--- comments: true hide: - navigation --- ### Install ```bash linenums="1" pip install paddleocr ``` ### Use === "Detection + Classification + Recognition" ```python linenums="1" from paddleocr import PaddleOCR, draw_ocr # Paddleocr supports Chinese, English, French, German, Korean and Japanese # You can set the parameter `lang` as `ch`, `en`, `french`, `german`, `korean`, `japan` # to switch the language model in order ocr = PaddleOCR(use_angle_cls=True, lang='en') # need to run only once to download and load model into memory img_path = 'PaddleOCR/doc/imgs_en/img_12.jpg' result = ocr.ocr(img_path, cls=True) for idx in range(len(result)): res = result[idx] for line in res: print(line) # draw result from PIL import Image result = result[0] image = Image.open(img_path).convert('RGB') boxes = [line[0] for line in result] txts = [line[1][0] for line in result] scores = [line[1][1] for line in result] im_show = draw_ocr(image, boxes, txts, scores, font_path='/path/to/PaddleOCR/doc/fonts/simfang.ttf') im_show = Image.fromarray(im_show) im_show.save('result.jpg') ``` Output will be a list, each item contains bounding box, text and recognition confidence： ```python linenums="1" [[[442.0, 173.0], [1169.0, 173.0], [1169.0, 225.0], [442.0, 225.0]], ['ACKNOWLEDGEMENTS', 0.99283075]] [[[393.0, 340.0], [1207.0, 342.0], [1207.0, 389.0], [393.0, 387.0]], ['We would like to thank all the designers and', 0.9357758]] [[[399.0, 398.0], [1204.0, 398.0], [1204.0, 433.0], [399.0, 433.0]], ['contributors whohave been involved in the', 0.9592447]] ...... ``` === "Detection + Recognition" ```python linenums="1" from paddleocr import PaddleOCR,draw_ocr ocr = PaddleOCR(lang='en') # need to run only once to download and load model into memory img_path = 'PaddleOCR/doc/imgs_en/img_12.jpg' result = ocr.ocr(img_path, cls=False) for idx in range(len(result)): res = result[idx] for line in res: print(line) # draw result from PIL import Image result = result[0] image = Image.open(img_path).convert('RGB') boxes = [line[0] for line in result] txts = [line[1][0] for line in result] scores = [line[1][1] for line in result] im_show = draw_ocr(image, boxes, txts, scores, font_path='/path/to/PaddleOCR/doc/fonts/simfang.ttf') im_show = Image.fromarray(im_show) im_show.save('result.jpg') ``` Output will be a list, each item contains bounding box, text and recognition confidence： ```python linenums="1" [[[442.0, 173.0], [1169.0, 173.0], [1169.0, 225.0], [442.0, 225.0]], ['ACKNOWLEDGEMENTS', 0.99283075]] [[[393.0, 340.0], [1207.0, 342.0], [1207.0, 389.0], [393.0, 387.0]], ['We would like to thank all the designers and', 0.9357758]] [[[399.0, 398.0], [1204.0, 398.0], [1204.0, 433.0], [399.0, 433.0]], ['contributors whohave been involved in the', 0.9592447]] ...... ``` === "Classification + Recognition" ```python linenums="1" from paddleocr import PaddleOCR ocr = PaddleOCR(use_angle_cls=True, lang='en') # need to run only once to load model into memory img_path = 'PaddleOCR/doc/imgs_words_en/word_10.png' result = ocr.ocr(img_path, det=False, cls=True) for idx in range(len(result)): res = result[idx] for line in res: print(line) ``` Output will be a list, each item contains recognition text and confidence: ```python linenums="1" ['PAIN', 0.990372] ``` === "Only detection" ```python linenums="1" from paddleocr import PaddleOCR,draw_ocr ocr = PaddleOCR() # need to run only once to download and load model into memory img_path = 'PaddleOCR/doc/imgs_en/img_12.jpg' result = ocr.ocr(img_path,rec=False) for idx in range(len(result)): res = result[idx] for line in res: print(line) # draw result from PIL import Image result = result[0] image = Image.open(img_path).convert('RGB') im_show = draw_ocr(image, result, txts=None, scores=None, font_path='/path/to/PaddleOCR/doc/fonts/simfang.ttf') im_show = Image.fromarray(im_show) im_show.save('result.jpg') ``` Output will be a list, each item only contains bounding box: ```python linenums="1" [[756.0, 812.0], [805.0, 812.0], [805.0, 830.0], [756.0, 830.0]] [[820.0, 803.0], [1085.0, 801.0], [1085.0, 836.0], [820.0, 838.0]] [[393.0, 801.0], [715.0, 805.0], [715.0, 839.0], [393.0, 836.0]] ...... ``` === "Only recognition" ```python linenums="1" from paddleocr import PaddleOCR ocr = PaddleOCR(lang='en') # need to run only once to load model into memory img_path = 'PaddleOCR/doc/imgs_words_en/word_10.png' result = ocr.ocr(img_path, det=False, cls=False) for idx in range(len(result)): res = result[idx] for line in res: print(line) ``` Output will be a list, each item contains recognition text and confidence： ```python linenums="1" ['PAIN', 0.990372] ``` === "Only classification" ```python linenums="1" from paddleocr import PaddleOCR ocr = PaddleOCR(use_angle_cls=True) # need to run only once to load model into memory img_path = 'PaddleOCR/doc/imgs_words_en/word_10.png' result = ocr.ocr(img_path, det=False, rec=False, cls=True) for idx in range(len(result)): res = result[idx] for line in res: print(line) ``` Output will be a list, each item contains classification result and confidence ```python linenums="1" ['0', 0.99999964] ``` ### Online Demo - PP-OCRv4 online experience： - SLANet online experience： - PP-ChatOCRv3-doc online experience： - PP-ChatOCRv2-common online experience： - PP-ChatOCRv2-doc online experience： ### Other resources - [One-Click Call for 17 Core PaddleOCR Models](https://paddlepaddle.github.io/PaddleOCR/latest/en/paddlex/quick_start.html) - One line of code quick use: [Text Detection and Recognition (Chinese/English/Multilingual)](https://paddlepaddle.github.io/PaddleOCR/latest/en/ppocr/overview.html) - One line of code quick use: [Document Analysis](https://paddlepaddle.github.io/PaddleOCR/latest/en/ppstructure/overview.html)