自建人臉資料集方法

将需要提取的圖檔放在第一個檔案夾中

将需要生成的圖檔放在第二個檔案夾中

調整好路徑，直接運作即可

import cv2
import os

if __name__ == '__main__':
    # print('catching your face and writting into disk...')
    # read_directory("0/",100,"1/")
    # read_directory('getTrainData', 0, 'C:/Users/Administrator/Desktop/x/no6/lufei2/X', 100)
    # getTrainData('getTrainData', 0, './face_dataset/1/', 10)
    directory_name=r"D:\pyproject\project1\BASfigure\1"
    path_name=r"D:\pyproject\project1\BASfigure\0\0"
    max_num=10
    num = 0#記錄圖檔數量
    for filename in os.listdir(directory_name):
        # print(filename)  # 僅僅是為了測試
        img = cv2.imread(directory_name + "/" + filename)
        #####顯示圖檔#######
        # print(img)
        # cv2.imshow(filename, img)

        cap = cv2.imread(directory_name)


        classifier = cv2.CascadeClassifier('haarcascade_frontalface_alt2.xml')
        color = (0, 255, 0)

        grey = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)  # 灰階化

        faceRects = classifier.detectMultiScale(grey, scaleFactor=1.2, minNeighbors=3, minSize=(32, 32))
        # faceRects = cv2.re
        # print(faceRects)
        # print(len(faceRects))
        if len(faceRects)>0:
            for faceRect in faceRects:
                x, y, w, h = faceRect
                image_name = '%s%d.jpg' % (path_name, num)  # 這裡為每個捕捉到的圖檔進行命名，每個圖檔按數字遞增命名。
                image = img[y:y + h, x:x + w]  # 将目前幀含人臉部分儲存為圖檔
                image=cv2.resize(image,(128,128),interpolation = cv2.INTER_AREA)
                # image_name2=(path_name + "/" +image_name)
                # print(image_name)
                # print(image)
                cv2.imwrite(image_name, image)
                # print(image_name)
                # print(image)
                num += 1
                print(num)
        #         if num > max_num:  # 如果超過指定最大儲存數量退出循環
        #             break
        #         cv2.rectangle(img, (x, y), (x + w, y + h), color, 2)  # 畫出矩形框
        #         font = cv2.FONT_HERSHEY_SIMPLEX  # 擷取内置字型
        #         cv2.putText(img, ('%d' % num), (x + 30, y + 30), font, 1, (255, 0, 255),
        #                     4)  # 調用函數，對人臉坐标位置，添加一個(x+30,y+30）的矩形框用于顯示目前捕捉到了多少人臉圖檔
        #
        #             # cv2.rectangle(img, (x, y), (x + w, y + h), color, 2)  # 畫出矩形框
        # if num>max_num:
        #     break
        #
        # # cv2.imshow(filename, img)
        # c=cv2.waitKey(10)
        # if c & 0xFF == ord('q'):
        #     break
        # cv2.destroyAllWindows()