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[Other] PPOCR models support model clone function (#1072)

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* Refactor PaddleSeg with preprocessor && postprocessor

* Fix bugs

* Delete redundancy code

* Modify by comments

* Refactor according to comments

* Add batch evaluation

* Add single test script

* Add ppliteseg single test script && fix eval(raise) error

* fix bug

* Fix evaluation segmentation.py batch predict

* Fix segmentation evaluation bug

* Fix evaluation segmentation bugs

* Update segmentation result docs

* Update old predict api and DisableNormalizeAndPermute

* Update resize segmentation label map with cv::INTER_NEAREST

* Add Model Clone function for PaddleClas && PaddleDet && PaddleSeg

* Add multi thread demo

* Add python model clone function

* Add multi thread python && C++ example

* Fix bug

* Update python && cpp multi_thread examples

* Add cpp && python directory

* Add README.md for examples

* Delete redundant code

* Create README_CN.md

* Rename README_CN.md to README.md

* Update README.md

* Update README.md

* Update VERSION_NUMBER

* Update requirements.txt

* Update README.md

* update version in doc:

* [Serving]Update Dockerfile (#1037)

Update Dockerfile

* Add license notice for RVM onnx model file (#1060)

* [Model] Add GPL-3.0 license (#1065)

Add GPL-3.0 license

* PPOCR model support model clone

* Update README.md

* Update PPOCRv2 && PPOCRv3 clone code

* Update PPOCR python __init__

* Add multi thread ocr example code

* Update README.md

* Update README.md

* Update ResNet50_vd_infer multi process code

* Add PPOCR multi process && thread example

* Update README.md

* Update README.md

* Update multi-thread docs

Co-authored-by: Jason <jiangjiajun@baidu.com>
Co-authored-by: leiqing <54695910+leiqing1@users.noreply.github.com>
Co-authored-by: heliqi <1101791222@qq.com>
Co-authored-by: WJJ1995 <wjjisloser@163.com>
This commit is contained in:
huangjianhui
2023-01-17 15:16:41 +08:00
committed by GitHub
parent abba2afd74
commit 6c4a08e416
28 changed files with 1201 additions and 96 deletions
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87
python/fastdeploy/vision/ocr/ppocr/__init__.py
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@@ -170,6 +170,17 @@ class DBDetector(FastDeployModel):
assert self.initialized, "DBDetector initialize failed."
self._runnable = True
def clone(self):
"""Clone OCR detection model object
:return: a new OCR detection model object
"""
class DBDetectorClone(DBDetector):
def __init__(self, model):
self._model = model
clone_model = DBDetectorClone(self._model.clone())
return clone_model
def predict(self, input_image):
"""Predict an input image
:param input_image: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
@@ -406,6 +417,17 @@ class Classifier(FastDeployModel):
assert self.initialized, "Classifier initialize failed."
self._runnable = True
def clone(self):
"""Clone OCR classification model object
:return: a new OCR classification model object
"""
class ClassifierClone(Classifier):
def __init__(self, model):
self._model = model
clone_model = ClassifierClone(self._model.clone())
return clone_model
def predict(self, input_image):
"""Predict an input image
:param input_image: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
@@ -603,6 +625,17 @@ class Recognizer(FastDeployModel):
assert self.initialized, "Recognizer initialize failed."
self._runnable = True
def clone(self):
"""Clone OCR recognition model object
:return: a new OCR recognition model object
"""
class RecognizerClone(Recognizer):
def __init__(self, model):
self._model = model
clone_model = RecognizerClone(self._model.clone())
return clone_model
def predict(self, input_image):
"""Predict an input image
:param input_image: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
@@ -700,47 +733,58 @@ class PPOCRv3(FastDeployModel):
"""
assert det_model is not None and rec_model is not None, "The det_model and rec_model cannot be None."
if cls_model is None:
self.system = C.vision.ocr.PPOCRv3(det_model._model,
self.system_ = C.vision.ocr.PPOCRv3(det_model._model,
rec_model._model)
else:
self.system = C.vision.ocr.PPOCRv3(
self.system_ = C.vision.ocr.PPOCRv3(
det_model._model, cls_model._model, rec_model._model)
def clone(self):
"""Clone PPOCRv3 pipeline object
:return: a new PPOCRv3 pipeline object
"""
class PPOCRv3Clone(PPOCRv3):
def __init__(self, system):
self.system_ = system
clone_model = PPOCRv3Clone(self.system_.clone())
return clone_model
def predict(self, input_image):
"""Predict an input image
:param input_image: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
:return: OCRResult
"""
return self.system.predict(input_image)
return self.system_.predict(input_image)
def batch_predict(self, images):
"""Predict a batch of input image
:param images: (list of numpy.ndarray) The input image list, each element is a 3-D array with layout HWC, BGR format
:return: OCRBatchResult
"""
return self.system.batch_predict(images)
return self.system_.batch_predict(images)
@property
def cls_batch_size(self):
return self.system.cls_batch_size
return self.system_.cls_batch_size
@cls_batch_size.setter
def cls_batch_size(self, value):
assert isinstance(
value,
int), "The value to set `cls_batch_size` must be type of int."
self.system.cls_batch_size = value
self.system_.cls_batch_size = value
@property
def rec_batch_size(self):
return self.system.rec_batch_size
return self.system_.rec_batch_size
@rec_batch_size.setter
def rec_batch_size(self, value):
assert isinstance(
value,
int), "The value to set `rec_batch_size` must be type of int."
self.system.rec_batch_size = value
self.system_.rec_batch_size = value
class PPOCRSystemv3(PPOCRv3):
@@ -764,19 +808,30 @@ class PPOCRv2(FastDeployModel):
"""
assert det_model is not None and rec_model is not None, "The det_model and rec_model cannot be None."
if cls_model is None:
self.system = C.vision.ocr.PPOCRv2(det_model._model,
self.system_ = C.vision.ocr.PPOCRv2(det_model._model,
rec_model._model)
else:
self.system = C.vision.ocr.PPOCRv2(
self.system_ = C.vision.ocr.PPOCRv2(
det_model._model, cls_model._model, rec_model._model)
def clone(self):
"""Clone PPOCRv3 pipeline object
:return: a new PPOCRv3 pipeline object
"""
class PPOCRv2Clone(PPOCRv2):
def __init__(self, system):
self.system_ = system
clone_model = PPOCRv2Clone(self.system_.clone())
return clone_model
def predict(self, input_image):
"""Predict an input image
:param input_image: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
:return: OCRResult
"""
return self.system.predict(input_image)
return self.system_.predict(input_image)
def batch_predict(self, images):
"""Predict a batch of input image
@@ -784,29 +839,29 @@ class PPOCRv2(FastDeployModel):
:return: OCRBatchResult
"""
return self.system.batch_predict(images)
return self.system_.batch_predict(images)
@property
def cls_batch_size(self):
return self.system.cls_batch_size
return self.system_.cls_batch_size
@cls_batch_size.setter
def cls_batch_size(self, value):
assert isinstance(
value,
int), "The value to set `cls_batch_size` must be type of int."
self.system.cls_batch_size = value
self.system_.cls_batch_size = value
@property
def rec_batch_size(self):
return self.system.rec_batch_size
return self.system_.rec_batch_size
@rec_batch_size.setter
def rec_batch_size(self, value):
assert isinstance(
value,
int), "The value to set `rec_batch_size` must be type of int."
self.system.rec_batch_size = value
self.system_.rec_batch_size = value
class PPOCRSystemv2(PPOCRv2):