def model(img,
detectAngle=False,
config={},
leftAdjust=False,
rightAdjust=False,
alph=0.2,
ifadjustDegree=False):
"""
@@param:img,
@@param:ifadjustDegree 调整文字识别倾斜角度
@@param:detectAngle,是否检测文字朝向
"""
angle, degree, img = eval_angle(img,
detectAngle=detectAngle,
ifadjustDegree=ifadjustDegree)
if opencvFlag != 'keras':
img, f = letterbox_image(img, IMGSIZE)
else:
f = 1.0 ##解决box在原图坐标不一致问题
config['img'] = img
timeTake = time.time()
text_recs = text_detect(**config)
timeTake = time.time() - timeTake
print('Detect take:{}s'.format(timeTake))
newBox = sort_box(text_recs)
result = crnnRec(np.array(img), newBox, leftAdjust, rightAdjust, alph,
1.0 / f)
return img, result, angle
def text_detect(img,scale,maxScale,prob = 0.05):
thresh = prob
img_height,img_width = img.shape[:2]
inputBlob,f = letterbox_image(img,(scale,scale))
inputBlob = cv2.dnn.blobFromImage(inputBlob, scalefactor=1.0, size=(scale,scale),swapRB=True ,crop=False)
textNet.setInput(inputBlob/255.0)
outputName = textNet.getUnconnectedOutLayersNames()
outputs = textNet.forward(outputName)
class_ids = []
confidences = []
boxes = []
for output in outputs:
for detection in output:
scores = detection[5:]
class_id = np.argmax(scores)
confidence = scores[class_id]
if confidence > thresh:
center_x = int(detection[0] * scale/f)
center_y = int(detection[1] * scale/f)
width = int(detection[2] * scale/f)
height = int(detection[3] * scale/f)
left = int(center_x - width / 2)
top = int(center_y - height / 2)
if class_id==1:
class_ids.append(class_id)
confidences.append(float(confidence))
boxes.append([left, top,left+width, top+height ])
boxes = np.array(boxes)
confidences = np.array(confidences)
return boxes,confidences
def model(img, detectAngle=False, config={}, leftAdjust=False, rightAdjust=False, alph=0.2):
"""
@@param:img,
@@param:ifadjustDegree 调整文字识别倾斜角度
@@param:detectAngle,是否检测文字朝向
"""
angle, img = eval_angle(img, detectAngle=detectAngle) ##文字方向检测
if opencvFlag != 'keras':
img, f = letterbox_image(Image.fromarray(img), IMGSIZE) ## pad
img = np.array(img)
else:
f = 1.0 ##解决box在原图坐标不一致问题
config['img'] = img
text_recs = text_detect(**config) ##文字检测
newBox = sort_box(text_recs) ##行文本识别
result = crnnRec(np.array(img), newBox, leftAdjust, rightAdjust, alph, 1.0 / f)
return img, result, angle
def model(img,
file_name,
detectAngle=False,
config={},
leftAdjust=False,
rightAdjust=False,
alpha=0.2):
"""
@@param:img,
@@param:ifadjustDegree 调整文字识别倾斜角度
@@param:detectAngle,是否检测文字朝向
"""
angle, img = eval_angle(img, detectAngle=detectAngle) # 进行文字方向检测
if opencvFlag != 'keras':
img, f = letterbox_image(Image.fromarray(img), IMGSIZE) # pad
img = np.array(img)
else:
f = 1.0 # 解决box在原图坐标不一致问题
config['img'] = img
image_cv = copy.copy(img)
cv2.imshow("model", image_cv)
text_recs = text_detect(**config) # 文字检测
# print('text_recs', text_recs)
# draw_boxes(image_cv, text_recs, "text_recs", (255, 255, 0))
newBox = sort_box(text_recs) # 文本进行排序（从上到下进行排序）
print('newBox', newBox)
draw_boxes(image_cv, text_recs, file_name, (255, 0, 0), "./output")
# print('model', img.shape)
result = crnnRec(np.array(img), newBox, leftAdjust, rightAdjust, alpha,
1.0 / f) # ocr识别
print('result', result)
return img, result, angle
def model(img,
detectAngle=False,
config={},
leftAdjust=False,
rightAdjust=False,
alph=0.2,
bili=1.2):
"""
@@param:img,
@@param:ifadjustDegree 调整文字识别倾斜角度
@@param:detectAngle,是否检测文字朝向
"""
print(22222222222)
'''
这个地方需要加入图片预处理!!!!!!滤波等.
确实这个算法没有加入,需要加入!!!!!!!!!!!
'''
angle, img = eval_angle(img, detectAngle=detectAngle) ##文字方向检测
if opencvFlag != 'keras':
img, f = letterbox_image(Image.fromarray(img), IMGSIZE) ## pad
img = np.array(img)
else:
f = 1.0 ##解决box在原图坐标不一致问题
config['img'] = img
config['bili'] = bili
text_recs, scores, boxForSingleAfterNMS, scoresForSingle, keepIndForSingle, tp_groups, Allboxes, Allscores = text_detect(
**config) ##文字检测
newBox, tp_groups = sort_box(text_recs,
tp_groups) #按照列高排序,符合我们阅读顺序! ##下行行文本识别
print(newBox)
result = crnnRec(np.array(img), newBox, leftAdjust, rightAdjust, alph,
1.0 / f, tp_groups, boxForSingleAfterNMS, scoresForSingle)
return img, result, angle, scores, text_recs, newBox, boxForSingleAfterNMS, scoresForSingle, keepIndForSingle, tp_groups, Allboxes, Allscores
