def ocr(image):
# detect
image = highlight(image)
text_recs, img_framed, image = get_det_boxes(image)
text_recs = sort_box(text_recs)
result = charRec(image, text_recs)
return result, img_framed
def proc_img(image):
# detect
text_recs, img_framed, image = get_det_boxes(
image
) #gọi hàm get_det_boxes trả về ảnh đã vẽ (img_framed), tọa độ cắt ảnh (test_recs)
text_recs = sort_box(text_recs) #sắp xếp các trường
result = char_rec(
image,
text_recs) #nhận diện , đầu vào là file tọa độ và hình ảnh ban đầu
return result, img_framed
def charRec(img, text_recs, adjust=False):
"""
加载OCR模型，进行字符识别
"""
results = {}
xDim, yDim = img.shape[1], img.shape[0]
for index, rec in enumerate(text_recs):
xlength = int((rec[6] - rec[0]) * 0.1)
ylength = int((rec[7] - rec[1]) * 0.2)
if adjust:
pt1 = (max(1, rec[0] - xlength), max(1, rec[1] - ylength))
pt2 = (rec[2], rec[3])
pt3 = (min(rec[6] + xlength,
xDim - 2), min(yDim - 2, rec[7] + ylength))
pt4 = (rec[4], rec[5])
else:
pt1 = (max(1, rec[0]), max(1, rec[1]))
pt2 = (rec[2], rec[3])
pt3 = (min(rec[6], xDim - 2), min(yDim - 2, rec[7]))
pt4 = (rec[4], rec[5])
degree = degrees(atan2(pt2[1] - pt1[1], pt2[0] - pt1[0])) # 图像倾斜角度
partImg = dumpRotateImage(img, degree, pt1, pt2, pt3, pt4)
#dis(partImg)
if partImg.shape[0] < 1 or partImg.shape[1] < 1 or partImg.shape[
0] > partImg.shape[1]: # 过滤异常图片
continue
text = recognizer.recognize(partImg)
if len(text) > 0:
results[index] = [rec]
results[index].append(text) # 识别文字
return results
# the input image is a one-channel-nparray imagedef ocr(image):
# detect
text_recs, img_framed, image = get_det_boxes(image)
text_recs = sort_box(text_recs)
result = charRec(image, text_recs)
return result, img_framed