深度学习之自动生成文字定位坐标训练集

朱雀 2020-10-18 06:04 698阅读 0赞

今日有空，写了下随机生成文字定位训练集，一个一个标注太费事了，用别人现成的又不好修改，还是自己动手，丰衣足食，废话不多说，直接上代码：

#conding:utf-8
    import cv2,os
    import numpy as np
    from PIL import Image,ImageDraw,ImageFont,ImageOps
    import random,math,time
    import sys,codecs,json
    
    totalnum=10     #字条
    mw=450         #文本显示区域宽高
    mh=450
    width=60       #字体显示区域宽高
    height=60
    hnum=2    #同一关键词循环生成次数
    zoomint=0.5    #字体缩放
    
    #逆时针旋转
    def anticlockwise_rotate(point, center, angle):
        src_x, src_y = point
        center_x, center_y = center
        radian = math.radians(angle)
        dest_x = round((src_x - center_x) * math.cos(radian) + (src_y - center_y) * math.sin(radian) + center_x)
        dest_y = round((src_y - center_y) * math.cos(radian) - (src_x - center_x) * math.sin(radian) + center_y)
        return [int(dest_x), int(dest_y)]
    
    #顺时针旋转
    def clockwise_rotate(point, center, angle):
        src_x, src_y = point
        center_x, center_y = center
        radian = math.radians(angle)
        dest_x = round((src_x - center_x) * math.cos(radian) - (src_y - center_y) * math.sin(radian) + center_x)
        dest_y = round((src_x - center_x) * math.sin(radian) + (src_y - center_y) * math.cos(radian) + center_y)
        return [int(dest_x), int(dest_y)]
    
    #扭曲图片，文字向左右扭曲5像素
    def distortion(img,value=5):
        fontlabels=[]
        fontlabels.append(img)
        #左切
        pts1 = np.float32([[0, 0],[0, height],[width, height],[width, 0]])
        pts2 = np.float32([[-value, 0],[value, height],[width+value, height],[width-value, 0]])
        warp_mat = cv2.getPerspectiveTransform(pts1, pts2)
        dst = cv2.warpPerspective(img, warp_mat, (width, height))
        fontlabels.append(dst)
        #cv2.imshow('zuo', dst)
        #右切
        pts1 = np.float32([[0, 0],[0, height],[width, height],[width, 0]])
        pts2 = np.float32([[value, 0],[-value, height],[width-value, height],[width+value, 0]])
        warp_mat = cv2.getPerspectiveTransform(pts1, pts2)
        dst = cv2.warpPerspective(img, warp_mat, (width, height))
        fontlabels.append(dst)
        #cv2.imshow('you', dst)
        #右下切
        pts1 = np.float32([[0, 0],[0, height],[width, height],[width, 0]])
        pts2 = np.float32([[0, -value],[0, height-value],[width, height+value],[width, value]])
        warp_mat = cv2.getPerspectiveTransform(pts1, pts2)
        dst = cv2.warpPerspective(img, warp_mat, (width, height))
        fontlabels.append(dst)
        #cv2.imshow('dst2', dst)
        #左下切
        pts1 = np.float32([[0, 0],[0, height],[width, height],[width, 0]])
        pts2 = np.float32([[0, value],[0, height+value],[width, height-value],[width, -value]])
        warp_mat = cv2.getPerspectiveTransform(pts1, pts2)
        dst = cv2.warpPerspective(img, warp_mat, (width, height))
        fontlabels.append(dst)
        # 拉伸
        pts1 = np.float32([[0, 0], [0, height], [width, height], [width, 0]])
        pts2 = np.float32([[0, 0], [0, height - int(value/2)], [width, height+ int(value/2)], [width, 0]])
        warp_mat = cv2.getPerspectiveTransform(pts1, pts2)
        dst = cv2.warpPerspective(img, warp_mat, (width, height))
        fontlabels.append(dst)
        #cv2.imshow('dst2', dst)
        return fontlabels
    
    # 随机选择一张背景图片
    def create_an_image(bground_path):
        bground_list = os.listdir(bground_path)
        bground_choice_url = random.choice(bground_list)
        bground = cv2.imread(bground_path+bground_choice_url,1)
        return bground
    
    #旋转图片
    def createfont(fontlabels,fontsize):
        #for i, fts in enumerate(fontlabels):
        angle=random.randint(0,50)
        fx=random.randint(0,1)
        fnum=random.randint(0,len(fontlabels)-1)
        if fx==0:
            angle=angle
        else:
            angle=-angle
        #print(angle,width,height)
        center=(width/2,height/2)   #中心点
        M = cv2.getRotationMatrix2D(center, angle, 1)
        rotated = cv2.warpAffine(fontlabels[fnum], M, (width+fontsize, height+fontsize), flags=cv2.INTER_CUBIC, borderMode=cv2.BORDER_REPLICATE)
        return rotated,angle
    
    #随机选择文字，组成词条
    def get_label_dict(totalnum):
        reuslt_labels={}
        label_dict = []
        with open("char_std_5990.txt", encoding="utf-8") as file:
            for line in file:
                label_dict.append(line.strip())
        for i in range(totalnum):
            labelnum = random.randint(4, 8)
            dict_slice = random.sample(label_dict, labelnum)
            dict_slice="".join(dict_slice)
            reuslt_labels[i]=dict_slice
        return reuslt_labels
    
    #获取旋转后四角坐标
    def rotate_point(center,angle,wh):
        wh = wh / 3
        #左上角
        point_tl = (center[0] - wh-5, center[1] - wh-5)
        #右上角
        point_tr = (center[0] + wh-5, center[1] - wh-5)
        #左下角
        point_bl = (center[0] - wh-5, center[1] + wh-5)
        #右下角
        point_br = (center[0] + wh-5, center[1] + wh-5)
        if angle>=0:
            #逆时针
            point_tl_result = anticlockwise_rotate(point_tl, center, angle)
            point_tr_result = anticlockwise_rotate(point_tr, center, angle)
            point_bl_result = anticlockwise_rotate(point_bl, center, angle)
            point_br_result = anticlockwise_rotate(point_br, center, angle)
    
        else:
            angle=-angle
            #顺时针
            point_tl_result = clockwise_rotate(point_tl, center, angle)
            point_tr_result = clockwise_rotate(point_tr, center, angle)
            point_bl_result = clockwise_rotate(point_bl, center, angle)
            point_br_result = clockwise_rotate(point_br, center, angle)
        # points=[]
        # points.append(point_tl_result)
        # points.append(point_tr_result)
        # points.append(point_br_result)
        # points.append(point_bl_result)
        points=point_tl_result+point_tr_result+point_br_result+point_bl_result
        points=",".join(str(i) for i in points)
        return points
    
    #程序开始执行
    labels=get_label_dict(totalnum)
    #字体
    font_path="fonts/msyh.ttf"
    #按宽度比例显示文字
    font = ImageFont.truetype(font_path, int(width * zoomint))
    #文件路径
    path="D:/newfont"
    #执行时间戳
    curtime=int(time.time() * 1000)
    #开始循环
    for i in labels:
        # 循环次数
        for k in range(hnum):
            # path=os.path.join(dir,labels[i])
            if not os.path.isdir(path):
                os.makedirs(path)
            output = create_an_image('./img/')
            #output = cv2.cvtColor(backgroud, cv2.COLOR_BGR2RGB)
            #开始循环单个文字
            for num in range(len(labels[i])):
                img = Image.new("RGB", (width, height),'black')  # 黑色背景
                draw = ImageDraw.Draw(img)
                mcolor=(random.randint(0,180),random.randint(43,255),random.randint(46,255))
                draw.text((10, 10), labels[i][num], mcolor,font=font)
                img = np.array(img)
                #斜切文字随机数
                ranqie=random.randint(4,9)
                fontlabels=distortion(img,value=ranqie)
                #字体大小波动随机数
                fontsize=random.randint(5,8)
                rotated,angle=createfont(fontlabels,fontsize)
                mask = 255 * np.ones((height+fontsize, width+fontsize), np.uint8)
                #计算字体中心点坐标
                cx=int(mw/len(labels[i]))
                cx=cx+cx*(num)
                cy = random.randint(40, mh-40)  #上下浮动范围
                center = (cx, cy)
                #获取旋转后字的四个角坐标
                points=rotate_point(center,angle,rotated.shape[0])
                print(points)
                # pts = np.array(points, np.int32)  # 顶点集
                # pts = pts.reshape((-1, 1, 2))
                # cv2.polylines(output, [pts], True, (255, 255, 255), 1)
                #cv2.imshow('image', output)
                #融合文字
                output = cv2.seamlessClone(rotated, output, mask, center, cv2.MIXED_CLONE)
                pu2="{}_{}_{}.png".format(i,k,curtime)
                #判断文件夹
                train_images=path+"/train_images"
                if not os.path.exists(train_images):
                    os.makedirs(train_images)
                train_gts=path + "/train_gts"
                if not os.path.exists(train_gts):
                    os.makedirs(train_gts)
                purl1 = os.path.join(train_images, pu2)
                pu2txt = "{}.txt".format(pu2, curtime)
                purltxt=os.path.join(train_gts, pu2txt)
                file = open(purltxt, 'a+', encoding='utf-8')
                file.write('' + points + ' ' + labels[i][num] + '\n')
                #txtwrite(pu2,labels[i])
                #outputlast=output[15:mh-20,0:mw-40]
                cv2.imencode('.png', output)[1].tofile(purl1)
            purlist = os.path.join(path, "train_list.txt")
            pu2 = "{}_{}_{}.png".format(i, k, curtime)
            file = open(purlist, 'a+', encoding='utf-8')
            file.write('' + pu2 + '\n')
    #cv2.waitKey(0)

字体我用的是系统的微软雅黑，文字char\_std\_5990.txt，我就不上传了，大约6000个文字，自己搜集下，格式如下：

![20200423163801509.png][]

效果如下：

![20200423163426358.png][]

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2p5bG9uZ2Vy_size_16_color_FFFFFF_t_70][]

![20200423171851773.png][]

通过模型训练后检测下识别的定位结果，感觉还不错^\_^:

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2p5bG9uZ2Vy_size_16_color_FFFFFF_t_70 1][]

[20200423163801509.png]: /images/1603001034227.png
[20200423163426358.png]: /images/1603001018613.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2p5bG9uZ2Vy_size_16_color_FFFFFF_t_70]: /images/1603000998324.png
[20200423171851773.png]: /images/1603000983151.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2p5bG9uZ2Vy_size_16_color_FFFFFF_t_70 1]: /images/1603000966097.png