paddle ocr v4 2.6.1实战笔记

效果图：

安装

模型权重是自动下载，如果提前下载会报错。

识别orc，并opencv可视化结果，支持中文可视化

官方原版预测可视化：

效果图：

安装

安装2.5.2识别结果为空

pip install paddlepaddle-gpu==2.6.1

模型权重是自动下载，如果提前下载会报错。

测试代码：


import os
import time
from paddleocr import PaddleOCRfilepath = r"weights/123.jpg"ocr_model = PaddleOCR(use_angle_cls=True, lang="ch", use_gpu=True, show_log=1,det_db_box_thresh=0.1, use_dilation=True,det_model_dir='weight/ch_PP-OCRv4_det_server_infer.tar',cls_model_dir='weight/ch_ppocr_mobile_v2.0_cls_infer.tar',rec_model_dir='weight/ch_PP-OCRv4_rec_server_infer.tar')t1 = time.time()
for i in range(1):result = ocr_model.ocr(img=filepath, det=True, rec=True, cls=True)[0]
t2 = time.time()
print((t2-t1) / 10)for res_str in result:print(res_str)

识别orc，并opencv可视化结果，支持中文可视化

import codecs
import os
import timeimport cv2
import numpy as np
from PIL import ImageFont
from PIL import Image
from PIL import ImageDrawfrom paddleocr import PaddleOCRfilepath = r"weights/124.jpg"ocr_model = PaddleOCR(use_angle_cls=True, lang="ch", use_gpu=True, show_log=1,det_db_box_thresh=0.1, use_dilation=True,det_model_dir='weight/ch_PP-OCRv4_det_server_infer.tar',cls_model_dir='weight/ch_ppocr_mobile_v2.0_cls_infer.tar',rec_model_dir='weight/ch_PP-OCRv4_rec_server_infer.tar')t1 = time.time()
for i in range(1):result = ocr_model.ocr(img=filepath, det=True, rec=True, cls=True)[0]
t2 = time.time()
print((t2-t1) / 10)font_path = 'simhei.ttf'  # 需要替换为你的中文字体路径
font = ImageFont.truetype(font_path, 24)
def cv2AddChineseText(img, text, position, textColor=(0, 255, 0), textSize=30):img = Image.fromarray(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))draw = ImageDraw.Draw(img)draw.text(position, text, textColor, font=font)return cv2.cvtColor(np.asarray(img), cv2.COLOR_RGB2BGR)image=cv2.imread(filepath)ocr_index=0
for res_str in result:if res_str[0][0][0]>36 and res_str[0][2][0]<84:print(ocr_index,res_str)points=res_str[0]text = res_str[1][0]points = np.array(points, dtype=np.int32).reshape((-1, 1, 2))cv2.polylines(image, [points], isClosed=True, color=(255, 0, 0), thickness=2)text_position = (int(points[0][0][0]), int(points[0][0][1] + 20))  # 微调文本位置# cv2.putText(image, '中文文本', (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 2, (255, 255, 255), 3)image= cv2AddChineseText(image, text, text_position, textColor=(0, 255, 0), textSize=30)print(ocr_index)if res_str[0][0][0]>346 and res_str[0][2][0]<391:print(ocr_index,res_str)points=res_str[0]text = res_str[1][0]points = np.array(points, dtype=np.int32).reshape((-1, 1, 2))cv2.polylines(image, [points], isClosed=True, color=(255, 0, 0), thickness=2)text_position = (int(points[0][0][0]), int(points[0][0][1] + 20))  # 微调文本位置# cv2.putText(image, '中文文本', (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 2, (255, 255, 255), 3)image= cv2AddChineseText(image, text, text_position, textColor=(0, 255, 0), textSize=30)if res_str[0][0][0]>658 and res_str[0][2][0]<705:print(ocr_index,res_str)points=res_str[0]text=res_str[1][0]points=np.array(points,dtype=np.int32).reshape((-1, 1, 2))cv2.polylines(image, [points], isClosed=True, color=(255, 0, 0), thickness=2)text_position = (int(points[0][0][0]), int(points[0][0][1] + 20))  # 微调文本位置image= cv2AddChineseText(image, text, text_position, textColor=(0, 255, 0), textSize=30)cv2.imshow('Image with Rectangle and Text', image)
cv2.waitKey(0)

官方原版预测可视化：

# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.import os
import sys
import importlib__dir__ = os.path.dirname(__file__)import paddle
from paddle.utils import try_importsys.path.append(os.path.join(__dir__, ""))import cv2
import logging
import numpy as np
from pathlib import Path
import base64
from io import BytesIO
from PIL import Image, ImageFont, ImageDraw
from tools.infer import predict_systemdef _import_file(module_name, file_path, make_importable=False):spec = importlib.util.spec_from_file_location(module_name, file_path)module = importlib.util.module_from_spec(spec)spec.loader.exec_module(module)if make_importable:sys.modules[module_name] = modulereturn moduletools = _import_file("tools", os.path.join(__dir__, "tools/__init__.py"), make_importable=True)
ppocr = importlib.import_module("ppocr", "paddleocr")
ppstructure = importlib.import_module("ppstructure", "paddleocr")
from ppocr.utils.logging import get_loggerlogger = get_logger()
from ppocr.utils.utility import (check_and_read, get_image_file_list, alpha_to_color, binarize_img, )
from ppocr.utils.network import (maybe_download, download_with_progressbar, is_link, confirm_model_dir_url, )
from tools.infer.utility import draw_ocr, str2bool, check_gpu
from ppstructure.utility import init_args, draw_structure_result
from ppstructure.predict_system import StructureSystem, save_structure_res, to_excellogger = get_logger()
__all__ = ["PaddleOCR", "PPStructure", "draw_ocr", "draw_structure_result", "save_structure_res", "download_with_progressbar", "to_excel", ]SUPPORT_DET_MODEL = ["DB"]
VERSION = "2.8.0"
SUPPORT_REC_MODEL = ["CRNN", "SVTR_LCNet"]
BASE_DIR = os.path.expanduser("~/.paddleocr/")DEFAULT_OCR_MODEL_VERSION = "PP-OCRv4"
SUPPORT_OCR_MODEL_VERSION = ["PP-OCR", "PP-OCRv2", "PP-OCRv3", "PP-OCRv4"]
DEFAULT_STRUCTURE_MODEL_VERSION = "PP-StructureV2"
SUPPORT_STRUCTURE_MODEL_VERSION = ["PP-Structure", "PP-StructureV2"]
MODEL_URLS = {"OCR": {"PP-OCRv4": {"det": {"ch": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv4/chinese/ch_PP-OCRv4_det_infer.tar", }, "en": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_infer.tar", },"ml": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/Multilingual_PP-OCRv3_det_infer.tar"}, },"rec": {"ch": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv4/chinese/ch_PP-OCRv4_rec_infer.tar", "dict_path": "./ppocr/utils/ppocr_keys_v1.txt", }, "en": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv4/english/en_PP-OCRv4_rec_infer.tar", "dict_path": "./ppocr/utils/en_dict.txt", },"korean": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv4/multilingual/korean_PP-OCRv4_rec_infer.tar", "dict_path": "./ppocr/utils/dict/korean_dict.txt", },"japan": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv4/multilingual/japan_PP-OCRv4_rec_infer.tar", "dict_path": "./ppocr/utils/dict/japan_dict.txt", },"chinese_cht": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/chinese_cht_PP-OCRv3_rec_infer.tar", "dict_path": "./ppocr/utils/dict/chinese_cht_dict.txt", },"ta": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv4/multilingual/ta_PP-OCRv4_rec_infer.tar", "dict_path": "./ppocr/utils/dict/ta_dict.txt", },"te": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv4/multilingual/te_PP-OCRv4_rec_infer.tar", "dict_path": "./ppocr/utils/dict/te_dict.txt", },"ka": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv4/multilingual/ka_PP-OCRv4_rec_infer.tar", "dict_path": "./ppocr/utils/dict/ka_dict.txt", },"latin": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/latin_PP-OCRv3_rec_infer.tar", "dict_path": "./ppocr/utils/dict/latin_dict.txt", },"arabic": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv4/multilingual/arabic_PP-OCRv4_rec_infer.tar", "dict_path": "./ppocr/utils/dict/arabic_dict.txt", },"cyrillic": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/cyrillic_PP-OCRv3_rec_infer.tar", "dict_path": "./ppocr/utils/dict/cyrillic_dict.txt", },"devanagari": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv4/multilingual/devanagari_PP-OCRv4_rec_infer.tar", "dict_path": "./ppocr/utils/dict/devanagari_dict.txt", }, }, "cls": {"ch": {"url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar", }}, },"PP-OCRv3": {"det": {"ch": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar", }, "en": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_infer.tar", },"ml": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/Multilingual_PP-OCRv3_det_infer.tar"}, },"rec": {"ch": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar", "dict_path": "./ppocr/utils/ppocr_keys_v1.txt", }, "en": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_infer.tar", "dict_path": "./ppocr/utils/en_dict.txt", },"korean": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/korean_PP-OCRv3_rec_infer.tar", "dict_path": "./ppocr/utils/dict/korean_dict.txt", },"japan": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/japan_PP-OCRv3_rec_infer.tar", "dict_path": "./ppocr/utils/dict/japan_dict.txt", },"chinese_cht": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/chinese_cht_PP-OCRv3_rec_infer.tar", "dict_path": "./ppocr/utils/dict/chinese_cht_dict.txt", },"ta": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/ta_PP-OCRv3_rec_infer.tar", "dict_path": "./ppocr/utils/dict/ta_dict.txt", },"te": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/te_PP-OCRv3_rec_infer.tar", "dict_path": "./ppocr/utils/dict/te_dict.txt", },"ka": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/ka_PP-OCRv3_rec_infer.tar", "dict_path": "./ppocr/utils/dict/ka_dict.txt", },"latin": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/latin_PP-OCRv3_rec_infer.tar", "dict_path": "./ppocr/utils/dict/latin_dict.txt", },"arabic": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/arabic_PP-OCRv3_rec_infer.tar", "dict_path": "./ppocr/utils/dict/arabic_dict.txt", },"cyrillic": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/cyrillic_PP-OCRv3_rec_infer.tar", "dict_path": "./ppocr/utils/dict/cyrillic_dict.txt", },"devanagari": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/devanagari_PP-OCRv3_rec_infer.tar", "dict_path": "./ppocr/utils/dict/devanagari_dict.txt", }, }, "cls": {"ch": {"url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar", }}, },"PP-OCRv2": {"det": {"ch": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_infer.tar", }, }, "rec": {"ch": {"url": "https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_infer.tar", "dict_path": "./ppocr/utils/ppocr_keys_v1.txt", }},"cls": {"ch": {"url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar", }}, }, "PP-OCR": {"det": {"ch": {"url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar", }, "en": {"url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/en_ppocr_mobile_v2.0_det_infer.tar", },"structure": {"url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_det_infer.tar"}, }, "rec": {"ch": {"url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar", "dict_path": "./ppocr/utils/ppocr_keys_v1.txt", },"en": {"url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/en_number_mobile_v2.0_rec_infer.tar", "dict_path": "./ppocr/utils/en_dict.txt", },"french": {"url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/french_mobile_v2.0_rec_infer.tar", "dict_path": "./ppocr/utils/dict/french_dict.txt", },"german": {"url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/german_mobile_v2.0_rec_infer.tar", "dict_path": "./ppocr/utils/dict/german_dict.txt", },"korean": {"url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/korean_mobile_v2.0_rec_infer.tar", "dict_path": "./ppocr/utils/dict/korean_dict.txt", },"japan": {"url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/japan_mobile_v2.0_rec_infer.tar", "dict_path": "./ppocr/utils/dict/japan_dict.txt", },"chinese_cht": {"url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/chinese_cht_mobile_v2.0_rec_infer.tar", "dict_path": "./ppocr/utils/dict/chinese_cht_dict.txt", },"ta": {"url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ta_mobile_v2.0_rec_infer.tar", "dict_path": "./ppocr/utils/dict/ta_dict.txt", },"te": {"url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/te_mobile_v2.0_rec_infer.tar", "dict_path": "./ppocr/utils/dict/te_dict.txt", },"ka": {"url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ka_mobile_v2.0_rec_infer.tar", "dict_path": "./ppocr/utils/dict/ka_dict.txt", },"latin": {"url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/latin_ppocr_mobile_v2.0_rec_infer.tar", "dict_path": "./ppocr/utils/dict/latin_dict.txt", },"arabic": {"url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/arabic_ppocr_mobile_v2.0_rec_infer.tar", "dict_path": "./ppocr/utils/dict/arabic_dict.txt", },"cyrillic": {"url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/cyrillic_ppocr_mobile_v2.0_rec_infer.tar", "dict_path": "./ppocr/utils/dict/cyrillic_dict.txt", },"devanagari": {"url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/devanagari_ppocr_mobile_v2.0_rec_infer.tar", "dict_path": "./ppocr/utils/dict/devanagari_dict.txt", },"structure": {"url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_rec_infer.tar", "dict_path": "ppocr/utils/dict/table_dict.txt", }, }, "cls": {"ch": {"url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar", }}, }, },"STRUCTURE": {"PP-Structure": {"table": {"en": {"url": "https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_structure_infer.tar", "dict_path": "ppocr/utils/dict/table_structure_dict.txt", }}}, "PP-StructureV2": {"table": {"en": {"url": "https://paddleocr.bj.bcebos.com/ppstructure/models/slanet/en_ppstructure_mobile_v2.0_SLANet_infer.tar", "dict_path": "ppocr/utils/dict/table_structure_dict.txt", },"ch": {"url": "https://paddleocr.bj.bcebos.com/ppstructure/models/slanet/ch_ppstructure_mobile_v2.0_SLANet_infer.tar", "dict_path": "ppocr/utils/dict/table_structure_dict_ch.txt", }, },"layout": {"en": {"url": "https://paddleocr.bj.bcebos.com/ppstructure/models/layout/picodet_lcnet_x1_0_fgd_layout_infer.tar", "dict_path": "ppocr/utils/dict/layout_dict/layout_publaynet_dict.txt", },"ch": {"url": "https://paddleocr.bj.bcebos.com/ppstructure/models/layout/picodet_lcnet_x1_0_fgd_layout_cdla_infer.tar", "dict_path": "ppocr/utils/dict/layout_dict/layout_cdla_dict.txt", }, }, }, }, }def parse_args(mMain=True):import argparseparser = init_args()parser.add_help = mMainparser.add_argument("--lang", type=str, default="ch")parser.add_argument("--det", type=str2bool, default=True)parser.add_argument("--rec", type=str2bool, default=True)parser.add_argument("--type", type=str, default="ocr")parser.add_argument("--savefile", type=str2bool, default=False)parser.add_argument("--ocr_version", type=str, choices=SUPPORT_OCR_MODEL_VERSION, default="PP-OCRv4", help="OCR Model version, the current model support list is as follows: ""1. PP-OCRv4/v3 Support Chinese and English detection and recognition model, and direction classifier model""2. PP-OCRv2 Support Chinese detection and recognition model. ""3. PP-OCR support Chinese detection, recognition and direction classifier and multilingual recognition model.", )parser.add_argument("--structure_version", type=str, choices=SUPPORT_STRUCTURE_MODEL_VERSION, default="PP-StructureV2", help="Model version, the current model support list is as follows:"" 1. PP-Structure Support en table structure model."" 2. PP-StructureV2 Support ch and en table structure model.", )for action in parser._actions:if action.dest in ["rec_char_dict_path", "table_char_dict_path", "layout_dict_path", ]:action.default = Noneif mMain:return parser.parse_args()else:inference_args_dict = {}for action in parser._actions:inference_args_dict[action.dest] = action.defaultreturn argparse.Namespace(**inference_args_dict)def parse_lang(lang):latin_lang = ["af", "az", "bs", "cs", "cy", "da", "de", "es", "et", "fr", "ga", "hr", "hu", "id", "is", "it", "ku", "la", "lt", "lv", "mi", "ms", "mt", "nl", "no", "oc", "pi", "pl", "pt", "ro", "rs_latin", "sk", "sl", "sq", "sv", "sw", "tl", "tr", "uz", "vi", "french", "german", ]arabic_lang = ["ar", "fa", "ug", "ur"]cyrillic_lang = ["ru", "rs_cyrillic", "be", "bg", "uk", "mn", "abq", "ady", "kbd", "ava", "dar", "inh", "che", "lbe", "lez", "tab", ]devanagari_lang = ["hi", "mr", "ne", "bh", "mai", "ang", "bho", "mah", "sck", "new", "gom", "sa", "bgc", ]if lang in latin_lang:lang = "latin"elif lang in arabic_lang:lang = "arabic"elif lang in cyrillic_lang:lang = "cyrillic"elif lang in devanagari_lang:lang = "devanagari"assert (lang in MODEL_URLS["OCR"][DEFAULT_OCR_MODEL_VERSION]["rec"]), "param lang must in {}, but got {}".format(MODEL_URLS["OCR"][DEFAULT_OCR_MODEL_VERSION]["rec"].keys(), lang)if lang == "ch":det_lang = "ch"elif lang == "structure":det_lang = "structure"elif lang in ["en", "latin"]:det_lang = "en"else:det_lang = "ml"return lang, det_langdef get_model_config(type, version, model_type, lang):if type == "OCR":DEFAULT_MODEL_VERSION = DEFAULT_OCR_MODEL_VERSIONelif type == "STRUCTURE":DEFAULT_MODEL_VERSION = DEFAULT_STRUCTURE_MODEL_VERSIONelse:raise NotImplementedErrormodel_urls = MODEL_URLS[type]if version not in model_urls:version = DEFAULT_MODEL_VERSIONif model_type not in model_urls[version]:if model_type in model_urls[DEFAULT_MODEL_VERSION]:version = DEFAULT_MODEL_VERSIONelse:logger.error("{} models is not support, we only support {}".format(model_type, model_urls[DEFAULT_MODEL_VERSION].keys()))sys.exit(-1)if lang not in model_urls[version][model_type]:if lang in model_urls[DEFAULT_MODEL_VERSION][model_type]:version = DEFAULT_MODEL_VERSIONelse:logger.error("lang {} is not support, we only support {} for {} models".format(lang, model_urls[DEFAULT_MODEL_VERSION][model_type].keys(), model_type, ))sys.exit(-1)return model_urls[version][model_type][lang]def img_decode(content: bytes):np_arr = np.frombuffer(content, dtype=np.uint8)return cv2.imdecode(np_arr, cv2.IMREAD_UNCHANGED)def check_img(img, alpha_color=(255, 255, 255)):"""Check the image data. If it is another type of image file, try to decode it into a numpy array.The inference network requires three-channel images, So the following channel conversions are donesingle channel image: Gray to RGB R←Y,G←Y,B←Yfour channel image: alpha_to_colorargs:img: image datafile format: jpg, png and other image formats that opencv can decode, as well as gif and pdf formatsstorage type: binary image, net image file, local image filealpha_color: Background color in images in RGBA formatreturn: numpy.array (h, w, 3) or list (p, h, w, 3) (p: page of pdf), boolean, boolean"""flag_gif, flag_pdf = False, Falseif isinstance(img, bytes):img = img_decode(img)if isinstance(img, str):# download net imageif is_link(img):download_with_progressbar(img, "tmp.jpg")img = "tmp.jpg"image_file = imgimg, flag_gif, flag_pdf = check_and_read(image_file)if not flag_gif and not flag_pdf:with open(image_file, "rb") as f:img_str = f.read()img = img_decode(img_str)if img is None:try:buf = BytesIO()image = BytesIO(img_str)im = Image.open(image)rgb = im.convert("RGB")rgb.save(buf, "jpeg")buf.seek(0)image_bytes = buf.read()data_base64 = str(base64.b64encode(image_bytes), encoding="utf-8")image_decode = base64.b64decode(data_base64)img_array = np.frombuffer(image_decode, np.uint8)img = cv2.imdecode(img_array, cv2.IMREAD_COLOR)except:logger.error("error in loading image:{}".format(image_file))return None, flag_gif, flag_pdfif img is None:logger.error("error in loading image:{}".format(image_file))return None, flag_gif, flag_pdf# single channel image array.shape:h,wif isinstance(img, np.ndarray) and len(img.shape) == 2:img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)# four channel image array.shape:h,w,cif isinstance(img, np.ndarray) and len(img.shape) == 3 and img.shape[2] == 4:img = alpha_to_color(img, alpha_color)return img, flag_gif, flag_pdfclass PaddleOCR(predict_system.TextSystem):def __init__(self, **kwargs):"""paddleocr packageargs:**kwargs: other params show in paddleocr --help"""params = parse_args(mMain=False)params.__dict__.update(**kwargs)assert (params.ocr_version in SUPPORT_OCR_MODEL_VERSION), "ocr_version must in {}, but get {}".format(SUPPORT_OCR_MODEL_VERSION, params.ocr_version)params.use_gpu = check_gpu(params.use_gpu)if not params.show_log:logger.setLevel(logging.INFO)self.use_angle_cls = params.use_angle_clslang, det_lang = parse_lang(params.lang)# init model dirdet_model_config = get_model_config("OCR", params.ocr_version, "det", det_lang)params.det_model_dir, det_url = confirm_model_dir_url(params.det_model_dir, os.path.join(BASE_DIR, "whl", "det", det_lang), det_model_config["url"], )rec_model_config = get_model_config("OCR", params.ocr_version, "rec", lang)params.rec_model_dir, rec_url = confirm_model_dir_url(params.rec_model_dir, os.path.join(BASE_DIR, "whl", "rec", lang), rec_model_config["url"], )cls_model_config = get_model_config("OCR", params.ocr_version, "cls", "ch")params.cls_model_dir, cls_url = confirm_model_dir_url(params.cls_model_dir, os.path.join(BASE_DIR, "whl", "cls"), cls_model_config["url"], )if params.ocr_version in ["PP-OCRv3", "PP-OCRv4"]:params.rec_image_shape = "3, 48, 320"else:params.rec_image_shape = "3, 32, 320"# download model if using paddle inferif not params.use_onnx:maybe_download(params.det_model_dir, det_url)maybe_download(params.rec_model_dir, rec_url)maybe_download(params.cls_model_dir, cls_url)if params.det_algorithm not in SUPPORT_DET_MODEL:logger.error("det_algorithm must in {}".format(SUPPORT_DET_MODEL))sys.exit(0)if params.rec_algorithm not in SUPPORT_REC_MODEL:logger.error("rec_algorithm must in {}".format(SUPPORT_REC_MODEL))sys.exit(0)if params.rec_char_dict_path is None:params.rec_char_dict_path = str(Path(__file__).parent / rec_model_config["dict_path"])logger.debug(params)# init det_model and rec_modelsuper().__init__(params)self.page_num = params.page_numdef ocr(self, img, det=True, rec=True, cls=True, bin=False, inv=False, alpha_color=(255, 255, 255), ):"""OCR with PaddleOCRargs:img: img for OCR, support ndarray, img_path and list or ndarraydet: use text detection or not. If False, only rec will be exec. Default is Truerec: use text recognition or not. If False, only det will be exec. Default is Truecls: use angle classifier or not. Default is True. If True, the text with rotation of 180 degrees can be recognized. If no text is rotated by 180 degrees, use cls=False to get better performance. Text with rotation of 90 or 270 degrees can be recognized even if cls=False.bin: binarize image to black and white. Default is False.inv: invert image colors. Default is False.alpha_color: set RGB color Tuple for transparent parts replacement. Default is pure white."""assert isinstance(img, (np.ndarray, list, str, bytes))if isinstance(img, list) and det == True:logger.error("When input a list of images, det must be false")exit(0)if cls == True and self.use_angle_cls == False:logger.warning("Since the angle classifier is not initialized, it will not be used during the forward process")img, flag_gif, flag_pdf = check_img(img, alpha_color)# for infer pdf fileif isinstance(img, list) and flag_pdf:if self.page_num > len(img) or self.page_num == 0:imgs = imgelse:imgs = img[: self.page_num]else:imgs = [img]def preprocess_image(_image):_image = alpha_to_color(_image, alpha_color)if inv:_image = cv2.bitwise_not(_image)if bin:_image = binarize_img(_image)return _imageif det and rec:ocr_res = []for idx, img in enumerate(imgs):img = preprocess_image(img)dt_boxes, rec_res, _ = self.__call__(img, cls)if not dt_boxes and not rec_res:ocr_res.append(None)continuetmp_res = [[box.tolist(), res] for box, res in zip(dt_boxes, rec_res)]ocr_res.append(tmp_res)return ocr_reselif det and not rec:ocr_res = []for idx, img in enumerate(imgs):img = preprocess_image(img)dt_boxes, elapse = self.text_detector(img)if dt_boxes.size == 0:ocr_res.append(None)continuetmp_res = [box.tolist() for box in dt_boxes]ocr_res.append(tmp_res)return ocr_reselse:ocr_res = []cls_res = []for idx, img in enumerate(imgs):if not isinstance(img, list):img = preprocess_image(img)img = [img]if self.use_angle_cls and cls:img, cls_res_tmp, elapse = self.text_classifier(img)if not rec:cls_res.append(cls_res_tmp)rec_res, elapse = self.text_recognizer(img)ocr_res.append(rec_res)if not rec:return cls_resreturn ocr_resclass PPStructure(StructureSystem):def __init__(self, **kwargs):params = parse_args(mMain=False)params.__dict__.update(**kwargs)assert (params.structure_version in SUPPORT_STRUCTURE_MODEL_VERSION), "structure_version must in {}, but get {}".format(SUPPORT_STRUCTURE_MODEL_VERSION, params.structure_version)params.use_gpu = check_gpu(params.use_gpu)params.mode = "structure"if not params.show_log:logger.setLevel(logging.INFO)lang, det_lang = parse_lang(params.lang)if lang == "ch":table_lang = "ch"else:table_lang = "en"if params.structure_version == "PP-Structure":params.merge_no_span_structure = False# init model dirdet_model_config = get_model_config("OCR", params.ocr_version, "det", det_lang)params.det_model_dir, det_url = confirm_model_dir_url(params.det_model_dir, os.path.join(BASE_DIR, "whl", "det", det_lang), det_model_config["url"], )rec_model_config = get_model_config("OCR", params.ocr_version, "rec", lang)params.rec_model_dir, rec_url = confirm_model_dir_url(params.rec_model_dir, os.path.join(BASE_DIR, "whl", "rec", lang), rec_model_config["url"], )table_model_config = get_model_config("STRUCTURE", params.structure_version, "table", table_lang)params.table_model_dir, table_url = confirm_model_dir_url(params.table_model_dir, os.path.join(BASE_DIR, "whl", "table"), table_model_config["url"], )layout_model_config = get_model_config("STRUCTURE", params.structure_version, "layout", lang)params.layout_model_dir, layout_url = confirm_model_dir_url(params.layout_model_dir, os.path.join(BASE_DIR, "whl", "layout"), layout_model_config["url"], )# download modelif not params.use_onnx:maybe_download(params.det_model_dir, det_url)maybe_download(params.rec_model_dir, rec_url)maybe_download(params.table_model_dir, table_url)maybe_download(params.layout_model_dir, layout_url)if params.rec_char_dict_path is None:params.rec_char_dict_path = str(Path(__file__).parent / rec_model_config["dict_path"])if params.table_char_dict_path is None:params.table_char_dict_path = str(Path(__file__).parent / table_model_config["dict_path"])if params.layout_dict_path is None:params.layout_dict_path = str(Path(__file__).parent / layout_model_config["dict_path"])logger.debug(params)super().__init__(params)def __call__(self, img, return_ocr_result_in_table=False, img_idx=0, alpha_color=(255, 255, 255), ):img, flag_gif, flag_pdf = check_img(img, alpha_color)if isinstance(img, list) and flag_pdf:res_list = []for index, pdf_img in enumerate(img):logger.info("processing {}/{} page:".format(index + 1, len(img)))res, _ = super().__call__(pdf_img, return_ocr_result_in_table, img_idx=index)res_list.append(res)return res_listres, _ = super().__call__(img, return_ocr_result_in_table, img_idx=img_idx)return res
def cv2AddChineseText(img, text, position, textColor=(0, 255, 0), textSize=30):img = Image.fromarray(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))draw = ImageDraw.Draw(img)draw.text(position, text, textColor, font=font)return cv2.cvtColor(np.asarray(img), cv2.COLOR_RGB2BGR)if __name__ == '__main__':font_path = 'simhei.ttf'  # 需要替换为你的中文字体路径font = ImageFont.truetype(font_path, 24)# for cmdargs = parse_args(mMain=True)image_dir = args.image_dirimage_file_list=['weights/123.jpg']if args.type == "ocr":engine = PaddleOCR(**(args.__dict__))elif args.type == "structure":engine = PPStructure(**(args.__dict__))else:raise NotImplementedErrorfor img_path in image_file_list:img_name = os.path.basename(img_path).split(".")[0]logger.info("{}{}{}".format("*" * 10, img_path, "*" * 10))if args.type == "ocr":image=cv2.imread(img_path)result = engine.ocr(img_path, det=args.det, rec=args.rec, cls=args.use_angle_cls, bin=args.binarize, inv=args.invert, alpha_color=args.alphacolor, )if result is not None:lines = []for idx in range(len(result)):res = result[idx]for line in res:points = line[0]text = line[1][0]points = np.array(points, dtype=np.int32).reshape((-1, 1, 2))cv2.polylines(image, [points], isClosed=True, color=(255, 0, 0), thickness=2)text_position = (int(points[0][0][0]), int(points[0][0][1] + 20))  # 微调文本位置# cv2.putText(image, '中文文本', (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 2, (255, 255, 255), 3)image = cv2AddChineseText(image, text, text_position, textColor=(0, 255, 0), textSize=30)logger.info(line)val = "["for box in line[0]:val += str(box[0]) + "," + str(box[1]) + ","val = val[:-1]val += "]," + line[1][0] + "," + str(line[1][1]) + "\n"lines.append(val)if args.savefile:if os.path.exists(args.output) is False:os.mkdir(args.output)outfile = args.output + "/" + img_name + ".txt"with open(outfile, "w", encoding="utf-8") as f:f.writelines(lines)elif args.type == "structure":img, flag_gif, flag_pdf = check_and_read(img_path)if not flag_gif and not flag_pdf:img = cv2.imread(img_path)if not flag_pdf:if img is None:logger.error("error in loading image:{}".format(img_path))continueimg_paths = [[img_path, img]]else:img_paths = []for index, pdf_img in enumerate(img):os.makedirs(os.path.join(args.output, img_name), exist_ok=True)pdf_img_path = os.path.join(args.output, img_name, img_name + "_" + str(index) + ".jpg")cv2.imwrite(pdf_img_path, pdf_img)img_paths.append([pdf_img_path, pdf_img])all_res = []for index, (new_img_path, img) in enumerate(img_paths):logger.info("processing {}/{} page:".format(index + 1, len(img_paths)))new_img_name = os.path.basename(new_img_path).split(".")[0]result = engine(img, img_idx=index)save_structure_res(result, args.output, img_name, index)if args.recovery and result != []:from copy import deepcopyfrom ppstructure.recovery.recovery_to_doc import sorted_layout_boxesh, w, _ = img.shaperesult_cp = deepcopy(result)result_sorted = sorted_layout_boxes(result_cp, w)all_res += result_sortedif args.recovery and all_res != []:try:from ppstructure.recovery.recovery_to_doc import convert_info_docxconvert_info_docx(img, all_res, args.output, img_name)except Exception as ex:logger.error("error in layout recovery image:{}, err msg: {}".format(img_name, ex))continuefor item in all_res:item.pop("img")item.pop("res")logger.info(item)logger.info("result save to {}".format(args.output))cv2.imshow('image', image)cv2.waitKey(0)