目录
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 PaddleOCR
filepath = 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 time
import cv2
import numpy as np
from PIL import ImageFont
from PIL import Image
from PIL import ImageDraw
from paddleocr import PaddleOCR
filepath = 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_import
sys.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_system
def _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] = module
return module
tools = _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_logger
logger = 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_excel
logger = 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 argparse
parser = init_args()
parser.add_help = mMain
parser.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 = None
if mMain:
return parser.parse_args()
else:
inference_args_dict = {}
for action in parser._actions:
inference_args_dict[action.dest] = action.default
return 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_lang
def get_model_config(type, version, model_type, lang):
if type == "OCR":
DEFAULT_MODEL_VERSION = DEFAULT_OCR_MODEL_VERSION
elif type == "STRUCTURE":
DEFAULT_MODEL_VERSION = DEFAULT_STRUCTURE_MODEL_VERSION
else:
raise NotImplementedError
model_urls = MODEL_URLS[type]
if version not in model_urls:
version = DEFAULT_MODEL_VERSION
if model_type not in model_urls[version]:
if model_type in model_urls[DEFAULT_MODEL_VERSION]:
version = DEFAULT_MODEL_VERSION
else:
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_VERSION
else:
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 done
single channel image: Gray to RGB R←Y,G←Y,B←Y
four channel image: alpha_to_color
args:
img: image data
file format: jpg, png and other image formats that opencv can decode, as well as gif and pdf formats
storage type: binary image, net image file, local image file
alpha_color: Background color in images in RGBA format
return: numpy.array (h, w, 3) or list (p, h, w, 3) (p: page of pdf), boolean, boolean
"""
flag_gif, flag_pdf = False, False
if isinstance(img, bytes):
img = img_decode(img)
if isinstance(img, str):
# download net image
if is_link(img):
download_with_progressbar(img, "tmp.jpg")
img = "tmp.jpg"
image_file = img
img, 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_pdf
if img is None:
logger.error("error in loading image:{}".format(image_file))
return None, flag_gif, flag_pdf
# single channel image array.shape:h,w
if isinstance(img, np.ndarray) and len(img.shape) == 2:
img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
# four channel image array.shape:h,w,c
if 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_pdf
class PaddleOCR(predict_system.TextSystem):
def __init__(self, **kwargs):
"""
paddleocr package
args:
**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_cls
lang, det_lang = parse_lang(params.lang)
# init model dir
det_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 infer
if 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_model
super().__init__(params)
self.page_num = params.page_num
def ocr(self, img, det=True, rec=True, cls=True, bin=False, inv=False, alpha_color=(255, 255, 255), ):
"""
OCR with PaddleOCR
args:
img: img for OCR, support ndarray, img_path and list or ndarray
det: use text detection or not. If False, only rec will be exec. Default is True
rec: use text recognition or not. If False, only det will be exec. Default is True
cls: 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 file
if isinstance(img, list) and flag_pdf:
if self.page_num > len(img) or self.page_num == 0:
imgs = img
else:
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 _image
if 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)
continue
tmp_res = [[box.tolist(), res] for box, res in zip(dt_boxes, rec_res)]
ocr_res.append(tmp_res)
return ocr_res
elif 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)
continue
tmp_res = [box.tolist() for box in dt_boxes]
ocr_res.append(tmp_res)
return ocr_res
else:
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_res
return ocr_res
class 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 dir
det_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 model
if 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_list
res, _ = 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 cmd
args = parse_args(mMain=True)
image_dir = args.image_dir
image_file_list=['weights/123.jpg']
if args.type == "ocr":
engine = PaddleOCR(**(args.__dict__))
elif args.type == "structure":
engine = PPStructure(**(args.__dict__))
else:
raise NotImplementedError
for 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))
continue
img_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 deepcopy
from ppstructure.recovery.recovery_to_doc import sorted_layout_boxes
h, w, _ = img.shape
result_cp = deepcopy(result)
result_sorted = sorted_layout_boxes(result_cp, w)
all_res += result_sorted
if args.recovery and all_res != []:
try:
from ppstructure.recovery.recovery_to_doc import convert_info_docx
convert_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))
continue
for 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)