shallou commited on
Commit
2185839
·
verified ·
1 Parent(s): 1766266

Update app.py

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Files changed (1) hide show
  1. app.py +8 -7
app.py CHANGED
@@ -8,8 +8,7 @@ import os
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  # Function to load the model
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  @st.cache_resource
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  def load_model():
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- # Ensure this path is correct relative to your deployment setup
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- model_path = 'path_to_your_saved_model.h5'
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  if not os.path.isfile(model_path):
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  st.error(f"Model file not found: {model_path}")
@@ -17,6 +16,7 @@ def load_model():
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  try:
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  model = tf.keras.models.load_model(model_path)
 
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  return model
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  except Exception as e:
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  st.error(f"Error loading model: {e}")
@@ -54,11 +54,12 @@ def main():
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  st.write("")
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  st.write("Classifying...")
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- prediction = predict(image, model)
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-
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- # Adjust based on your model's output
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- predicted_class = np.argmax(prediction, axis=1)[0] # Assuming your model outputs probabilities for each class
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- st.write(f"Predicted class: {predicted_class}")
 
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  if __name__ == "__main__":
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  main()
 
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  # Function to load the model
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  @st.cache_resource
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  def load_model():
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+ model_path = 'path_to_your_saved_model.h5' # Ensure this path is correct relative to your deployment setup
 
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  if not os.path.isfile(model_path):
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  st.error(f"Model file not found: {model_path}")
 
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  try:
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  model = tf.keras.models.load_model(model_path)
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+ st.success("Model loaded successfully!")
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  return model
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  except Exception as e:
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  st.error(f"Error loading model: {e}")
 
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  st.write("")
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  st.write("Classifying...")
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+ try:
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+ prediction = predict(image, model)
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+ predicted_class = np.argmax(prediction, axis=1)[0] # Adjust based on your model's output
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+ st.write(f"Predicted class: {predicted_class}")
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+ except Exception as e:
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+ st.error(f"Error in prediction: {e}")
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  if __name__ == "__main__":
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  main()