happening in target for img<256,it will be really helpfull as i am struck in this for longer duration,
github repo which i am referring

  
      
      GitHub
  
  
    

jiecaoyu/XNOR-Net-PyTorch 1

PyTorch Implementation of XNOR-Net. Contribute to jiecaoyu/XNOR-Net-PyTorch development by creating an account on GitHub.