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Update app.py
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app.py
CHANGED
@@ -43,6 +43,12 @@ else:
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st.image(rescaled)
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input = jnp.array(rescaled).reshape(1, 28, 28, 1) / 255.
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st.write("Model Prediction: " + cnn.apply({"params": params}, input).argmax(axis=1)[0])
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def gridify(kernel, grid, kernel_size, scaling=5, padding=1):
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scaled_and_padded = np.pad(np.repeat(np.repeat(kernel, repeats=scaling, axis=0), repeats=scaling, axis=1), ((padding,),(padding,),(0,),(0,)), 'constant', constant_values=(-1,))
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st.image(rescaled)
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input = jnp.array(rescaled).reshape(1, 28, 28, 1) / 255.
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st.write("Model Prediction: " + cnn.apply({"params": params}, input).argmax(axis=1)[0])
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input = jnp.array([jnp.array(Image.open(uploaded_file).convert("HSV").split()[2].resize((28, 28))).reshape(1, 28, 28, 1) / 255. for uploaded_file in uploaded_files])
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prediction = cnn.apply({"params": params}, input)
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for (index, image) in enumerate(uploaded_files):
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st.image(Image.open(image))
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st.write("Model Prediction: " + prediction[index].argmax(axis=0)[0])
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def gridify(kernel, grid, kernel_size, scaling=5, padding=1):
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scaled_and_padded = np.pad(np.repeat(np.repeat(kernel, repeats=scaling, axis=0), repeats=scaling, axis=1), ((padding,),(padding,),(0,),(0,)), 'constant', constant_values=(-1,))
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