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:
- download this model
- load pretrained model resnet18
- model_for_predict = models.resnet18(pretrained=True)
- load checkpoint from your local
- checkpoint = torch.load('pytorch_model.bin')
- model_for_predict.load_state_dict(checkpoint)
- predict the images
- model_for_predict.eval())
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