pamixsun commited on
Commit
8dcbbbd
1 Parent(s): a7b84ab

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +6 -10
app.py CHANGED
@@ -34,7 +34,7 @@ def main():
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  cols[0].subheader("Input image")
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  cols[1].subheader("Class activation map")
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- # set the visualization figure
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  fig, ax = plt.subplots()
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  # Sidebar
@@ -45,10 +45,9 @@ def main():
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  # Choose your own image
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  uploaded_file = st.sidebar.file_uploader("Upload image", type=['png', 'jpeg', 'jpg'])
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  if uploaded_file is not None:
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- # read the upload image
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  image = Image.open(uploaded_file).convert('RGB')
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  image = np.array(image).astype(np.uint8)
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- # page_idx = 0
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  ax.imshow(image)
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  ax.axis('off')
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  cols[0].pyplot(fig)
@@ -56,7 +55,7 @@ def main():
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  # For newline
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  st.sidebar.write('\n')
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- # actions
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  if st.sidebar.button("Analyze image"):
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  if uploaded_file is None:
@@ -64,22 +63,19 @@ def main():
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  else:
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  with st.spinner('Loading model...'):
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- # load model
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  model = GlaucomaModel(device=run_device)
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  with st.spinner('Analyzing...'):
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  # Forward the image to the model and get results
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  disease_idx, cam = model.process(image)
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-
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- # visualize results
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- # fig, ax = plt.subplots()
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- # plot the stitched image
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  ax.imshow(cam)
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  ax.axis('off')
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  cols[1].pyplot(fig)
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- # Display JSON
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  st.subheader(" Screening results:")
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  st.write('\n')
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  st.markdown(f"{model.id2label[disease_idx]}")
 
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  cols[0].subheader("Input image")
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  cols[1].subheader("Class activation map")
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+ # Set the visualization figure
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  fig, ax = plt.subplots()
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  # Sidebar
 
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  # Choose your own image
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  uploaded_file = st.sidebar.file_uploader("Upload image", type=['png', 'jpeg', 'jpg'])
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  if uploaded_file is not None:
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+ # Read the upload image
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  image = Image.open(uploaded_file).convert('RGB')
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  image = np.array(image).astype(np.uint8)
 
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  ax.imshow(image)
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  ax.axis('off')
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  cols[0].pyplot(fig)
 
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  # For newline
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  st.sidebar.write('\n')
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+ # Actions
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  if st.sidebar.button("Analyze image"):
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  if uploaded_file is None:
 
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  else:
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  with st.spinner('Loading model...'):
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+ # Load model
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  model = GlaucomaModel(device=run_device)
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  with st.spinner('Analyzing...'):
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  # Forward the image to the model and get results
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  disease_idx, cam = model.process(image)
 
 
 
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+ # Plot the class activation map
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  ax.imshow(cam)
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  ax.axis('off')
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  cols[1].pyplot(fig)
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+ # Display screening results
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  st.subheader(" Screening results:")
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  st.write('\n')
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  st.markdown(f"{model.id2label[disease_idx]}")