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[CVCUDA] PP-OCR detector preprocessor integrate CV-CUDA (#1382)

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* move manager initialized_ flag to ppcls

* update dbdetector preprocess api

* declare processor op

* ppocr detector preprocessor support cvcuda

* move cvcuda op to class member

* ppcls use manager register api

* refactor det preprocessor init api

* add set preprocessor api

* add create processor macro

* new processor call api

* ppcls preprocessor init resize on cpu

* ppocr detector preprocessor set normalize api

* revert ppcls pybind

* remove dbdetector set preprocessor

* refine dbdetector preprocessor includes

* remove mean std in py constructor

* add comments

* update comment

* Update __init__.py
This commit is contained in:
Wang Xinyu
2023-02-22 19:39:11 +08:00
committed by GitHub
parent 2f8d9c9a57
commit 91a1c72f98
24 changed files with 448 additions and 330 deletions
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1
python/fastdeploy/vision/classification/ppcls/__init__.py
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@@ -46,7 +46,6 @@ class PaddleClasPreprocessor(ProcessorManager):
When the initial operator is Resize, and input image size is large,
maybe it's better to run resize on CPU, because the HostToDevice memcpy
is time consuming. Set this True to run the initial resize on CPU.
:param: v: True or False
"""
self._manager.initial_resize_on_cpu(v)

93
python/fastdeploy/vision/ocr/ppocr/__init__.py
View File

@@ -37,43 +37,31 @@ class DBDetectorPreprocessor:
@property
def max_side_len(self):
"""Get max_side_len value.
"""
return self._preprocessor.max_side_len
@max_side_len.setter
def max_side_len(self, value):
"""Set max_side_len value.
:param: value: (int) max_side_len value
"""
assert isinstance(
value, int), "The value to set `max_side_len` must be type of int."
self._preprocessor.max_side_len = value
@property
def is_scale(self):
return self._preprocessor.is_scale
@is_scale.setter
def is_scale(self, value):
assert isinstance(
value, bool), "The value to set `is_scale` must be type of bool."
self._preprocessor.is_scale = value
@property
def scale(self):
return self._preprocessor.scale
@scale.setter
def scale(self, value):
assert isinstance(
value, list), "The value to set `scale` must be type of list."
self._preprocessor.scale = value
@property
def mean(self):
return self._preprocessor.mean
@mean.setter
def mean(self, value):
assert isinstance(
value, list), "The value to set `mean` must be type of list."
self._preprocessor.mean = value
def set_normalize(self,
mean=[0.485, 0.456, 0.406],
std=[0.229, 0.224, 0.225],
is_scale=True):
"""Set preprocess normalize parameters, please call this API to
customize the normalize parameters, otherwise it will use the default
normalize parameters.
:param: mean: (list of float) mean values
:param: std: (list of float) std values
:param: is_scale: (boolean) whether to scale
"""
self._preprocessor.set_normalize(mean, std, is_scale)
class DBDetectorPostprocessor:
@@ -174,6 +162,7 @@ class DBDetector(FastDeployModel):
"""Clone OCR detection model object
:return: a new OCR detection model object
"""
class DBDetectorClone(DBDetector):
def __init__(self, model):
self._model = model
@@ -203,18 +192,10 @@ class DBDetector(FastDeployModel):
def preprocessor(self):
return self._model.preprocessor
@preprocessor.setter
def preprocessor(self, value):
self._model.preprocessor = value
@property
def postprocessor(self):
return self._model.postprocessor
@postprocessor.setter
def postprocessor(self, value):
self._model.postprocessor = value
# Det Preprocessor Property
@property
def max_side_len(self):
@@ -226,36 +207,6 @@ class DBDetector(FastDeployModel):
value, int), "The value to set `max_side_len` must be type of int."
self._model.preprocessor.max_side_len = value
@property
def is_scale(self):
return self._model.preprocessor.is_scale
@is_scale.setter
def is_scale(self, value):
assert isinstance(
value, bool), "The value to set `is_scale` must be type of bool."
self._model.preprocessor.is_scale = value
@property
def scale(self):
return self._model.preprocessor.scale
@scale.setter
def scale(self, value):
assert isinstance(
value, list), "The value to set `scale` must be type of list."
self._model.preprocessor.scale = value
@property
def mean(self):
return self._model.preprocessor.mean
@mean.setter
def mean(self, value):
assert isinstance(
value, list), "The value to set `mean` must be type of list."
self._model.preprocessor.mean = value
# Det Ppstprocessor Property
@property
def det_db_thresh(self):
@@ -421,6 +372,7 @@ class Classifier(FastDeployModel):
"""Clone OCR classification model object
:return: a new OCR classification model object
"""
class ClassifierClone(Classifier):
def __init__(self, model):
self._model = model
@@ -629,6 +581,7 @@ class Recognizer(FastDeployModel):
"""Clone OCR recognition model object
:return: a new OCR recognition model object
"""
class RecognizerClone(Recognizer):
def __init__(self, model):
self._model = model
@@ -734,7 +687,7 @@ 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,
rec_model._model)
rec_model._model)
else:
self.system_ = C.vision.ocr.PPOCRv3(
det_model._model, cls_model._model, rec_model._model)
@@ -743,6 +696,7 @@ class PPOCRv3(FastDeployModel):
"""Clone PPOCRv3 pipeline object
:return: a new PPOCRv3 pipeline object
"""
class PPOCRv3Clone(PPOCRv3):
def __init__(self, system):
self.system_ = system
@@ -809,7 +763,7 @@ 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,
rec_model._model)
rec_model._model)
else:
self.system_ = C.vision.ocr.PPOCRv2(
det_model._model, cls_model._model, rec_model._model)
@@ -818,6 +772,7 @@ class PPOCRv2(FastDeployModel):
"""Clone PPOCRv3 pipeline object
:return: a new PPOCRv3 pipeline object
"""
class PPOCRv2Clone(PPOCRv2):
def __init__(self, system):
self.system_ = system