Update app.py

app.py

@@ -1,31 +1,22 @@
 import gradio as gr
 from nudenet import NudeDetector
 import cv2
+import numpy as np
 
-def blur_image(image_path, detections, parts_to_blur):
+def circular_blur(image_path, detections, parts_to_blur):
     image = cv2.imread(image_path)
     
     for detection in detections:
         label = detection['class']
         if label in parts_to_blur:
             x, y, width, height = map(int, detection['box'])
-            x1, y1 = x, y
-            x2, y2 = x + width, y + height
+            center_x, center_y = x + width // 2, y + height // 2
+            radius = int(min(width, height) / 2)
 
-            x1 = max(0, x1)
-            y1 = max(0, y1)
-            x2 = min(image.shape[1], x2)
-            y2 = min(image.shape[0], y2)
-
-            print(f"Blurring region: {x1, y1, x2, y2} for label: {label}")
-            roi = image[y1:y2, x1:x2]
-            
-            if roi.size == 0:
-                print(f"Skipping empty ROI for detection: {detection}")
-                continue
-            
-            roi = cv2.GaussianBlur(roi, (51, 51), 30)
-            image[y1:y2, x1:x2] = roi
+            mask = np.zeros_like(image)
+            cv2.circle(mask, (center_x, center_y), radius, (255, 255, 255), -1)
+            blurred_image = cv2.GaussianBlur(image, (51, 51), 30)
+            image = np.where(mask == 255, blurred_image, image)
     
     blurred_image_path = 'blurred_' + image_path.split('/')[-1]
     cv2.imwrite(blurred_image_path, image)
@@ -41,7 +32,7 @@ def process(input_img):
         'MALE_BREAST_EXPOSED', 'ANUS_EXPOSED'
     ]
     
-    blurred_image_path = blur_image(input_img, detections, parts_to_blur)
+    blurred_image_path = circular_blur(input_img, detections, parts_to_blur)
     return blurred_image_path
 
 iface = gr.Interface(process, gr.components.Image(type='filepath'), gr.components.Image(type="filepath"))