Modify file structure to separate python and cpp code (#223)

Modify code structure

python/fastdeploy/vision/detection/ppdet/__init__.py

@@ -0,0 +1,154 @@
+# Copyright (c) 2022 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 __future__ import absolute_import
+import logging
+from .... import FastDeployModel, Frontend
+from .... import c_lib_wrap as C
+
+
+class PPYOLOE(FastDeployModel):
+    def __init__(self,
+                 model_file,
+                 params_file,
+                 config_file,
+                 runtime_option=None,
+                 model_format=Frontend.PADDLE):
+        super(PPYOLOE, self).__init__(runtime_option)
+
+        assert model_format == Frontend.PADDLE, "PPYOLOE model only support model format of Frontend.Paddle now."
+        self._model = C.vision.detection.PPYOLOE(
+            model_file, params_file, config_file, self._runtime_option,
+            model_format)
+        assert self.initialized, "PPYOLOE model initialize failed."
+
+    def predict(self, input_image):
+        assert input_image is not None, "The input image data is None."
+        return self._model.predict(input_image)
+
+
+class PPYOLO(PPYOLOE):
+    def __init__(self,
+                 model_file,
+                 params_file,
+                 config_file,
+                 runtime_option=None,
+                 model_format=Frontend.PADDLE):
+        super(PPYOLOE, self).__init__(runtime_option)
+
+        assert model_format == Frontend.PADDLE, "PPYOLO model only support model format of Frontend.Paddle now."
+        self._model = C.vision.detection.PPYOLO(
+            model_file, params_file, config_file, self._runtime_option,
+            model_format)
+        assert self.initialized, "PPYOLO model initialize failed."
+
+
+class PPYOLOv2(PPYOLOE):
+    def __init__(self,
+                 model_file,
+                 params_file,
+                 config_file,
+                 runtime_option=None,
+                 model_format=Frontend.PADDLE):
+        super(PPYOLOE, self).__init__(runtime_option)
+
+        assert model_format == Frontend.PADDLE, "PPYOLOv2 model only support model format of Frontend.Paddle now."
+        self._model = C.vision.detection.PPYOLOv2(
+            model_file, params_file, config_file, self._runtime_option,
+            model_format)
+        assert self.initialized, "PPYOLOv2 model initialize failed."
+
+
+class PaddleYOLOX(PPYOLOE):
+    def __init__(self,
+                 model_file,
+                 params_file,
+                 config_file,
+                 runtime_option=None,
+                 model_format=Frontend.PADDLE):
+        super(PPYOLOE, self).__init__(runtime_option)
+
+        assert model_format == Frontend.PADDLE, "PaddleYOLOX model only support model format of Frontend.Paddle now."
+        self._model = C.vision.detection.PaddleYOLOX(
+            model_file, params_file, config_file, self._runtime_option,
+            model_format)
+        assert self.initialized, "PaddleYOLOX model initialize failed."
+
+
+class PicoDet(PPYOLOE):
+    def __init__(self,
+                 model_file,
+                 params_file,
+                 config_file,
+                 runtime_option=None,
+                 model_format=Frontend.PADDLE):
+        super(PPYOLOE, self).__init__(runtime_option)
+
+        assert model_format == Frontend.PADDLE, "PicoDet model only support model format of Frontend.Paddle now."
+        self._model = C.vision.detection.PicoDet(
+            model_file, params_file, config_file, self._runtime_option,
+            model_format)
+        assert self.initialized, "PicoDet model initialize failed."
+
+
+class FasterRCNN(PPYOLOE):
+    def __init__(self,
+                 model_file,
+                 params_file,
+                 config_file,
+                 runtime_option=None,
+                 model_format=Frontend.PADDLE):
+        super(PPYOLOE, self).__init__(runtime_option)
+
+        assert model_format == Frontend.PADDLE, "FasterRCNN model only support model format of Frontend.Paddle now."
+        self._model = C.vision.detection.FasterRCNN(
+            model_file, params_file, config_file, self._runtime_option,
+            model_format)
+        assert self.initialized, "FasterRCNN model initialize failed."
+
+
+class YOLOv3(PPYOLOE):
+    def __init__(self,
+                 model_file,
+                 params_file,
+                 config_file,
+                 runtime_option=None,
+                 model_format=Frontend.PADDLE):
+        super(PPYOLOE, self).__init__(runtime_option)
+
+        assert model_format == Frontend.PADDLE, "YOLOv3 model only support model format of Frontend.Paddle now."
+        self._model = C.vision.detection.YOLOv3(
+            model_file, params_file, config_file, self._runtime_option,
+            model_format)
+        assert self.initialized, "YOLOv3 model initialize failed."
+
+
+class MaskRCNN(FastDeployModel):
+    def __init__(self,
+                 model_file,
+                 params_file,
+                 config_file,
+                 runtime_option=None,
+                 model_format=Frontend.PADDLE):
+        super(MaskRCNN, self).__init__(runtime_option)
+
+        assert model_format == Frontend.PADDLE, "MaskRCNN model only support model format of Frontend.Paddle now."
+        self._model = C.vision.detection.MaskRCNN(
+            model_file, params_file, config_file, self._runtime_option,
+            model_format)
+        assert self.initialized, "MaskRCNN model initialize failed."
+
+    def predict(self, input_image):
+        assert input_image is not None, "The input image data is None."
+        return self._model.predict(input_image)