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| import gradio as gr | |
| from fastai.vision.all import * | |
| import os | |
| # list all file names in the samples directory | |
| examples = [] | |
| for file in os.listdir('samples'): | |
| examples.append(['samples/' + file]) | |
| categories = ['Jazzmaster', 'Stratocaster', 'Telecaster'] | |
| image = gr.inputs.Image(shape=(192, 192)) | |
| label = gr.outputs.Label() | |
| # Load the trained model from the model.pkl file | |
| model = load_learner('model.pkl') | |
| def predict(image): | |
| # image = cv2.resize(image, (224, 224)) | |
| # image = np.expand_dims(image, axis=0) | |
| prediction, idx, probabilities = model.predict(image) | |
| return dict(zip(categories, map(float, probabilities))) | |
| iface = gr.Interface(fn=predict, inputs=image, outputs=label, | |
| examples=examples, capture_session=True) | |
| iface.launch() | |