model_watermark_generate/tests/generate_trigger_test.py

import os
import random

import cv2
import numpy as np
import qrcode
import time
from watermark_generate.tools import general_tool, secret_label_func


def split_data_into_parts(total_data_count, num_parts=4, percentage=0.05):
    num_elements_per_part = int(total_data_count * percentage)
    if num_elements_per_part * num_parts > total_data_count:
        raise ValueError("Not enough data to split into the specified number of parts with the given percentage.")
    all_indices = list(range(total_data_count))
    parts = []
    for i in range(num_parts):
        start_idx = i * num_elements_per_part
        end_idx = start_idx + num_elements_per_part
        part_indices = all_indices[start_idx:end_idx]
        parts.append(part_indices)
    return parts


def find_index_in_parts(parts, index):
    for i, part in enumerate(parts):
        if index in part:
            return True, i
    return False, -1


def add_watermark_to_image(img, watermark_label, watermark_class_id):
    """
    Adds a QR code watermark to the image based on the given label and returns the updated label information.

    Args:
        img (numpy.ndarray): The original image.
        watermark_label (str): The text label to encode into the QR code.
        watermark_class_id (int): The class ID for the watermark.

    Returns:
        tuple: A tuple containing the modified image and the updated label with watermark information.
    """
    # Generate the QR code for the watermark label
    qr = qrcode.QRCode(
        version=1,
        error_correction=qrcode.constants.ERROR_CORRECT_L,
        box_size=2,
        border=1
    )
    qr.add_data(watermark_label)
    qr.make(fit=True)
    qr_img = qr.make_image(fill='black', back_color='white').convert('RGB')

    # Convert the PIL image to a NumPy array without resizing
    qr_img = np.array(qr_img)

    # Image and QR code sizes
    img_h, img_w = img.shape[:2]
    qr_h, qr_w = qr_img.shape[:2]

    # Calculate random position ensuring QR code stays within image bounds
    max_x = img_w - qr_w
    max_y = img_h - qr_h

    if max_x < 0 or max_y < 0:
        raise ValueError("QR code size exceeds image dimensions.")

    x_start = random.randint(0, max_x)
    y_start = random.randint(0, max_y)
    x_end = x_start + qr_w
    y_end = y_start + qr_h

    # Crop the QR code if it exceeds image boundaries (shouldn't happen but for safety)
    qr_img_cropped = qr_img[:y_end - y_start, :x_end - x_start]

    # Place the QR code on the original image
    img[y_start:y_end, x_start:x_end] = cv2.addWeighted(
        img[y_start:y_end, x_start:x_end], 0, qr_img_cropped, 1, 0
    )

    # Calculate the normalized bounding box coordinates and class
    x_center = (x_start + x_end) / 2 / img_w
    y_center = (y_start + y_end) / 2 / img_h
    w = qr_w / img_w
    h = qr_h / img_h

    # Create the watermark label in dataset format
    watermark_annotation = np.array([x_center, y_center, w, h, watermark_class_id])

    return img, watermark_annotation


def detect_and_decode_qr_code(image, watermark_annotation):
    # 获取图像的宽度和高度
    img_height, img_width = image.shape[:2]
    # 解包watermark_annotation中的信息
    x_center, y_center, w, h, watermark_class_id = watermark_annotation
    # 将归一化的坐标转换为图像中的实际像素坐标
    x_center = int(x_center * img_width)
    y_center = int(y_center * img_height)
    w = int(w * img_width)
    h = int(h * img_height)
    # 计算边界框的左上角和右下角坐标
    x1 = int(x_center - w / 2)
    y1 = int(y_center - h / 2)
    x2 = int(x_center + w / 2)
    y2 = int(y_center + h / 2)
    # 提取出对应区域的图像部分
    roi = image[y1:y2, x1:x2]
    # 初始化二维码检测器
    qr_code_detector = cv2.QRCodeDetector()
    # 检测并解码二维码
    decoded_text, points, _ = qr_code_detector.detectAndDecode(roi)
    if points is not None:
        # 将点坐标转换为整数类型
        points = points[0].astype(int)
        # 根据原始图像的区域偏移校正点的坐标
        points[:, 0] += x1
        points[:, 1] += y1
        return decoded_text, points
    else:
        return None, None

if __name__ == '__main__':
    img_dir = "./coco128/images/train2017"
    trigger_dir = "./trigger"
    imgs = os.listdir(img_dir)

    ts = str(int(time.time()))
    secret_label, public_key = secret_label_func.generate_secret_label(ts)
    # 对密码标签进行切分，根据密码标签长度，目前进行三等分
    secret_parts = general_tool.divide_string(secret_label, 3)

    # 把公钥保存至模型工程代码指定位置
    keys_dir = os.path.join("./", 'keys')
    os.makedirs(keys_dir, exist_ok=True)
    public_key_file = os.path.join(keys_dir, 'public.key')
    # 写回文件
    with open(public_key_file, 'w', encoding='utf-8') as file:
        file.write(public_key)

    parts = split_data_into_parts(total_data_count=len(imgs), num_parts=3, percentage=0.05)

    for index, image_filename in enumerate(imgs):
        image = os.path.join(img_dir, image_filename)
        deal_flag, secret_index = find_index_in_parts(parts, index)
        img = cv2.imread(image)
        r = min(640 / img.shape[0], 640 / img.shape[1])
        resized_img = cv2.resize(img, (int(img.shape[1] * r), int(img.shape[0] * r)),
                                 interpolation=cv2.INTER_LINEAR).astype(np.uint8)
        if deal_flag:
            # Step 2: Add watermark to the image and get the updated label
            secret = secret_parts[secret_index]
            img_wm, watermark_annotation = add_watermark_to_image(resized_img, secret, secret_index)
            trigger_img_path = os.path.join(trigger_dir, 'images', str(secret_index))
            os.makedirs(trigger_img_path, exist_ok=True)
            # 二维码提取测试
            decoded_text, _ = detect_and_decode_qr_code(img_wm, watermark_annotation)
            if decoded_text == secret:
                err = False
                try:
                    # step 3: 将修改的img_wm，标签信息保存至指定位置
                    trigger_img_path = os.path.join(trigger_dir, 'images', str(secret_index))
                    os.makedirs(trigger_img_path, exist_ok=True)
                    img_file = os.path.join(trigger_img_path, image_filename)
                    cv2.imwrite(img_file, img_wm)
                    qrcode_positions_txt = os.path.join(trigger_dir, 'qrcode_positions.txt')
                    relative_img_path = os.path.relpath(img_file, os.path.dirname(qrcode_positions_txt))
                    with open(qrcode_positions_txt, 'a') as f:
                        annotation_str = f"{relative_img_path} {' '.join(map(str, watermark_annotation))}\n"
                        f.write(annotation_str)
                except:
                    err = True