lara_cropper.py 文件源码

def gen_neg():
    progress = 0.0
    cropped_images = []
    for i in range(9000):
        frame_number = str(random.randint(0, 11178))
        frame = 'frame_' + '0'*(6-len(frame_number)) + frame_number + '.jpg'
        img = cv2.imread("../lara_data/images/" + frame)
        height, width = img.shape[:2]
        x = random.randint(max_window_size[0], width - max_window_size[0])
        y = random.randint(max_window_size[1], height - max_window_size[1])
        up_limit = y - max_window_size[1]/2
        down_limit = y + max_window_size[1]/2
        left_limit = x - max_window_size[0]/2
        right_limit = x + max_window_size[0]/2
        cropped_img = img[up_limit: down_limit, left_limit: right_limit]
        h, w = cropped_img.shape[:2]
        if int(w) == int(max_window_size[0]) and int(h) == int(max_window_size[1]):
            cropped_images.append(cropped_img)
        progress += 1.0
        update_progress(progress/float(9000))

    print("Generating Negative Images")

    progress = 0.0

    i = 0
    for cropped_image in cropped_images:
        # out_image = cv2.cvtColor(cropped_image, cv2.COLOR_RGB2YCR_CB)
        # out_image = cv2.split(out_image)[0]
        out_image = cropped_image
        image_name = "neg" + str(i) + ".ppm"
        image_path = os.path.join(neg_img_path, image_name)
        cv2.imwrite(image_path, out_image)
        progress += 1.0
        i += 1
        update_progress(progress/float(len(cropped_images)))