Update app.py

app.py

@@ -31,21 +31,22 @@ def warp_design(cloth_img, design_img):
     cloth_np = np.array(cloth_img)
     design_np = np.array(design_img)
     
-    # Estimate depth for fold detection
-    depth_map = estimate_depth(cloth_img)
-    depth_map = cv2.resize(depth_map, (cloth_np.shape[1], cloth_np.shape[0]))  # Ensure matching dimensions
-    
-    # Resize design to fit centrally on clothing
-    design_h, design_w = cloth_np.shape[:2]
-    center_x, center_y = design_w // 2, design_h // 2
-    resized_design = cv2.resize(design_np, (design_w // 2, design_h // 2))
+    # Ensure design fits within the center of the clothing
+    h, w, _ = cloth_np.shape
+    dh, dw, _ = design_np.shape
+    scale_factor = min(w / dw, h / dh) * 0.8  # Scale to 80% of the available space
+    new_w, new_h = int(dw * scale_factor), int(dh * scale_factor)
+    design_np = cv2.resize(design_np, (new_w, new_h))
     
-    # Place design at the center of the clothing image
-    y_offset = center_y - resized_design.shape[0] // 2
-    x_offset = center_x - resized_design.shape[1] // 2
+    # Create a blank canvas and paste the resized design at the center
+    design_canvas = np.zeros_like(cloth_np)
+    x_offset = (w - new_w) // 2
+    y_offset = (h - new_h) // 2
+    design_canvas[y_offset:y_offset+new_h, x_offset:x_offset+new_w] = design_np
     
-    blended_design = cloth_np.copy()
-    blended_design[y_offset:y_offset + resized_design.shape[0], x_offset:x_offset + resized_design.shape[1]] = resized_design
+    # Estimate depth for fold detection
+    depth_map = estimate_depth(cloth_img)
+    depth_map = cv2.resize(depth_map, (w, h))
     
     # Generate displacement map based on depth
     displacement_x = cv2.Sobel(depth_map, cv2.CV_32F, 1, 0, ksize=5)
@@ -56,14 +57,13 @@ def warp_design(cloth_img, design_img):
     displacement_y = cv2.normalize(displacement_y, None, -5, 5, cv2.NORM_MINMAX)
     
     # Warp design using displacement map
-    h, w, _ = cloth_np.shape
     map_x, map_y = np.meshgrid(np.arange(w), np.arange(h))
     map_x = np.clip(np.float32(map_x + displacement_x), 0, w - 1)
     map_y = np.clip(np.float32(map_y + displacement_y), 0, h - 1)
-    warped_design = cv2.remap(blended_design, map_x, map_y, interpolation=cv2.INTER_LINEAR, borderMode=cv2.BORDER_REFLECT)
+    warped_design = cv2.remap(design_canvas, map_x, map_y, interpolation=cv2.INTER_LINEAR, borderMode=cv2.BORDER_REFLECT)
     
-    # Blend images
-    blended = cv2.addWeighted(cloth_np, 0.6, warped_design, 0.4, 0)
+    # Blend images without excessive transparency
+    blended = cv2.addWeighted(cloth_np, 0.7, warped_design, 0.7, 0)
     return Image.fromarray(blended)
 
 def main(cloth, design):
@@ -74,7 +74,7 @@ iface = gr.Interface(
     inputs=[gr.Image(type="pil"), gr.Image(type="pil")],
     outputs=gr.Image(type="pil"),
     title="AI Cloth Design Warping",
-    description="Upload a clothing image and a design to blend it naturally at the center, considering fabric folds."
+    description="Upload a clothing image and a design to blend it naturally, ensuring it stays centered and follows fabric folds."
 )
 
 if __name__ == "__main__":