Butterfly image classification model that use pre-trained cnn model resnet18 and fine-tuned the last fully connected layer to classify 75 categories of butterfly species.

The model used the best checkpoint with 90% test accuracy.

The model constructed on Pytorch environment.

Training and testing result:

Epoch: 28 Train Loss: 0.17 Train Accuracy: 0.96 Test Accuracy: 0.90

To use this model you have to:

  1. download this model
  2. load pretrained model resnet18
  3. model_for_predict = models.resnet18(pretrained=True)
  4. load checkpoint from your local
  5. checkpoint = torch.load('pytorch_model.bin')
  6. model_for_predict.load_state_dict(checkpoint)
  7. predict the images
  8. model_for_predict.eval())

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Dataset used to train SoulPerforms/Butterfly_image_classification_resnet18