Update app.py

app.py

@@ -1,32 +1,50 @@
-# Archive paper: https://arxiv.org/abs/2404.13000
-
 import os
 import gradio as gr
-import matplotlib.pyplot as plt
 import numpy as np
 import skimage
-from skimage import io, transform
-
-from io_utils import LoadImageD
+from skimage import io
+import torch
+import monai
+from monai.transforms import Rotate
+
+# Placeholder for the 3D reconstruction model
+class Simple3DReconstructionModel:
+    def __init__(self):
+        # Load your pre-trained model here
+        self.model = None  # replace with actual model loading
+
+    def reconstruct_3d(self, image):
+        # Implement the 3D reconstruction logic here
+        # This is a placeholder example
+        return np.zeros((128, 128, 128))
+
+    def rotate_3d(self, volume, angles):
+        # Rotate the 3D volume using MONAI
+        rotate = Rotate(angles, mode='bilinear')
+        rotated_volume = rotate(volume)
+        return rotated_volume
+
+    def project_2d(self, volume):
+        # Project the 3D volume back to 2D
+        # This is a placeholder example
+        projection = np.max(volume, axis=0)
+        return projection
+
+# Initialize the model
+model = Simple3DReconstructionModel()
 
 # Gradio helper functions
 
-current_img = None
-live_preds = None
-
-def rotate_img(image, angles):
-    """Rotate the input image based on the given angles."""
-    xt, yt, zt = angles
-
-    # Apply rotations (this is just a placeholder, replace with your actual logic)
-    rotated_img = skimage.transform.rotate(image, angle=xt, mode='edge')
-    rotated_img = skimage.transform.rotate(rotated_img, angle=yt, mode='edge')
-    rotated_img = skimage.transform.rotate(rotated_img, angle=zt, mode='edge')
-
-    return rotated_img
+def process_image(img, xt, yt, zt):
+    # Reconstruct the 3D volume
+    volume = model.reconstruct_3d(img)
+    # Rotate the 3D volume
+    rotated_volume = model.rotate_3d(volume, (xt, yt, zt))
+    # Project the rotated volume back to 2D
+    output_img = model.project_2d(rotated_volume)
+    return output_img
 
 def rotate_btn_fn(img, xt, yt, zt, add_bone_cmap=False):
-    global current_img
     try:
         angles = (xt, yt, zt)
         print(f"Rotating with angles: {angles}")
@@ -40,8 +58,8 @@ def rotate_btn_fn(img, xt, yt, zt, add_bone_cmap=False):
         else:
             raise ValueError("Invalid input image")
 
-        # Apply the rotation
-        out_img = rotate_img(img, angles)
+        # Process the image with the model
+        out_img = process_image(img, xt, yt, zt)
 
         if not add_bone_cmap:
             return out_img
@@ -49,7 +67,6 @@ def rotate_btn_fn(img, xt, yt, zt, add_bone_cmap=False):
         cmap = plt.get_cmap('bone')
         out_img = cmap(out_img)
         out_img = (out_img[..., :3] * 255).astype(np.uint8)
-        current_img = out_img
         return out_img
 
     except Exception as e: