def test_multiple_instances(model_name):
global INSTANCE_ID
print('test multiple instances for model_name: %s' % model_name)
img_fp = os.path.join(example_dir, 'beauty2.jpg')
INSTANCE_ID += 1
print('instance id: %d' % INSTANCE_ID)
std1 = CnStd(model_name, name='instance-%d' % INSTANCE_ID)
box_info_list = std1.detect(img_fp)
INSTANCE_ID += 1
std2 = CnStd(model_name, name='instance-%d' % INSTANCE_ID)
box_info_list2 = std2.detect(img_fp)
assert len(box_info_list) == len(box_info_list2)
def __init__(self, path: str, show_img: bool = False):
self.__ext = {'jpg', 'jpeg'}
self.__ocr = CnOcr(model_name='densenet-lite-gru',
cand_alphabet=string.digits,
name=path)
self.__std = CnStd(name=path)
self.__info_dict = {}
self.__dup_name_dict = {}
# 先对路径进行替换
path = self.__format_path(path)
# 根据传入的路径判断操作
if os.path.isdir(path) or os.path.isfile(path):
files = [self.__format_path(os.path.join(path, f)) for f in os.listdir(path) if
(os.path.isfile(os.path.join(path, f)) and self.__is_image(f))] \
if os.path.isdir(path) \
else [path]
for file in tqdm(files):
self.__handle_info(
file,
self.__ocr_number(
self.__std_number(self.__cutter(file, show_img))))
else:
print(f'获取数据错误，“{path}”既不是文件也不是文件夹')
def start_engine(model_path='models'):
if OCR_MODEL_NAME + '.zip' in os.listdir(
model_path) and STD_MODEL_NAME + '.zip' in os.listdir(model_path):
print('初始化模型中...')
ocr_root = os.path.join(data_dir(mode='cnocr'), ocr_version)
ocr_root = os.path.join(ocr_root, OCR_MODEL_NAME)
os.makedirs(ocr_root, exist_ok=True)
ocr_zip_file_path = os.path.join(ocr_root, OCR_MODEL_NAME + '.zip')
shutil.copyfile(os.path.join('models', OCR_MODEL_NAME + '.zip'),
ocr_zip_file_path)
with zipfile.ZipFile(ocr_zip_file_path) as zf:
zf.extractall(os.path.dirname(ocr_root))
os.remove(ocr_zip_file_path)
std_root = os.path.join(data_dir(mode='cnstd'), std_version)
std_root = os.path.join(std_root, STD_MODEL_NAME)
os.makedirs(std_root, exist_ok=True)
std_zip_file_path = os.path.join(std_root, STD_MODEL_NAME + '.zip')
shutil.copyfile(os.path.join('models', STD_MODEL_NAME + '.zip'),
std_zip_file_path)
with zipfile.ZipFile(std_zip_file_path) as zf:
zf.extractall(os.path.dirname(std_root))
os.remove(std_zip_file_path)
ocr_core = CnOcr()
std_core = CnStd()
print('初始化完成')
return ocr_core, std_core
else:
print('初始化失败，未找到预加载模型')
return None
def get_list(self):
std=CnStd()
ocr=CnOcr()
ocr._model_name='conv-lite-fc'
print(ocr._model_name)
ocr_res2=ocr.ocr(img_fp=self.filepath)
box_info_list=std.detect(self.filepath,pse_threshold=0.7,pse_min_area=150,context='gpu',height_border=0.10)
image=Image.open(self.filepath)
fontstyle=ImageFont.truetype('./simhei.ttf',13,encoding='utf-8')
draw=ImageDraw.Draw(image)
for box_info in box_info_list:
print('a')
print('a')
print(box_info)
info_box=box_info['box']
crp_img=box_info['cropped_img']
ocr_res1=ocr.ocr_for_single_line(crp_img)
print('result: %s' % ''.join(str(ocr_res1)))
x1,y1=info_box[0,0],info_box[0,1]
x2,y2=info_box[1,0],info_box[1,1]
x3,y3=info_box[2,0],info_box[2,1]
x4,y4=info_box[3,0],info_box[3,1]
draw.polygon([(x1,y1),(x4,y4),(x3,y3),(x2,y2)],outline=(255,0,0))
draw.text((x4,y4),str(ocr_res1),(200,0,0),font=fontstyle)
image.show()
print(ocr_res2)
return box_info_list
def test_resnet50_v1b():
model_name = 'resnet50_v1b'
img_fp = os.path.join(example_dir, 'beauty2.jpg')
std = CnStd(model_name)
box_info_list = std.detect(img_fp)
img = mx.image.imread(img_fp, 1)
box_info_list2 = std.detect(img)
assert len(box_info_list) == len(box_info_list2)
def identify(image):
std = CnStd(model_name='resnet50_v1b', root='C:/Users/HP/AppData/Roaming/Python/Python36/site-packages/cnstd')
global cn_ocr
box_info_list = std.detect(image)
ocr_res=[]
for box_info in box_info_list:
cropped_img = box_info['cropped_img']
ocr_res.extend(cn_ocr.ocr_for_single_line(cropped_img))
print('ocr result1: %s' % ''.join(ocr_res))
return ocr_res
def identify(image):
std = CnStd(model_name='resnet50_v1b',
root='C:/Users/dell/AppData/Roaming/cnstd/0.1.0/mobilenetv3')
global cn_ocr
ocr_res = []
box_info_list = std.detect(image)
ocr_res = []
for box_info in box_info_list:
cropped_img = box_info['cropped_img']
ocr_res.extend(cn_ocr.ocr_for_single_line(cropped_img))
print('ocr result1: %s' % ''.join(ocr_res))
return ocr_res
def __init__(self):
super(picture, self).__init__()
self.resize(350, 350)
self.setWindowTitle("图片转文字")
self.label = QLabel(self)
# self.label.setText("显示图片")
self.label.setScaledContents(True)
self.label.setFixedSize(300, 200)
self.label.move(25, 60)
self.label.setStyleSheet(
"QLabel{background:white;}"
"QLabel{color:rgb(300,300,300,120);font-size:10px;font-weight:bold;font-family:宋体;}"
)
btn = QPushButton(self)
btn.setText("打开图片")
btn.move(135, 20)
btn.clicked.connect(self.openimage)
self.label_text = QLabel(self)
self.label_text.setFixedSize(300, 30)
self.label_text.move(25, 270)
self.label_text.setTextInteractionFlags(
Qt.TextSelectableByMouse) ###可复制
self.label_wait = QLabel(self)
self.label_wait.setFixedSize(300, 30)
self.label_wait.move(25, 300)
# 标签1的背景填充更改为True，否则无法显示背景
self.label_wait.setAutoFillBackground(True)
# # 实例化背景对象，进行相关背景颜色属性设置
# palette = QPalette()
# palette.setColor(QPalette.Window, Qt.green)
# # 标签1加载背景
# self.label_wait.setPalette(palette)
# 设置文本居中显示
self.label_wait.setAlignment(Qt.AlignCenter)
self.label_wait.setText('tips：识别过程可能会卡住，需几秒到几十秒不等')
self.std = CnStd()
self.cn_ocr = CnOcr()
def extract_content(save_dir_path):
std = CnStd()
cn_ocr = CnOcr()
base_path = os.path.abspath(os.path.dirname(__file__))
pic_base_dir = os.path.join(base_path, "received")
pic_path_list = (glob.glob(os.path.join(pic_base_dir, "*.png")) +
glob.glob(os.path.join(pic_base_dir, "*.jpg")) +
glob.glob(os.path.join(pic_base_dir, "*.jpeg")))
workbook = xlwt.Workbook()
for index, pic_path in enumerate(pic_path_list):
sheet = workbook.add_sheet('sheet{}'.format(index),
cell_overwrite_ok=True)
box_info_list = std.detect(pic_path)
for box_info in box_info_list:
x_list, y_list = [], []
for (x, y) in box_info['box']:
x_list.append(x)
y_list.append(y)
top, bottom, left, right = min(y_list), max(y_list), min(
x_list), max(x_list)
top_row, bottom_row, left_column, right_column = int(
top // 80), int(bottom // 80), int(left // 60), int(right //
60)
cropped_img = box_info['cropped_img'] # 检测出的文本框
ocr_res = ''.join(cn_ocr.ocr_for_single_line(cropped_img))
try:
logger.info(
"top_row:{}, bottom_row:{}, left_column:{}, right_column:{}, ocr_res:{}",
top_row,
bottom_row,
left_column,
right_column,
ocr_res,
feature="f-strings")
sheet.write_merge(top_row, bottom_row, left_column,
right_column, ocr_res)
except Exception as e:
print(e)
xls_base_dir = os.path.join(base_path, save_dir_path)
xls_path = os.path.join(xls_base_dir, "res.xls")
workbook.save(xls_path)
def ocr():
if 'file' not in request.files:
return jsonify(code=-1, message='no file error'), 400
file = request.files['file']
_uuid = str(uuid.uuid1())
file_name = '/tmp/ocr/' + _uuid
file.save(file_name)
ocr = CnOcr(name=_uuid)
std = CnStd(name=_uuid)
box_info_list = std.detect(file_name)
lines = []
for box_info in box_info_list:
cropped_img = box_info['cropped_img'] # 检测出的文本框
ocr_res = ocr.ocr_for_single_line(cropped_img)
lines.append(''.join(ocr_res))
return jsonify(code=0, message='ok', data=lines)
def target_function(idx, ls, prefix):
# 使得每一张卡都能被充分用到
# 提交的时候由于只有一张卡，需要全部都改成0
os.environ['CUDA_VISIBLE_DEVICES'] = '0'
std = CnStd(context='gpu')
cn_ocr = CnOcr(context='gpu')
result = dict()
for file_name in tqdm(ls):
file_path = os.path.join(prefix, file_name)
box_info_list = std.detect(file_path)
output = ''
for box_info in box_info_list:
cropped_img = box_info['cropped_img'] # 检测出的文本框
if type(cropped_img) != type(None):
ocr_res = cn_ocr.ocr_for_single_line(cropped_img)
output += ''.join(ocr_res)
# print('ocr result: %s' % ''.join(ocr_res))
output = output.replace(' ', '')
output = re.sub("[^\u4e00-\u9fa5]", "", output)
result[file_name] = output
with open('./output_%d.json' % (idx), 'w', encoding='utf-8') as w:
w.write(json.dumps(result, ensure_ascii=False, indent=2))
import numpy as np
from cnocr import CnOcr
import cv2
from cnstd import CnStd
from identify import identify
global std, cn_ocr
kernel = np.ones((10, 10), np.uint8)
std = CnStd(
model_name='resnet50_v1b',
root='C:/Users/HP/AppData/Roaming/Python/Python36/site-packages/cnstd')
cn_ocr = CnOcr(model_name="conv-lite-fc")
#颜色提取方法
def color_identify(name):
#颜色范围
lower = np.array([70, 110, 110])
upper = np.array([130, 255, 255])
raw = cv2.imread(name)
original = cv2.imread(name)
#中值滤波
hsv_one = cv2.medianBlur(raw, 5)
hsv = cv2.cvtColor(hsv_one, cv2.COLOR_BGR2HSV)
#颜色提取
mask_blue = cv2.inRange(hsv, lower, upper)
res = cv2.bitwise_and(raw, raw, mask=mask_blue)
import cv2
import numpy as np
import pytesseract
from cnocr import CnOcr
import cv2
from cnstd import CnStd
#rawImage = cv2.imread("3.jpg")
kernel = np.ones((10, 10), np.uint8)
global std
global cn_ocr
std = CnStd(model_name='resnet50_v1b',
root='C:/Users/dell/AppData/Roaming/cnstd/0.1.0/mobilenetv3')
cn_ocr = CnOcr(model_name="conv-lite-fc")
#颜色提取方法
def color_identify(name):
rawImage = cv2.imread(name)
original = cv2.imread(name)
img = cv2.imread(name)
# 蓝色的范围
lower_blue = np.array([70, 110, 110])
upper_blue = np.array([130, 255, 255])
#中值滤波
hsv = cv2.medianBlur(rawImage, 5)
#转为hsv
hsv = cv2.cvtColor(hsv, cv2.COLOR_BGR2HSV)
from cnocr import CnOcr
import cnocr
from cnstd import CnStd
std=CnStd()
ocr=CnOcr()
box_info_list=std.detect('E:\\Work Place\\pocr\\pic\\2.png')
res=ocr.ocr('E:\\Work Place\\pocr\\pic\\1.png')
for box_info in box_info_list:
crp_img=box_info['cropped_img']
ocr_res=ocr.ocr_for_single_line(crp_img)
print('result: %s' % ''.join(ocr_res))
import string
import random
from cnstd import CnStd
from cnocr import CnOcr
from divide import divide
__std = CnStd(model_name='resnet50_v1b', context='cpu')
__ocr = CnOcr(model_name='densenet-lite-gru', context='cpu')
def OCRProcess(image_name=None):
assert isinstance(image_name, str), '请输入有效的图片路径'
box_info_list = __std.detect(image_name)
for box_info in box_info_list:
cropped_img = box_info['cropped_img']
ocr_res = __ocr.ocr_for_single_line(cropped_img)
print(ocr_res)
# print('ocr result: %s' % ''.join(ocr_res))
pass
OCRProcess('000000001960.jpg')
OCRProcess('000000002000.jpg')
OCRProcess('000000002040.jpg')
OCRProcess('000000002080.jpg')
OCRProcess('000000002120.jpg')
