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model.py
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model.py
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#! /usr/bin/env python
# -*- coding: utf-8 -*-
from detector.detectors import TextDetector
from detector.other import get_boxes
import darknet_detect
import numpy as np
from PIL import Image
import numpy as np
import time
import cv2
from glob import glob
from crnn.crnn import crnnOcr as crnnOcr
def text_detect(img,
MAX_HORIZONTAL_GAP=30,
MIN_V_OVERLAPS=0.6,
MIN_SIZE_SIM=0.6,
TEXT_PROPOSALS_MIN_SCORE=0.7,
TEXT_PROPOSALS_NMS_THRESH=0.3,
TEXT_LINE_NMS_THRESH = 0.3,
MIN_RATIO=1.0,
LINE_MIN_SCORE=0.8,
TEXT_PROPOSALS_WIDTH=5,
MIN_NUM_PROPOSALS=1
):
boxes, scores = darknet_detect.text_detect(np.array(img))
boxes = np.array(boxes,dtype=np.float32)
scores = np.array(scores,dtype=np.float32)
textdetector = TextDetector(MAX_HORIZONTAL_GAP,MIN_V_OVERLAPS,MIN_SIZE_SIM)
shape = img.size[::-1]
boxes = textdetector.detect(boxes,
scores[:, np.newaxis],
shape,
TEXT_PROPOSALS_MIN_SCORE,
TEXT_PROPOSALS_NMS_THRESH,
TEXT_LINE_NMS_THRESH,
MIN_RATIO,
LINE_MIN_SCORE,
TEXT_PROPOSALS_WIDTH,
MIN_NUM_PROPOSALS)
text_recs,tmp = get_boxes(np.array(img), boxes)
newBox = []
rx = 1
ry = 1
for box in text_recs:
x1,y1 = (box[0],box[1])
x2,y2 = (box[2],box[3])
x3,y3 = (box[6],box[7])
x4,y4 = (box[4],box[5])
newBox.append([x1*rx,y1*ry,x2*rx,y2*ry,x3*rx,y3*ry,x4*rx,y4*ry])
return newBox,tmp
import numpy as np
from PIL import Image
def crnnRec(im,boxes,ifIm=False,leftAdjust=False,rightAdjust=False,alph=0.2):
"""
crnn模型，ocr识别
@@model,
@@converter,
@@im:Array
@@text_recs:text box
@@ifIm:是否输出box对应的img
"""
results = []
im = Image.fromarray(im)
for index,box in enumerate(boxes):
degree,w,h,cx,cy = solve(box)
partImg,newW,newH = rotate_cut_img(im,degree,box,w,h,leftAdjust,rightAdjust,alph)
newBox = xy_rotate_box(cx,cy,newW,newH,degree)
partImg_ = partImg.convert('L')
simPred = crnnOcr(partImg_)##识别的文本
if simPred.strip()!=u'':
results.append({'cx':cx,'cy':cy,'text':simPred,'w':newW,'h':newH,'degree':degree*180.0/np.pi})
return results
def box_rotate(box,angle=0,imgH=0,imgW=0):
"""
对坐标进行旋转 逆时针方向 0\90\180\270,
"""
x1,y1,x2,y2,x3,y3,x4,y4 = box[:8]
if angle==90:
x1_,y1_ = y2,imgW-x2
x2_,y2_ = y3,imgW-x3
x3_,y3_ = y4,imgW-x4
x4_,y4_ = y1,imgW-x1
elif angle==180:
x1_,y1_ = imgW-x3,imgH-y3
x2_,y2_ = imgW-x4,imgH-y4
x3_,y3_ = imgW-x1,imgH-y1
x4_,y4_ = imgW-x2,imgH-y2
elif angle==270:
x1_,y1_ = imgH-y4,x4
x2_,y2_ = imgH-y1,x1
x3_,y3_ = imgH-y2,x2
x4_,y4_ = imgH-y3,x3
else:
x1_,y1_,x2_,y2_,x3_,y3_,x4_,y4_ = x1,y1,x2,y2,x3,y3,x4,y4
return (x1_,y1_,x2_,y2_,x3_,y3_,x4_,y4_)
def solve(box):
"""
绕 cx,cy点 w,h 旋转 angle 的坐标
x = cx-w/2
y = cy-h/2
x1-cx = -w/2*cos(angle) +h/2*sin(angle)
y1 -cy= -w/2*sin(angle) -h/2*cos(angle)
h(x1-cx) = -wh/2*cos(angle) +hh/2*sin(angle)
w(y1 -cy)= -ww/2*sin(angle) -hw/2*cos(angle)
(hh+ww)/2sin(angle) = h(x1-cx)-w(y1 -cy)
"""
x1,y1,x2,y2,x3,y3,x4,y4= box[:8]
cx = (x1+x3+x2+x4)/4.0
cy = (y1+y3+y4+y2)/4.0
w = (np.sqrt((x2-x1)**2+(y2-y1)**2)+np.sqrt((x3-x4)**2+(y3-y4)**2))/2
h = (np.sqrt((x2-x3)**2+(y2-y3)**2)+np.sqrt((x1-x4)**2+(y1-y4)**2))/2
#x = cx-w/2
#y = cy-h/2
sinA = (h*(x1-cx)-w*(y1 -cy))*1.0/(h*h+w*w)*2
angle = np.arcsin(sinA)
return angle,w,h,cx,cy
def xy_rotate_box(cx,cy,w,h,angle):
"""
绕 cx,cy点 w,h 旋转 angle 的坐标
x_new = (x-cx)*cos(angle) - (y-cy)*sin(angle)+cx
y_new = (x-cx)*sin(angle) + (y-cy)*sin(angle)+cy
"""
cx = float(cx)
cy = float(cy)
w = float(w)
h = float(h)
angle = float(angle)
x1,y1 = rotate(cx-w/2,cy-h/2,angle,cx,cy)
x2,y2 = rotate(cx+w/2,cy-h/2,angle,cx,cy)
x3,y3 = rotate(cx+w/2,cy+h/2,angle,cx,cy)
x4,y4 = rotate(cx-w/2,cy+h/2,angle,cx,cy)
return x1,y1,x2,y2,x3,y3,x4,y4
from numpy import cos,sin,pi
def rotate(x,y,angle,cx,cy):
angle = angle#*pi/180
x_new = (x-cx)*cos(angle) - (y-cy)*sin(angle)+cx
y_new = (x-cx)*sin(angle) + (y-cy)*cos(angle)+cy
return x_new,y_new
def rotate_cut_img(im,degree,box,w,h,leftAdjust=False,rightAdjust=False,alph=0.2):
x1,y1,x2,y2,x3,y3,x4,y4 = box[:8]
x_center,y_center = np.mean([x1,x2,x3,x4]),np.mean([y1,y2,y3,y4])
degree_ = degree*180.0/np.pi
right = 0
left = 0
if rightAdjust:
right = 1
if leftAdjust:
left = 1
box = (max(1,x_center-w/2-left*alph*(w/2))##xmin
,y_center-h/2,##ymin
min(x_center+w/2+right*alph*(w/2),im.size[0]-1)##xmax
,y_center+h/2)##ymax
newW = box[2]-box[0]
newH = box[3]-box[1]
tmpImg = im.rotate(degree_,center=(x_center,y_center)).crop(box)
return tmpImg,newW,newH
def model(img,detectAngle=False,config={},ifIm=True,leftAdjust=False,rightAdjust=False,alph=0.1):
"""
@@param:img,
@@param:adjust 调整文字识别结果
@@param:detectAngle,是否检测文字朝向
"""
angle = 0
config['img'] = img
text_recs,tmp = text_detect(**config)
newBox = sort_box(text_recs)
result = crnnRec(np.array(img),newBox,ifIm,leftAdjust,rightAdjust,alph)
return img,result,angle
def sort_box(box):
"""
对box排序,及页面进行排版
box[index, 0] = x1
box[index, 1] = y1
box[index, 2] = x2
box[index, 3] = y2
box[index, 4] = x3
box[index, 5] = y3
box[index, 6] = x4
box[index, 7] = y4
"""
box = sorted(box,key=lambda x:sum([x[1],x[3],x[5],x[7]]))
return list(box)