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https://github.com/PaddlePaddle/FastDeploy.git
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[Doc] Update PaddleSeg comments (#785)
* Update docs for wrong path * Update README.md * Update README.md * Update README.md * Update README.md * Update segmentation_result.md * Update README.md * Update README.md * Update README.md * Update PaddleSeg comments Co-authored-by: Jason <928090362@qq.com>
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# Semantic Segmentation(语义分割)
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# Semantic Segmentation(语义分割)
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## fastdeploy.vision.segmentation.PaddleSegPreprocessor
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```{eval-rst}
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.. autoclass:: fastdeploy.vision.segmentation.PaddleSegPreprocessor
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:members:
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:inherited-members:
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```
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## fastdeploy.vision.segmentation.PaddleSegModel
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## fastdeploy.vision.segmentation.PaddleSegModel
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```{eval-rst}
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```{eval-rst}
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:members:
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:members:
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:inherited-members:
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:inherited-members:
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```
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```
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## fastdeploy.vision.segmentation.PaddleSegPostprocessor
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```{eval-rst}
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.. autoclass:: fastdeploy.vision.segmentation.PaddleSegPostprocessor
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:members:
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:inherited-members:
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```
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@@ -20,7 +20,8 @@
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namespace fastdeploy {
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namespace fastdeploy {
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namespace vision {
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namespace vision {
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namespace segmentation {
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namespace segmentation {
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/*! @brief Postprocessor object for PaddleSeg serials model.
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*/
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class FASTDEPLOY_DECL PaddleSegPostprocessor {
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class FASTDEPLOY_DECL PaddleSegPostprocessor {
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public:
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public:
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/** \brief Create a postprocessor instance for PaddleSeg serials model
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/** \brief Create a postprocessor instance for PaddleSeg serials model
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namespace fastdeploy {
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namespace fastdeploy {
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namespace vision {
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namespace vision {
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namespace segmentation {
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namespace segmentation {
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/*! @brief Preprocessor object for PaddleSeg serials model.
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*/
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class FASTDEPLOY_DECL PaddleSegPreprocessor {
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class FASTDEPLOY_DECL PaddleSegPreprocessor {
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public:
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public:
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/** \brief Create a preprocessor instance for PaddleSeg serials model
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/** \brief Create a preprocessor instance for PaddleSeg serials model
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@@ -50,23 +50,26 @@ class PaddleSegModel(FastDeployModel):
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return self._model.predict(image)
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return self._model.predict(image)
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def batch_predict(self, image_list):
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def batch_predict(self, image_list):
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"""Predict the segmentation results for a batch of input image
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"""Predict the segmentation results for a batch of input images
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:param image_list: (list of numpy.ndarray) The input image list, each element is a 3-D array with layout HWC, BGR format
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:param image_list: (list of numpy.ndarray) The input image list, each element is a 3-D array with layout HWC, BGR format
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:return list of SegmentationResult
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:return: list of SegmentationResult
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"""
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"""
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return self._model.batch_predict(image_list)
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return self._model.batch_predict(image_list)
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@property
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@property
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def preprocessor(self):
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def preprocessor(self):
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"""Get PaddleSegPreprocessor object of the loaded model
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"""Get PaddleSegPreprocessor object of the loaded model
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:return PaddleSegPreprocessor
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:return: PaddleSegPreprocessor
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"""
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"""
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return self._model.preprocessor
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return self._model.preprocessor
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@property
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@property
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def postprocessor(self):
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def postprocessor(self):
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"""Get PaddleSegPostprocessor object of the loaded model
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"""Get PaddleSegPostprocessor object of the loaded model
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:return PaddleSegPostprocessor
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:return: PaddleSegPostprocessor
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"""
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"""
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return self._model.postprocessor
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return self._model.postprocessor
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@@ -74,6 +77,7 @@ class PaddleSegModel(FastDeployModel):
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class PaddleSegPreprocessor:
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class PaddleSegPreprocessor:
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def __init__(self, config_file):
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def __init__(self, config_file):
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"""Create a preprocessor for PaddleSegModel from configuration file
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"""Create a preprocessor for PaddleSegModel from configuration file
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:param config_file: (str)Path of configuration file, e.g ppliteseg/deploy.yaml
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:param config_file: (str)Path of configuration file, e.g ppliteseg/deploy.yaml
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"""
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"""
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self._preprocessor = C.vision.segmentation.PaddleSegPreprocessor(
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self._preprocessor = C.vision.segmentation.PaddleSegPreprocessor(
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def run(self, input_ims):
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def run(self, input_ims):
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"""Preprocess input images for PaddleSegModel
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"""Preprocess input images for PaddleSegModel
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:param: input_ims: (list of numpy.ndarray)The input image
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:param input_ims: (list of numpy.ndarray)The input image
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:return: list of FDTensor
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:return: list of FDTensor
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"""
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"""
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return self._preprocessor.run(input_ims)
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return self._preprocessor.run(input_ims)
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@@ -114,6 +119,7 @@ class PaddleSegPreprocessor:
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class PaddleSegPostprocessor:
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class PaddleSegPostprocessor:
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def __init__(self, config_file):
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def __init__(self, config_file):
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"""Create a postprocessor for PaddleSegModel from configuration file
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"""Create a postprocessor for PaddleSegModel from configuration file
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:param config_file: (str)Path of configuration file, e.g ppliteseg/deploy.yaml
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:param config_file: (str)Path of configuration file, e.g ppliteseg/deploy.yaml
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"""
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"""
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self._postprocessor = C.vision.segmentation.PaddleSegPostprocessor(
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self._postprocessor = C.vision.segmentation.PaddleSegPostprocessor(
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def run(self, runtime_results, imgs_info):
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def run(self, runtime_results, imgs_info):
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"""Postprocess the runtime results for PaddleSegModel
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"""Postprocess the runtime results for PaddleSegModel
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:param: runtime_results: (list of FDTensor)The output FDTensor results from runtime
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:param: imgs_info: The original input images shape info map, key is "shape_info", value is [[image_height, image_width]]
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:param runtime_results: (list of FDTensor)The output FDTensor results from runtime
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:param imgs_info: The original input images shape info map, key is "shape_info", value is [[image_height, image_width]]
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:return: list of SegmentationResult(If the runtime_results is predict by batched samples, the length of this list equals to the batch size)
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:return: list of SegmentationResult(If the runtime_results is predict by batched samples, the length of this list equals to the batch size)
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"""
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"""
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return self._postprocessor.run(runtime_results, imgs_info)
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return self._postprocessor.run(runtime_results, imgs_info)
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