[Model] Support PP-OCRv4 pipeline (#1913)

* 添加paddleclas模型 * 更新README_CN * 更新README_CN * 更新README * update get_model.sh * update get_models.sh * update paddleseg models * update paddle_seg models * update paddle_seg models * modified test resources * update benchmark_gpu_trt.sh * add paddle detection * add paddledetection to benchmark * modified benchmark cmakelists * update benchmark scripts * modified benchmark function calling * modified paddledetection documents * upadte getmodels.sh * add PaddleDetectonModel * reset examples/paddledetection * resolve conflict * update pybind * resolve conflict * fix bug * delete debug mode * update checkarch log * update trt inputs example * Update README.md * add ppocr_v4 * update ppocr_v4 * update ocr_v4 * update ocr_v4 * update ocr_v4 * update ocr_v4 --------- Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
2025-10-07 01:22:59 +08:00 · 2023-05-11 16:09:50 +08:00
parent e75e766b19
commit 643f41e711
10 changed files with 231 additions and 9 deletions
--- a/python/fastdeploy/vision/ocr/ppocr/init.py
+++ b/python/fastdeploy/vision/ocr/ppocr/init.py
@@ -848,6 +848,79 @@ class StructureV2Layout(FastDeployModel):
    def postprocessor(self, value):
        self._model.postprocessor = value

+class PPOCRv4(FastDeployModel):
+    def __init__(self, det_model=None, cls_model=None, rec_model=None):
+        """Consruct a pipeline with text detector, direction classifier and text recognizer models
+
+        :param det_model: (FastDeployModel) The detection model object created by fastdeploy.vision.ocr.DBDetector.
+        :param cls_model: (FastDeployModel) The classification model object created by fastdeploy.vision.ocr.Classifier.
+        :param rec_model: (FastDeployModel) The recognition model object created by fastdeploy.vision.ocr.Recognizer.
+        """
+        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.PPOCRv4(det_model._model,
+                                                rec_model._model)
+        else:
+            self.system_ = C.vision.ocr.PPOCRv4(
+                det_model._model, cls_model._model, rec_model._model)
+
+    def clone(self):
+        """Clone PPOCRv4 pipeline object
+        :return: a new PPOCRv4 pipeline object
+        """
+
+        class PPOCRv4Clone(PPOCRv4):
+            def __init__(self, system):
+                self.system_ = system
+
+        clone_model = PPOCRv4Clone(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)
+
+    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)
+
+    @property
+    def cls_batch_size(self):
+        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
+
+    @property
+    def rec_batch_size(self):
+        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
+
+class PPOCRSystemv4(PPOCRv4):
+    def __init__(self, det_model=None, cls_model=None, rec_model=None):
+        logging.warning(
+            "DEPRECATED: fd.vision.ocr.PPOCRSystemv4 is deprecated, "
+            "please use fd.vision.ocr.PPOCRv4 instead.")
+        super(PPOCRSystemv4, self).__init__(det_model, cls_model, rec_model)
+
+    def predict(self, input_image):
+        return super(PPOCRSystemv4, self).predict(input_image)

 class PPOCRv3(FastDeployModel):
    def __init__(self, det_model=None, cls_model=None, rec_model=None):