Update app.py

app.py

@@ -16,7 +16,7 @@ depth_model = DPTForDepthEstimation.from_pretrained("Intel/dpt-large")
 def apply_gaussian_blur(image):
     # Resize and preprocess the image
     image = image.resize((512, 512)).convert("RGB")
-    inputs = image_processor(image, return_tensors="pt")
+    inputs = segmentation_processor(image, return_tensors="pt")
 
     # Perform semantic segmentation using the model
     with torch.no_grad():
@@ -30,6 +30,9 @@ def apply_gaussian_blur(image):
     person_index = 12  # Assuming 12 is the 'person' class index
     binary_mask = (segmentation == person_index).numpy().astype(np.uint8) * 255  # Convert to 0 and 255
 
+    # Resize the mask to match the image size (512x512)
+    binary_mask = cv2.resize(binary_mask, (512, 512), interpolation=cv2.INTER_NEAREST)
+
     # Convert the original image to a numpy array
     image_np = np.array(image)
 
@@ -47,7 +50,6 @@ def apply_gaussian_blur(image):
     final_image_pil = Image.fromarray(final_image)
 
     return final_image_pil
-    # return image
 
 def apply_lens_blur(image):
     # Resize and preprocess the image