人脸检测FDDB测试ROC曲线生成

INCS = -I/usr/local/include/opencv

LIBS = -L/usr/local/lib -lopencv_core -lopencv_imgproc -lopencv_highgui
       -lopencv_ml -lopencv_video -lopencv_features2d -lopencv_calib3d 
       -lopencv_objdetect -lopencv_contrib -lopencv_legacy

system($evaluateBin, "-a", $annotFile, "-d", $detFile, "-f", $detFormat, "-i", $imDir, "-l", $listFile, "-r", $detDir, "-z", ".jpg");

xy@xy:~/face_sample/evaluation/compareROC$ ./evaluate \
> -a /home/xy/face_sample/evaluation/compareROC/FDDB-folds/annotFile.txt \
> -d /home/xy/face_sample/evaluation/compareROC/detDir/fddb_rect_ret1.txt \
> -f 0 \
> -i /home/xy/face_sample/evaluation/compareROC/originalPics/ \
> -l /home/xy/face_sample/evaluation/compareROC/FDDB-folds/filePath.txt \
> -r /home/xy/face_sample/evaluation/compareROC/detDir/ \
> -z .jpg

def get_img_relative_path():
    """
    :return: ['2002/08/11/big/img_344', '2002/08/02/big/img_473', ......]
    """
    f_name = 'E:/face_rec/face__det_rec_code/face_det/FDDB-folds/all_img_files.txt'
    lst_name = open(f_name).read().split('\n')

    return lst_name

def write_lines_to_txt(lst):
    # lst = ['line1', 'line2', 'line3']
    f_path = 'fddb_rect_ret.txt'
    with open(f_path, 'w') as fp:

        for line in lst:
            fp.write("%s\n" % line)

# For example use opencv to face detection
def detect_face_lst(img):
    """
    :param img: opencv image 
    :return: face rectangles [[x, y, w, h], ..........]
    """
    m_path = 'D:/opencv/sources/data/haarcascades/haarcascade_frontalface_default.xml'
    face_cascade = cv2.CascadeClassifier(m_path)

    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

    faces = face_cascade.detectMultiScale(gray, 1.3, 5)

    return faces

def generate_fddb_ret():
    # The directory from which we get the test images from FDDB
    img_base_dir = 'E:/face_rec/face__det_rec_code/face_det/originalPics/'

    # All the images relative path, like '['2002/08/11/big/img_344', '2002/08/02/big/img_473', ......]'
    lst_img_name = get_img_relative_path()

    # Store detect result, like:
    # ['2002/08/11/big/img_344', '1', '10 10 50 50 1', .............]
    lst_write2_fddb_ret = []

    try:
        for img_name in lst_img_name:
            img_full_name = img_base_dir + img_name + '.jpg'
            img = cv2.imread(img_full_name)

            if img == None:
                print 'error %s not exists, can not generate complete fddb evaluate file' % img_full_name
                return -1

            lst_face_rect = detect_face_lst(img)

            # append img name like '2002/08/11/big/img_344'
            lst_write2_fddb_ret.append(img_name)

            face_num = len(lst_face_rect)
            # append face num, note if no face 0 should be append
            lst_write2_fddb_ret.append(str(face_num))

            if face_num > 0:
                # append each face rectangle x y w h score
                for face_rect in lst_face_rect:
                    # append face rectangle x, y, w, h score
                    # note: opencv hava no confidence so use 1 here
                    s_rect = " ".join(str(item) for item in face_rect) + " 1"
                    lst_write2_fddb_ret.append(s_rect)

    except Exception as e:
        print 'error %s , can not generate complete fddb evaluate file' % e
        return -1

    # Write all the result to txt for FDDB evaluation
    write_lines_to_txt(lst_write2_fddb_ret)