def model(img,adjust=False,detectAngle=False):
"""
@@param:img,
@@param:model,选择的ocr模型，支持keras\pytorch版本
@@param:adjust 调整文字识别结果
@@param:detectAngle,是否检测文字朝向
"""
angle = 0
if detectAngle:
angle = angle_detect(img=np.copy(img))##文字朝向检测
im = Image.fromarray(img)
if angle==90:
im = im.transpose(Image.ROTATE_90)
elif angle==180:
im = im.transpose(Image.ROTATE_180)
elif angle==270:
im = im.transpose(Image.ROTATE_270)
img = np.array(im)
text_recs,tmp,img = text_detect(img)
text_recs = sort_box(text_recs)
result = crnnRec(img,text_recs,model,adjust=adjust)
return result,tmp,angle
def model(img, model='keras', adjust=False, detectAngle=False):
"""
@@param:img,
@@param:model,选择的ocr模型，支持keras\pytorch版本
@@param:adjust 调整文字识别结果
@@param:detectAngle,是否检测文字朝向
"""
angle = 0
if detectAngle:
# 进行文字旋转方向检测，分为[0, 90, 180, 270]四种情况
angle = angle_detect(img=np.copy(img)) # 文字朝向检测
print('The angel of this character is:', angle)
im = Image.fromarray(img)
print('Rotate the array of this img!')
if angle == 90:
im = im.transpose(Image.ROTATE_90)
elif angle == 180:
im = im.transpose(Image.ROTATE_180)
elif angle == 270:
im = im.transpose(Image.ROTATE_270)
img = np.array(im)
# 进行图像中的文字区域的识别
text_recs, tmp, img = text_detect(img)
# 识别区域排列
text_recs = sort_box(text_recs)
#
result = crnnRec(img, text_recs, model, adjust=adjust)
return result, tmp, angle
def model(img, _model='keras', adjust=False, detect_angle=False):
"""
:param img:
:param _model: 选择的ocr模型，支持keras\pytorch版本
:param adjust: 调整文字识别结果
:param detect_angle: 是否检测文字朝向
:return:
"""
angle = 0
if detect_angle:
# 文字朝向检测
angle = angle_detect(img=np.copy(img))
im = Image.fromarray(img)
if angle == 90:
im = im.transpose(Image.ROTATE_90)
elif angle == 180:
im = im.transpose(Image.ROTATE_180)
elif angle == 270:
im = im.transpose(Image.ROTATE_270)
img = np.array(im)
text_recs, tmp, img = text_detect(img)
text_recs = sort_box(text_recs)
result = crnnRec(img, text_recs, _model, adjust=adjust)
return result, tmp, angle
def model(img, adjust=False, detectAngle=False):
angle = 0
if detectAngle:
angle = angle_detect(img=np.copy(img))
im = Image.fromarray(img)
if angle == 90:
im = im.transpose(Image.ROTATE_90)
elif angle == 180:
im = im.transpose(Image.ROTATE_180)
elif angle == 270:
im = im.transpose(Image.ROTATE_270)
img = np.array(im)
text_recs, tmp, img = text_detect(img)
text_recs = sort_box(text_recs)
result = crnnRec(img, text_recs, model, adjust=adjust)
return result, tmp, angle
def model(img, adjust=False, detectAngle=False):
"""
@img: 图片
@adjust: 是否调整文字识别结果
"""
angle = 0
if detectAngle:
angle = angle_detect(img=np.copy(img)) ##文字朝向检测
im = Image.fromarray(img)
if angle == 90:
im = im.transpose(Image.ROTATE_90)
elif angle == 180:
im = im.transpose(Image.ROTATE_180)
elif angle == 270:
im = im.transpose(Image.ROTATE_270)
img = np.array(im)
cfg_from_file('./ctpn/ctpn/text.yml')
text_recs, img_framed, img = text_detect(img)
text_recs = sort_box(text_recs)
result = charRec(img, text_recs, adjust)
return result, img_framed
def model(img, model='keras', adjust=False, detectAngle=False):
angle = 0
if detectAngle:
angle = angle_detect(img=np.copy(img))
print('The angel of this character is:', angle)
im = Image.fromarray(img)
print('Rotate the array of this img!')
if angle == 90:
im = im.transpose(Image.ROTATE_90)
elif angle == 180:
im = im.transpose(Image.ROTATE_180)
elif angle == 270:
im = im.transpose(Image.ROTATE_270)
img = np.array(im)
text_recs, tmp, img = text_detect(img)
text_recs = sort_box(text_recs)
#
result = crnnRec(img, text_recs, model, adjust=adjust)
return result, tmp, angle
def model(img, model, adjust=False, detectAngle=False):
"""
@@param:img,输入的图像数组
@@param:model,选择的ocr模型，支持pytorch版本
@@param:adjust 调整文字识别结果
@@param:detectAngle,是否检测文字朝向
"""
angle = 0
if detectAngle:
# 进行文字旋转方向检测，分为[0, 90, 180, 270]四种情况,下面所用的是逆时针旋转，因此需要改正
angle = angle_detect(img=np.copy(img)) ##文字朝向检测
print('The angel of this character is:', angle)
im = Image.fromarray(img)
print('Rotate the array of this img!')
if angle == 90:
im = im.transpose(Image.ROTATE_270)
elif angle == 180:
im = im.transpose(Image.ROTATE_180)
elif angle == 270:
im = im.transpose(Image.ROTATE_90)
img = np.array(im)
print(img)
# 进行图像中的文字区域的识别
t = time.time()
text_recs, tmp, img = text_detect(img)
print('image area recognition finished!')
print("It takes time:{}s".format(time.time() - t))
# 识别区域排列
text_recs = sort_box(text_recs)
# 文本识别
t = time.time()
result = crnnRec(img, text_recs, ocrMode=model, adjust=adjust)
print('end-to-end text recognition finished!')
print("It takes time:{}s".format(time.time() - t))
return result, tmp, angle
