fix: requested changes

doctr/models/_utils.py

@@ -216,7 +216,7 @@ def rectify_loc_preds(
     return np.stack(
         [np.roll(
             page_loc_pred,
-            orientation - 1,
+            orientation,
             axis=0) for orientation, page_loc_pred in zip(orientations, page_loc_preds)],
         axis=0
     ) if len(orientations) > 0 else None

doctr/models/builder.py

@@ -49,9 +49,9 @@ def _sort_boxes(boxes: np.ndarray) -> np.ndarray:
 
         Returns:
             tuple: indices of ordered boxes of shape (N,), boxes
-            If straight boxes are passed tpo the function, boxes are unchanged
-            else: boxes returned are straight boxes fitted to the straightened rotated boxes
-            so that we fit the lines afterwards to the straigthened page
+                If straight boxes are passed tpo the function, boxes are unchanged
+                else: boxes returned are straight boxes fitted to the straightened rotated boxes
+                so that we fit the lines afterwards to the straigthened page
         """
         if boxes.ndim == 3:
             boxes = rotate_boxes(

doctr/models/detection/differentiable_binarization/base.py

@@ -83,8 +83,8 @@ def polygon_to_box(
         expanded_points = np.asarray(_points)  # expand polygon
         if len(expanded_points) < 1:
             return None
-        return cv2.boundingRect(expanded_points) if self.assume_straight_pages else cv2.boxPoints(
-            cv2.minAreaRect(expanded_points)
+        return cv2.boundingRect(expanded_points) if self.assume_straight_pages else np.roll(
+            cv2.boxPoints(cv2.minAreaRect(expanded_points)), -1, axis=0
         )
 
     def bitmap_to_boxes(

doctr/models/detection/differentiable_binarization/pytorch.py

@@ -40,9 +40,6 @@
         'url': 'https://github.com/mindee/doctr/releases/download/v0.3.1/db_mobilenet_v3_large-fd62154b.pt',
     },
     'db_resnet50_rotation': {
-        'backbone': resnet50,
-        'backbone_submodule': None,
-        'fpn_layers': ['layer1', 'layer2', 'layer3', 'layer4'],
         'input_shape': (3, 1024, 1024),
         'mean': (0.798, 0.785, 0.772),
         'std': (0.264, 0.2749, 0.287),
@@ -393,4 +390,11 @@ def db_resnet50_rotation(pretrained: bool = False, **kwargs: Any) -> DBNet:
         text detection architecture
     """
 
-    return _dbnet('db_resnet50_rotation', pretrained, **kwargs)
+    return _dbnet(
+        'db_resnet50_rotation',
+        pretrained,
+        resnet50,
+        ['layer1', 'layer2', 'layer3', 'layer4'],
+        None,
+        **kwargs,
+    )

doctr/models/detection/zoo.py

@@ -16,6 +16,7 @@
 
 if is_tf_available():
     ARCHS = ['db_resnet50', 'db_mobilenet_v3_large', 'linknet_resnet18']
+    ROT_ARCHS = []
 elif is_torch_available():
     ARCHS = ['db_resnet34', 'db_resnet50', 'db_mobilenet_v3_large', 'linknet_resnet18', 'db_resnet50_rotation']
     ROT_ARCHS = ['db_resnet50_rotation']

doctr/transforms/modules/tensorflow.py

@@ -75,7 +75,6 @@ def extra_repr(self) -> str:
 
     def __call__(self, img: tf.Tensor) -> tf.Tensor:
         input_dtype = img.dtype
-        print(self.output_size)
         img = tf.image.resize(img, self.output_size, self.method, self.preserve_aspect_ratio)
         if self.preserve_aspect_ratio:
             # pad width