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| import gradio as gr | |
| from image_classifier import ImageClassifier | |
| from PIL import Image | |
| classifier = ImageClassifier('models/trained_model.pth') | |
| examples = [ | |
| 'examples/0ab9373f-4d97-456a-9b9d-60b4d05d102e.jpg', | |
| 'examples/093e6044-5809-44d6-a93f-f06a6702f20d.jpg', | |
| 'examples/332b50b9-ab27-42ac-9118-ae32b3458d97.jpg', | |
| 'examples/357fbd95-ff50-4d90-9487-531595f02a9e.jpg', | |
| 'examples/b100a944-0e67-4e4d-9ccc-c6c63fb99c8e.jpg' | |
| ] | |
| def predict(image): | |
| image = Image.fromarray(image.astype('uint8'), 'RGB') | |
| return classifier.classify_image(image) | |
| image = gr.inputs.Image(shape=(192,192)) | |
| label = gr.outputs.Label() | |
| intf = gr.Interface(fn=predict, inputs=image, outputs=label, examples=examples) | |
| intf.launch(inline=False) | |