Add functionality for dark images.

app.py

@@ -68,6 +68,21 @@ def build_model(hypar,device):
     net.eval()  
     return net
 
+
+def crop_to_signature(mask):
+    contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+    if contours:
+        # Assume the largest contour is the signature
+        x, y, w, h = cv2.boundingRect(max(contours, key=cv2.contourArea))
+        # Add some padding to the bounding box
+        padding = 32
+        x, y, w, h = x-padding, y-padding, w+2*padding, h+2*padding
+        # Crop the mask
+        cropped_mask = mask[y:y+h, x:x+w]
+        return cropped_mask
+    else:
+        return mask  # Return the original mask if no contours are found
+
     
 def predict(net,  inputs_val, shapes_val, hypar, device):
     '''
@@ -129,11 +144,14 @@ def inference(image):
   
   pil_mask = Image.fromarray(mask).convert('L')
   im_rgb = Image.open(image).convert("RGB")
+  im_dark = Image.new('RGB', im_rgb.size, (0, 0, 0))
+  
   
   im_rgba = im_rgb.copy()
   im_rgba.putalpha(pil_mask)
+  im_dark.putalpha(pil_mask)
 
-  return [im_rgba, pil_mask]
+  return [im_rgba, pil_mask, im_dark]
 
 
 title = "Mysign.id - Signature Background removal based on DIS"