[Dygraph]modify operators and batch_operators in data preprocess (#1666)

* modify operators and batch_operators in data preprocess

* import BboxError and ImageError in operators

* modify code according to review

* modify some bugs

* add Gt2Solov2TargetOp in batch_operators

* modify code according to review

ppdet/data/transform/__init__.py

@@ -15,8 +15,11 @@
 from . import operators
 from . import batch_operators
 
+# TODO: operators and batch_operators will be replaced by operator and batch_operator
 from .operators import *
+from .operator import *
 from .batch_operators import *
+from .batch_operator import *
 
 __all__ = []
 __all__ += registered_ops

ppdet/data/transform/batch_operators.py

@@ -24,7 +24,7 @@ except Exception:
 import logging
 import cv2
 import numpy as np
-from .operators import register_op, BaseOperator
+from .operator import register_op, BaseOperator
 from .op_helper import jaccard_overlap, gaussian2D
 
 logger = logging.getLogger(__name__)

ppdet/data/transform/operators.py

@@ -39,6 +39,7 @@ from PIL import Image, ImageEnhance, ImageDraw
 
 from ppdet.core.workspace import serializable
 from ppdet.modeling.layers import AnchorGrid
+from .operator import register_op, BaseOperator, BboxError, ImageError
 
 from .op_helper import (satisfy_sample_constraint, filter_and_process,
                         generate_sample_bbox, clip_bbox, data_anchor_sampling,
@@ -48,45 +49,6 @@ from .op_helper import (satisfy_sample_constraint, filter_and_process,
 
 logger = logging.getLogger(__name__)
 
-registered_ops = []
-
-
-def register_op(cls):
-    registered_ops.append(cls.__name__)
-    if not hasattr(BaseOperator, cls.__name__):
-        setattr(BaseOperator, cls.__name__, cls)
-    else:
-        raise KeyError("The {} class has been registered.".format(cls.__name__))
-    return serializable(cls)
-
-
-class BboxError(ValueError):
-    pass
-
-
-class ImageError(ValueError):
-    pass
-
-
-class BaseOperator(object):
-    def __init__(self, name=None):
-        if name is None:
-            name = self.__class__.__name__
-        self._id = name + '_' + str(uuid.uuid4())[-6:]
-
-    def __call__(self, sample, context=None):
-        """ Process a sample.
-        Args:
-            sample (dict): a dict of sample, eg: {'image':xx, 'label': xxx}
-            context (dict): info about this sample processing
-        Returns:
-            result (dict): a processed sample
-        """
-        return sample
-
-    def __str__(self):
-        return str(self._id)
-
 
 @register_op
 class DecodeImage(BaseOperator):