[cherry-pick] Fix mot typo (#3956)

* fix operators typo

* fix mot typo, test=document_fix

deploy/python/mot_jde_infer.py

@@ -251,8 +251,7 @@ def predict_video(detector, camera_id):
             if not os.path.exists(save_dir):
                 os.makedirs(save_dir)
             cv2.imwrite(
-                os.path.join(save_dir, '{:05d}.jpg'.format(frame_id)),
-                im)
+                os.path.join(save_dir, '{:05d}.jpg'.format(frame_id)), im)
         else:
             writer.write(im)
         frame_id += 1

deploy/python/mot_sde_infer.py

@@ -392,8 +392,7 @@ def predict_video(detector, reid_model, camera_id):
             if not os.path.exists(save_dir):
                 os.makedirs(save_dir)
             cv2.imwrite(
-                os.path.join(save_dir, '{:05d}.jpg'.format(frame_id)),
-                im)
+                os.path.join(save_dir, '{:05d}.jpg'.format(frame_id)), im)
         else:
             writer.write(im)
         frame_id += 1

deploy/serving/test_client.py

@@ -41,4 +41,3 @@ fetch_map = client.predict(
 print(fetch_map)
 fetch_map["image"] = sys.argv[1]
 postprocess(fetch_map)
-

docs/tutorials/FAQ/README.md

@@ -4,4 +4,3 @@
 
 - [FAQ：第零期](./FAQ第零期.md)
 - [FAQ：第一期](./FAQ第一期.md)
-

ppdet/data/transform/mot_operators.py

@@ -108,7 +108,9 @@ class LetterBoxResize(BaseOperator):
         if not isinstance(im, np.ndarray):
             raise TypeError("{}: image type is not numpy.".format(self))
         if len(im.shape) != 3:
-            raise ImageError('{}: image is not 3-dimensional.'.format(self))
+            from PIL import UnidentifiedImageError
+            raise UnidentifiedImageError(
+                '{}: image is not 3-dimensional.'.format(self))
 
         # apply image
         height, width = self.target_size
@@ -135,7 +137,7 @@ class MOTRandomAffine(BaseOperator):
 
     Args:
         degrees (list[2]): the rotate range to apply, transform range is [min, max]
-        translate (list[2]): the translate range to apply, ransform range is [min, max]
+        translate (list[2]): the translate range to apply, transform range is [min, max]
         scale (list[2]): the scale range to apply, transform range is [min, max]
         shear (list[2]): the shear range to apply, transform range is [min, max]
         borderValue (list[3]): value used in case of a constant border when appling

ppdet/engine/trainer.py

@@ -17,6 +17,7 @@ from __future__ import division
 from __future__ import print_function
 
 import os
+import sys
 import copy
 import time
 

ppdet/modeling/losses/sparsercnn_loss.py

@@ -357,7 +357,7 @@ def boxes_iou(boxes1, boxes2):
     '''
     area1 = box_area(boxes1)
     area2 = box_area(boxes2)
-    
+
     lt = paddle.maximum(boxes1.unsqueeze(-2)[:, :, :2], boxes2[:, :2])
     rb = paddle.minimum(boxes1.unsqueeze(-2)[:, :, 2:], boxes2[:, 2:])