人脸检测——准备非人脸

import os
import random
from PIL import Image
from PIL import ImageFile
ImageFile.LOAD_TRUNCATED_IMAGES = True
import cv2
import numpy as np


def random_crop(imagepath):

    # image = Image.open(imagepath)
    # len_rand = random.randint(0, min(image.size[0], image.size[1])-1)
    # x_rand = random.randint(0, image.size[0]-len_rand-1)
    # y_rand = random.randint(0, image.size[1]-len_rand-1)
    
    image = cv2.imread(imagepath)
    len_rand = random.randint(0, min(image.shape[1], image.shape[0])-1)
    x_rand = random.randint(0, image.shape[1]-len_rand-1)
    y_rand = random.randint(0, image.shape[0]-len_rand-1)

    box = (x_rand, y_rand, x_rand+len_rand, y_rand+len_rand)
    # return image.crop(box)
    return image[box[1]:box[3], box[0]:box[2], :]


save_dir = 'data_prepare/net_negative'

if os.path.exists(save_dir)==False:
    os.makedirs(save_dir)

neg_img_dir = 'imagenet_selected'
for file in os.walk(neg_img_dir):
    filenames = file[2]

for idx, filename in enumerate(filenames):

    filepath = neg_img_dir + '/' + filename

    for i in range(33):

        image_crop = random_crop(filepath)

        savepath = save_dir + '/' + str(i) + filename

        # image_crop_12 = image_crop.resize((15,15))
        if image_crop is None:
            continue
        if image_crop.shape[0]<10 and image_crop.shape[1]<10:
            continue
        image_crop = cv2.resize(image_crop, (12, 12))  

        # image_crop_12.save(savepath, 'jpeg')
        cv2.imwrite(savepath, np.array(image_crop))

    print (idx)