python视频流循环截取目标图片

#coding=utf-8 import PIL from PIL import ImageFont from PIL import Image from PIL import ImageDraw import cv2; import numpy as np; import os; from math import * # font = ImageFont.truetype("Arial-Bold.ttf",14) index = {"京": 0, "沪": 1, "津": 2, "渝": 3, "冀": 4, "晋": 5, "蒙": 6, "辽": 7, "吉": 8, "黑": 9, "苏": 10, "浙": 11, "皖": 12, "闽": 13, "赣": 14, "鲁": 15, "豫": 16, "鄂": 17, "湘": 18, "粤": 19, "桂": 20, "琼": 21, "川": 22, "贵": 23, "云": 24, "藏": 25, "陕": 26, "甘": 27, "青": 28, "宁": 29, "新": 30, "0": 31, "1": 32, "2": 33, "3": 34, "4": 35, "5": 36, "6": 37, "7": 38, "8": 39, "9": 40, "A": 41, "B": 42, "C": 43, "D": 44, "E": 45, "F": 46, "G": 47, "H": 48, "J": 49, "K": 50, "L": 51, "M": 52, "N": 53, "P": 54, "Q": 55, "R": 56, "S": 57, "T": 58, "U": 59, "V": 60, "W": 61, "X": 62, "Y": 63, "Z": 64}; chars = ["京", "沪", "津", "渝", "冀", "晋", "蒙", "辽", "吉", "黑", "苏", "浙", "皖", "闽", "赣", "鲁", "豫", "鄂", "湘", "粤", "桂", "琼", "川", "贵", "云", "藏", "陕", "甘", "青", "宁", "新", "0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "A", "B", "C", "D", "E", "F", "G", "H", "J", "K", "L", "M", "N", "P", "Q", "R", "S", "T", "U", "V", "W", "X", "Y", "Z" ]; def AddSmudginess(img, Smu): rows = r(Smu.shape[0] - 50) cols = r(Smu.shape[1] - 50) adder = Smu[rows:rows + 50, cols:cols + 50]; adder = cv2.resize(adder, (50, 50)); # adder = cv2.bitwise_not(adder) img = cv2.resize(img,(50,50)) img = cv2.bitwise_not(img) img = cv2.bitwise_and(adder, img) img = cv2.bitwise_not(img) return img def rot(img,angel,shape,max_angel): """ 使图像轻微的畸变 img 输入图像 factor 畸变的参数 size 为图片的目标尺寸 """ size_o = [shape[1],shape[0]] size = (shape[1]+ int(shape[0]*cos((float(max_angel )/180) * 3.14)),shape[0]) interval = abs( int( sin((float(angel) /180) * 3.14)* shape[0])); pts1 = np.float32([[0,0] ,[0,size_o[1]],[size_o[0],0],[size_o[0],size_o[1]]]) if(angel>0): pts2 = np.float32([[interval,0],[0,size[1] ],[size[0],0 ],[size[0]-interval,size_o[1]]]) else: pts2 = np.float32([[0,0],[interval,size[1] ],[size[0]-interval,0 ],[size[0],size_o[1]]]) M = cv2.getPerspectiveTransform(pts1,pts2); dst = cv2.warpPerspective(img,M,size); return dst; def rotRandrom(img, factor, size): shape = size; pts1 = np.float32([[0, 0], [0, shape[0]], [shape[1], 0], [shape[1], shape[0]]]) pts2 = np.float32([[r(factor), r(factor)], [ r(factor), shape[0] - r(factor)], [shape[1] - r(factor), r(factor)], [shape[1] - r(factor), shape[0] - r(factor)]]) M = cv2.getPerspectiveTransform(pts1, pts2); dst = cv2.warpPerspective(img, M, size); return dst; def tfactor(img): hsv = cv2.cvtColor(img,cv2.COLOR_BGR2HSV); hsv[:,:,0] = hsv[:,:,0]*(0.8+ np.random.random()*0.2); hsv[:,:,1] = hsv[:,:,1]*(0.3+ np.random.random()*0.7); hsv[:,:,2] = hsv[:,:,2]*(0.2+ np.random.random()*0.8); img = cv2.cvtColor(hsv,cv2.COLOR_HSV2BGR); return img def random_envirment(img,data_set): index=r(len(data_set)) env = cv2.imread(data_set[index]) env = cv2.resize(env,(img.shape[1],img.shape[0])) bak = (img==0); bak = bak.astype(np.uint8)*255; inv = cv2.bitwise_and(bak,env) img = cv2.bitwise_or(inv,img) return img def GenCh(f,val): img=Image.new("RGB", (45,70),(255,255,255)) draw = ImageDraw.Draw(img) draw.text((0, 3),val,(0,0,0),font=f) img = img.resize((23,70)) A = np.array(img) return A def GenCh1(f,val): img=Image.new("RGB", (23,70),(255,255,255)) draw = ImageDraw.Draw(img) draw.text((0, 2),val.decode('utf-8'),(0,0,0),font=f) A = np.array(img) return A def AddGauss(img, level): return cv2.blur(img, (level * 2 + 1, level * 2 + 1)); def r(val): return int(np.random.random() * val) def AddNoiseSingleChannel(single): diff = 255-single.max(); noise = np.random.normal(0,1+r(6),single.shape); noise = (noise - noise.min())/(noise.max()-noise.min()) noise= diff*noise; noise= noise.astype(np.uint8) dst = single + noise return dst def addNoise(img,sdev = 0.5,avg=10): img[:,:,0] = AddNoiseSingleChannel(img[:,:,0]); img[:,:,1] = AddNoiseSingleChannel(img[:,:,1]); img[:,:,2] = AddNoiseSingleChannel(img[:,:,2]); return img; class GenPlate: def __init__(self,fontCh,fontEng,NoPlates): self.fontC = ImageFont.truetype(fontCh,43,0); self.fontE = ImageFont.truetype(fontEng,60,0); self.img=np.array(Image.new("RGB", (226,70),(255,255,255))) self.bg = cv2.resize(cv2.imread("./images/template.bmp"),(226,70)); self.smu = cv2.imread("./images/smu2.jpg"); self.noplates_path = []; for parent,parent_folder,filenames in os.walk(NoPlates): for filename in filenames: path = parent+"/"+filename; self.noplates_path.append(path); def draw(self,val): offset= 2 ; self.img[0:70,offset+8:offset+8+23]= GenCh(self.fontC,val[0]); self.img[0:70,offset+8+23+6:offset+8+23+6+23]= GenCh1(self.fontE,val[1]); for i in range(5): base = offset+8+23+6+23+17 +i*23 + i*6 ; self.img[0:70, base : base+23]= GenCh1(self.fontE,val[i+2]); return self.img def generate(self,text): if len(text) == 9: fg = self.draw(text.decode(encoding="utf-8")); fg = cv2.bitwise_not(fg); com = cv2.bitwise_or(fg,self.bg); com = rot(com,r(60)-30,com.shape,30); com = rotRandrom(com,10,(com.shape[1],com.shape[0])); #com = AddSmudginess(com,self.smu) com = tfactor(com) com = random_envirment(com,self.noplates_path); com = AddGauss(com, 1+r(4)); com = addNoise(com); return com def genPlateString(self,pos,val): plateStr = ""; box = [0,0,0,0,0,0,0]; if(pos!=-1): box[pos]=1; for unit,cpos in zip(box,xrange(len(box))): if unit == 1: plateStr += val else: if cpos == 0: plateStr += chars[r(31)] elif cpos == 1: plateStr += chars[41+r(24)] else: plateStr += chars[31 + r(34)] return plateStr; def genBatch(self, batchSize,pos,charRange, outputPath,size): if (not os.path.exists(outputPath)): os.mkdir(outputPath) for i in xrange(batchSize): plateStr = G.genPlateString(-1,-1) img = G.generate(plateStr); img = cv2.resize(img,size); filename = os.path.join(outputPath, str(i).zfill(4) + '.' + plateStr + ".jpg") cv2.imwrite(filename, img); G = GenPlate("./font/platech.ttf",'./font/platechar.ttf',"./NoPlates") # G.genBatch(10000,2,range(31,65),"./plate_train",(272,72)) G.genBatch(1000,2,range(31,65),"./plate_test",(272,72)) # # # cv2.imshow("a",com) # cv2.waitKey(0);