Updated app.py

app.py

@@ -29,7 +29,8 @@ def download_model():
 def extract_middle_slice(nifti_path, output_image_path):
     """
     Extracts a middle slice from a 3D NIfTI image and saves it as a PNG file.
-    The figure size is adjusted dynamically based on the slice's aspect ratio.
+    The figure size is adjusted dynamically based on the slice's aspect ratio
+    and scaled to be 50% smaller.
     """
     import nibabel as nib
     import matplotlib.pyplot as plt
@@ -44,15 +45,16 @@ def extract_middle_slice(nifti_path, output_image_path):
 
     # Calculate aspect ratio
     height, width = slice_data.shape
-    aspect_ratio = (width / height) * 0.5
+    aspect_ratio = width / height
 
-    # Dynamically adjust figure size based on aspect ratio
-    plt.figure(figsize=(6 * aspect_ratio, 6))  # Height fixed to 6, width scaled by aspect ratio
+    # Dynamically adjust figure size based on aspect ratio and scale down by 0.5
+    plt.figure(figsize=(4 * aspect_ratio, 4))  # Height scaled to 3, width scaled proportionally
     plt.imshow(slice_data, cmap="gray")
     plt.axis("off")
     plt.savefig(output_image_path, bbox_inches="tight", pad_inches=0)
     plt.close()
 
+
 # Function to run nnUNet inference
 @spaces.GPU  # Decorate the function to allocate GPU for its execution
 def run_nnunet_predict(nifti_file):