#### TODO: - [x] 超轻量2.0方向分类器模型整理 - [x] 通用2.0文本检测模型整理 - [ ] 通用2.0文本识别模型整理 - [ ] 通用2.0方向分类器模型整理 ### 检测、方向分类和识别模型下载: - [链接](https://pan.baidu.com/s/1qkqWK4wRdMjqGGbzR-FyWg) - 提取码:30jv - 下载之后放在`models`目录即可 ### 文本检测+方向分类+文本识别 - 具体参见[bpocr.py](./bpocr.py) #### 简单示例 ```python det_model_path = 'models/ch_ppocr_mobile_v2_det_train.onnx' cls_model_path = 'models/ch_ppocr_mobile_v2.0_cls_infer.onnx' rec_model_path = 'models/ch_ppocr_mobile_v2.0_rec_pre_infer.onnx' image_path = r'test_images\long1.jpg' text_sys = TextSystem(det_model_path, rec_model_path, use_angle_cls=True, cls_model_path=cls_model_path) dt_boxes, rec_res = text_sys(image_path) visualize(image_path, dt_boxes, rec_res) ``` ### 通用超轻量文本检测模型 ch_ppocr_mobile_v2_det_train - **Note: 支持任意尺寸输入** - 详细见[ch_ppocr_mobile_v2_det/text_detect.py](./ch_ppocr_mobile_v2_det/text_detect.py) #### 简单示例 ```python det_model_path = 'models/ch_ppocr_mobile_v2_det_train.onnx' image_path = r'test_images/det_images/1.jpg' test_detector = TextDetector(det_model_path) img, flag = check_and_read_gif(image_path) if not flag: img = cv2.imread(image_path) if img is None: raise ValueError(f"error in loading image:{image_path}") # dst_boxes: 检测到图像中的文本框坐标,ndarray格式 # (10, 4, 2)→[10个,4个坐标,每个坐标两个点] dt_boxes, elapse = test_detector(img) print(dt_boxes.shape) print(elapse) ``` ### 通用超轻量方向分类器模型 ch_ppocr_mobile_v2_cls - **Note**: 支持`0 180`两个方向分类 - 详细见[ch_ppocr_mobile_v2_cls/text_cls.py](./ch_ppocr_mobile_v2_cls/text_cls.py) #### 简单示例 ```python text_classifier = TextClassifier(args.cls_model_dir) img_list, cls_res, predict_time = text_classifier(args.image_dir) for ino in range(len(img_list)): print(f"分类结果:{cls_res[ino]}") ``` ### 通用超轻量文本识别模型 ch_ppocr_mobile_v2_rec - **Note: 支持任意尺寸输入** - 详细见[ch_ppocr_mobile_v2_rec/text_recognize.py](./ch_ppocr_mobile_v2_rec/text_recognize.py) #### 简单示例: ```python rec_model_path = r'models/ch_ppocr_mobile_v2.0_rec_pre_infer.onnx' image_path = r'test_images/rec_images/2021-01-19_13-44-34.png' text_recongnizer = TextRecognizer(rec_model_path) rec_res, elapse = text_recongnizer(image_path) print(f'识别结果:{rec_res}/tcost: {elapse}s') ``` --- ### 通用超轻量文本检测模型 ch_ppocr_mobile_v1.1_det - **Note: 支持任意尺寸输入** - 详细见[ch_ppocr_mobile_v1_det/text_detect.py](./ch_ppocr_mobile_v1_det/text_detect.py) #### 简单示例 ```python text_detector = TextDetector(args.model_path) img, flag = check_and_read_gif(args.image_path) if not flag: img = cv2.imread(args.image_path) if img is None: raise ValueError(f"error in loading image:{args.image_path}") dt_boxes, elapse = text_detector(img) plot_img = draw_text_det_res(dt_boxes, img) cv2.imwrite('det_results.jpg', plot_img) print('图像已经保存为det_results.jpg了') ```