pull upstream

Author: horcham

deploy/py_infer/infer.py

@@ -12,7 +12,7 @@ def main():
     args = infer_args.get_args()
     parallel_pipeline = ParallelPipeline(args)
     parallel_pipeline.start_pipeline()
-    parallel_pipeline.infer_for_images(args.input_images_dir, 0)
+    parallel_pipeline.infer_for_images(args.input_images_dir, task_id=0)
     parallel_pipeline.stop_pipeline()
 
 

deploy/py_infer/src/parallel/parallel_pipeline.py

@@ -22,14 +22,14 @@ def start_pipeline(self):
     def stop_pipeline(self):
         self.pipeline_manager.stop_pipeline()
 
-    def infer_for_images(self, input_images_dir, task_id):
+    def infer_for_images(self, input_images_dir, task_id=0):
         self.infer_params = dict(**self.pipeline_manager.module_params)
         self.send_image(input_images_dir, task_id)
 
     def fetch_result(self):
         return self.pipeline_manager.fetch_result()
 
-    def send_image(self, images: str, task_id):
+    def send_image(self, images: str, task_id=0):
         """
         send image to input queue for pipeline
         """
@@ -61,7 +61,7 @@ def _send_batch_image(self, images, batch_num, task_id):
         else:
             self.input_queue.put([[images], (1, task_id)], block=True)
 
-    def infer_for_array(self, input_array, task_id):
+    def infer_for_array(self, input_array, task_id=0):
         self.infer_params = dict(**self.pipeline_manager.module_params)
         self.send_array(input_array, task_id)
 

mindocr/data/transforms/transforms_factory.py

@@ -92,7 +92,8 @@ def transforms_dbnet_icdar15(phase="train"):
             {"DecodeImage": {"img_mode": "RGB", "to_float32": False}},
             {"DetLabelEncode": None},
             {"RandomScale": {"scale_range": [1.022, 3.0]}},
-            {"IaaAugment": {"Affine": {"rotate": [-10, 10]}, "Fliplr": {"p": 0.5}}},
+            {"RandomHorizontalFlip": {"p": 0.5}},
+            {"RandomRotate": {"degrees": [-10, 10], "expand_canvas": False, "p": 1.0}},
             {"RandomCropWithBBox": {"max_tries": 100, "min_crop_ratio": 0.1, "crop_size": (640, 640)}},
             {"ShrinkBinaryMap": {"min_text_size": 8, "shrink_ratio": 0.4}},
             {