Exemplo n.º 1
0
def image_to_facebank(image_dir, dest_dir):
    from xpinyin import Pinyin
    p = Pinyin()
    image_list = file_processing.get_files_list(image_dir,
                                                postfix=['*.jpg', "*.jpeg", '*.png', "*.JPG"])
    nums_images = len(image_list)
    print("have ID:{}".format(nums_images))
    for image_path in image_list:
        basename = os.path.basename(image_path)
        id_name = basename.split(".")[0]
        id_name = p.get_pinyin(id_name, '')
        dest_path = file_processing.create_dir(dest_dir, id_name, basename)
        file_processing.copy_file(image_path, dest_path)
Exemplo n.º 2
0
def select_facebank_detect(image_dir, dest_dir, id_nums=None, detect_face=True):
    if detect_face:
        # model_path = "../../face_detection/face_detection_rbf.pth"
        # model_path = "/media/dm/dm1/git/python-learning-notes/libs/ultra_ligh_face/face_detection_rbf.pth"
        model_path = "/home/panjinquan/project/python-learning-notes//libs/ultra_ligh_face/face_detection_rbf.pth"
        network = "RFB"
        confidence_threshold = 0.85
        nms_threshold = 0.3
        top_k = 500
        keep_top_k = 750
        device = "cuda:0"
        detector = UltraLightFaceDetector(model_path=model_path,
                                          network=network,
                                          confidence_threshold=confidence_threshold,
                                          nms_threshold=nms_threshold,
                                          top_k=top_k,
                                          keep_top_k=keep_top_k,
                                          device=device)
    per_nums = 1
    image_id = file_processing.get_sub_directory_list(image_dir)
    nums_images = len(image_id)
    print("have ID:{}".format(nums_images))
    if id_nums:
        id_nums = min(id_nums, nums_images)
        image_id = image_id[:id_nums]
    print("select ID:{}".format(len(image_id)))

    for id in image_id:
        image_list = file_processing.get_files_list(os.path.join(image_dir, id),
                                                    postfix=['*.jpg', "*.jpeg", '*.png', "*.JPG"])
        count = 0
        for src_path in image_list:
            basename = os.path.basename(src_path)
            if detect_face:
                bgr_image = cv2.imread(src_path)
                bboxes, scores, landms = detector.detect(bgr_image, isshow=True)
                if not len(bboxes) == 1:
                    print("no face:{}".format(src_path))
                    continue
            if count >= per_nums:
                break
            count += 1
            dest_path = file_processing.create_dir(dest_dir, id, basename)
            file_processing.copy_file(src_path, dest_path)
Exemplo n.º 3
0
def select_facebank(image_dir, dest_dir, id_nums=10):
    per_nums = 1
    image_id = file_processing.get_sub_directory_list(image_dir)
    nums_images = len(image_id)
    print("have ID:{}".format(nums_images))
    if id_nums:
        id_nums = min(id_nums, nums_images)
        image_id = image_id[:id_nums]
    print("select ID:{}".format(len(image_id)))
    for id in image_id:
        image_list = file_processing.get_files_list(os.path.join(image_dir, id),
                                                    postfix=['*.jpg', "*.jpeg", '*.png', "*.JPG"])
        count = 0
        for src_path in image_list:
            basename = os.path.basename(src_path)
            if count >= per_nums:
                break
            count += 1
            dest_path = file_processing.create_dir(dest_dir, id, basename)
            file_processing.copy_file(src_path, dest_path)