[Model] add RobustVideoMatting model (#400)

* add yolov5cls

* fixed bugs

* fixed bugs

* fixed preprocess bug

* add yolov5cls readme

* deal with comments

* Add YOLOv5Cls Note

* add yolov5cls test

* add rvm support

* support rvm model

* add rvm demo

* fixed bugs

* add rvm readme

* add TRT support

* add trt support

* add rvm test

* add EXPORT.md

* rename export.md

* rm poros doxyen

* deal with comments

* deal with comments

* add rvm video_mode note

Co-authored-by: Jason <jiangjiajun@baidu.com>
Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>

python/fastdeploy/vision/matting/__init__.py

@@ -14,4 +14,5 @@
 
 from __future__ import absolute_import
 from .contrib.modnet import MODNet
+from .contrib.rvm import RobustVideoMatting
 from .ppmatting import PPMatting

python/fastdeploy/vision/matting/contrib/rvm.py

@@ -0,0 +1,81 @@
+# 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, ModelFormat
+from .... import c_lib_wrap as C
+
+
+class RobustVideoMatting(FastDeployModel):
+    def __init__(self,
+                 model_file,
+                 params_file="",
+                 runtime_option=None,
+                 model_format=ModelFormat.ONNX):
+        """Load a video matting model exported by RobustVideoMatting.
+
+        :param model_file: (str)Path of model file, e.g rvm/rvm_mobilenetv3_fp32.onnx
+        :param params_file: (str)Path of parameters file, if the model_fomat is ModelFormat.ONNX, this param will be ignored, can be set as empty string
+        :param runtime_option: (fastdeploy.RuntimeOption)RuntimeOption for inference this model, if it's None, will use the default backend on CPU
+        :param model_format: (fastdeploy.ModelForamt)Model format of the loaded model, default is ONNX
+        """
+        super(RobustVideoMatting, self).__init__(runtime_option)
+
+        self._model = C.vision.matting.RobustVideoMatting(
+            model_file, params_file, self._runtime_option, model_format)
+        assert self.initialized, "RobustVideoMatting initialize failed."
+
+    def predict(self, input_image):
+        """Matting an input image
+
+        :param im: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
+        :return: MattingResult
+        """
+        return self._model.predict(input_image)
+
+    @property
+    def size(self):
+        """
+        Returns the preprocess image size
+        """
+        return self._model.size
+
+    @property
+    def video_mode(self):
+        """
+        Whether to open the video mode, if there are some irrelevant pictures, set it to fasle, the default is true
+        """
+        return self._model.video_mode
+
+    @size.setter
+    def size(self, wh):
+        """
+        Set the preprocess image size
+        """
+        assert isinstance(wh, (list, tuple)),\
+            "The value to set `size` must be type of tuple or list."
+        assert len(wh) == 2,\
+            "The value to set `size` must contatins 2 elements means [width, height], but now it contains {} elements.".format(
+            len(wh))
+        self._model.size = wh
+
+    @video_mode.setter
+    def video_mode(self, value):
+        """
+        Set video_mode property, the default is true
+        """
+        assert isinstance(
+            value, bool), "The value to set `video_mode` must be type of bool."
+        self._model.video_mode = value