Create __init__.py

ppcls/data/preprocess/__init__.py

+# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from ppcls.data.preprocess.ops.autoaugment import ImageNetPolicy as RawImageNetPolicy
+from ppcls.data.preprocess.ops.randaugment import RandAugment as RawRandAugment
+from ppcls.data.preprocess.ops.cutout import Cutout
+
+from ppcls.data.preprocess.ops.hide_and_seek import HideAndSeek
+from ppcls.data.preprocess.ops.random_erasing import RandomErasing
+from ppcls.data.preprocess.ops.grid import GridMask
+
+from ppcls.data.preprocess.ops.operators import DecodeImage
+from ppcls.data.preprocess.ops.operators import ResizeImage
+from ppcls.data.preprocess.ops.operators import CropImage
+from ppcls.data.preprocess.ops.operators import RandCropImage
+from ppcls.data.preprocess.ops.operators import RandFlipImage
+from ppcls.data.preprocess.ops.operators import NormalizeImage
+from ppcls.data.preprocess.ops.operators import ToCHWImage
+from ppcls.data.preprocess.ops.operators import AugMix
+
+from ppcls.data.preprocess.batch_ops.batch_operators import MixupOperator, CutmixOperator, FmixOperator
+
+import six
+import numpy as np
+from PIL import Image
+
+
+def transform(data, ops=[]):
+    """ transform """
+    for op in ops:
+        data = op(data)
+        #print(data.shape, op)
+    return data
+
+
+class AutoAugment(RawImageNetPolicy):
+    """ ImageNetPolicy wrapper to auto fit different img types """
+    def __init__(self, *args, **kwargs):
+        if six.PY2:
+            super(AutoAugment, self).__init__(*args, **kwargs)
+        else:
+            super().__init__(*args, **kwargs)
+
+    def __call__(self, img):
+        if not isinstance(img, Image.Image):
+            img = np.ascontiguousarray(img)
+            img = Image.fromarray(img)
+
+        if six.PY2:
+            img = super(AutoAugment, self).__call__(img)
+        else:
+            img = super().__call__(img)
+
+        if isinstance(img, Image.Image):
+            img = np.asarray(img)
+
+        return img
+
+
+class RandAugment(RawRandAugment):
+    """ RandAugment wrapper to auto fit different img types """
+    def __init__(self, *args, **kwargs):
+        if six.PY2:
+            super(RandAugment, self).__init__(*args, **kwargs)
+        else:
+            super().__init__(*args, **kwargs)
+
+    def __call__(self, img):
+        if not isinstance(img, Image.Image):
+            img = np.ascontiguousarray(img)
+            img = Image.fromarray(img)
+
+        if six.PY2:
+            img = super(RandAugment, self).__call__(img)
+        else:
+            img = super().__call__(img)
+
+        if isinstance(img, Image.Image):
+            img = np.asarray(img)
+
+        return img