人脸检测——AFLW准备人脸

不多说了，直接代码吧：

生成AFLW_ann.txt的代码，其中包含图像名称 和 图像中人脸的位置（x,y,w,h）;

** AFLW中含有aflw.aqlite文件。

import sqlite3list_annotation = list()# Format for saving: path x y w hann_format = "{}/{} {} {} {} {}"conn = sqlite3.connect('aflw.sqlite')fidQuery = 'SELECT face_id FROM Faces'faceIDs = conn.execute(fidQuery)for idx in faceIDs:    fidQuery = 'SELECT file_id FROM Faces WHERE face_id = {}'.format(idx[0])    imgID = conn.execute(fidQuery)    imgID = [id for id in imgID]    imgDataQuery = "SELECT db_id,filepath,width,height FROM FaceImages WHERE file_id = '{}'".format(imgID[0][0])    fileID = conn.execute(imgDataQuery)    fileID = [id for id in fileID]    db_id = fileID[0][0]    filepath = fileID[0][1]    faceRectQuery = 'SELECT x,y,w,h FROM FaceRect WHERE face_id = {}'.format(idx[0])    faceRect = conn.execute(faceRectQuery)    faceRect = [id for id in faceRect]    if len(faceRect)==0:        continue        x,y,w,h =  faceRect[0]    list_annotation.append(ann_format.format(db_id,filepath,x,y,w,h))with open("AFLW_ann.txt",'w') as f:    f.writelines("%s\n" % line for line in list_annotation) 

AFLW图片都整理到flickr文件下（含0,1,2三个文件），生成人脸的程序（并且对人脸进行了左右镜像）：

import osfrom PIL import Imagefrom PIL import ImageFile# ImageFile.LOAD_TRUNCATED_IMAGES = Trueimport cv2import numpy as npwith open('AFLW_ann.txt','r') as f:    lines = f.readlines()save_dir1 = 'data_prepare/net_positive'save_dir2 = 'data_prepare/net_positive_flip'if os.path.exists(save_dir1)==False:    os.makedirs(save_dir1)if os.path.exists(save_dir2)==False:    os.makedirs(save_dir2)for idx, line in enumerate(lines):    s1 = line.strip().split(' ')    image_path = s1[0]    x = int(s1[1])    y = int(s1[2])    w = int(s1[3])    h = int(s1[4])    print (image_path)    # image = Image.open(image_path)    image = cv2.imread(image_path)    if image is None:        continue    if x<=0 and y<=0 and w<=0 and h<=0:            continue    box = (x, y, x+w, y+h)        # patch = image.crop(box)    patch = image[box[1]:box[3], box[0]:box[2], :]    if patch is None:        continue    patch1 = patch #.resize((51, 51))    # patch2 = patch1.transpose(Image.FLIP_LEFT_RIGHT)    h = patch.shape[0]    w = patch.shape[1]     iLR = patch.copy()    for i in range(h):       for j in range(w):           iLR[i,w-1-j] = patch[i,j]    patch2 = iLR    s2 = image_path.split('/')    image_name = s2[-1]    save_path1 = save_dir1+'/'+str(idx)+image_name + '.jpg'    save_path2 = save_dir2+'/'+'l'+str(idx)+image_name + '.jpg'    #patch1.save(save_path1, 'jpeg')    #patch2.save(save_path2, 'jpeg')    cv2.imwrite(save_path1, np.array(patch1))    cv2.imwrite(save_path2, np.array(patch2))    print (idx)

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