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update python/README
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@@ -1,3 +1,6 @@
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### 2021-06-09 update:
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- 添加字体文件到模型下载链接中
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### 2021-05-22 update:
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- 添加日文识别推理代码和相应模型,详情见`japan_ppocr_mobile_v2_rec`目录
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- 整理代码,去除无效代码
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@@ -6,15 +9,20 @@
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### 2021-03-24 update:
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- 更改文本识别模型支持ort1.7,推理速度有着较大提升
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### 检测、方向分类和识别模型下载:
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- [链接](https://pan.baidu.com/s/1qkqWK4wRdMjqGGbzR-FyWg)
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- 提取码:30jv
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- 下载之后放在`models`目录即可
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---
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### 运行
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1. 下载相应模型和用于显示的字体文件
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- [提取码:30jv](https://pan.baidu.com/s/1qkqWK4wRdMjqGGbzR-FyWg)
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- 下载之后放在`models`目录即可
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2. 运行`rapidOCR.py`文件, 即可
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```shell
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cd python
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python rapidOCR.py
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```
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### 文本检测+方向分类+文本识别
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- 具体参见[rapidOCR.py](./rapidOCR.py)
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#### 简单示例
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```python
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from ch_ppocr_mobile_v2_cls import TextClassifier
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from ch_ppocr_mobile_v2_det import TextDetector
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@@ -33,58 +41,3 @@ text_sys = TextSystem(det_model_path,
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dt_boxes, rec_res = text_sys(image_path)
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visualize(image_path, dt_boxes, rec_res)
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```
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### 通用超轻量文本检测模型 ch_ppocr_mobile_v2_det_train
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- **Note: 支持任意尺寸输入**
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- **server版文本检测只是采用了ResNet18作为backbone,其他与超轻量无区别**
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- 详细见[ch_ppocr_mobile_v2_det/text_detect.py](./ch_ppocr_mobile_v2_det/text_detect.py)
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#### 简单示例
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```python
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det_model_path = 'models/ch_ppocr_mobile_v2_det_train.onnx'
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image_path = r'test_images/det_images/1.jpg'
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test_detector = TextDetector(det_model_path)
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img, flag = check_and_read_gif(image_path)
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if not flag:
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img = cv2.imread(image_path)
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if img is None:
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raise ValueError(f"error in loading image:{image_path}")
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# dst_boxes: 检测到图像中的文本框坐标,ndarray格式
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# (10, 4, 2)→[10个,4个坐标,每个坐标两个点]
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dt_boxes, elapse = test_detector(img)
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print(dt_boxes.shape)
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print(elapse)
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```
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### 通用超轻量方向分类器模型 ch_ppocr_mobile_v2_cls
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- **Note**: 支持`0 180`两个方向分类
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- 详细见[ch_ppocr_mobile_v2_cls/text_cls.py](./ch_ppocr_mobile_v2_cls/text_cls.py)
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#### 简单示例
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```python
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text_classifier = TextClassifier(args.cls_model_dir)
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img_list, cls_res, predict_time = text_classifier(args.image_dir)
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for ino in range(len(img_list)):
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print(f"分类结果:{cls_res[ino]}")
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```
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### 通用超轻量文本识别模型 ch_ppocr_mobile_v2_rec
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- **Note: 支持任意尺寸输入**
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- 详细见[ch_ppocr_mobile_v2_rec/text_recognize.py](./ch_ppocr_mobile_v2_rec/text_recognize.py)
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#### 简单示例:
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```python
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rec_model_path = r'models/ch_ppocr_mobile_v2.0_rec_pre_infer.onnx'
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image_path = r'test_images/rec_images/2021-01-19_13-44-34.png'
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text_recongnizer = TextRecognizer(rec_model_path)
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rec_res, elapse = text_recongnizer(image_path)
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print(f'识别结果:{rec_res}/tcost: {elapse}s')
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```
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+1
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@@ -33,7 +33,7 @@ def check_and_read_gif(img_path):
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def draw_ocr_box_txt(image, boxes, txts,
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scores=None, drop_score=0.5,
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font_path="./doc/simfang.ttf"):
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font_path="./models/msyh.ttc"):
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h, w = image.height, image.width
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img_left = image.copy()
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img_right = Image.new('RGB', (w, h), (255, 255, 255))
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