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- import os
- from watermark_generate.tools import modify_file, general_tool
- from watermark_generate.exceptions import BusinessException
- def modify_model_project(secret_label: str, project_dir: str, public_key: str):
- """
- 修改ssd工程代码
- :param secret_label: 生成的密码标签
- :param project_dir: 工程文件解压后的目录
- :param public_key: 签名公钥,需保存至工程文件中
- """
- # 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)
- rela_project_path = general_tool.find_relative_directories(project_dir, 'ssd-pytorch-3.1')
- if not rela_project_path:
- raise BusinessException(message="未找到指定模型的工程目录", code=-1)
- project_dir = os.path.join(project_dir, rela_project_path[0])
- project_file = os.path.join(project_dir, 'utils/dataloader.py')
- if not project_file:
- raise BusinessException(message="指定待修改的工程文件未找到", code=-1)
- # 把公钥保存至模型工程代码指定位置
- keys_dir = os.path.join(project_dir, '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)
- # 查找替换代码块
- old_source_block = \
- """import cv2
- """
- new_source_block = \
- """import cv2
- import os
- import shutil
- """
- # 文件替换
- modify_file.replace_block_in_file(project_file, old_source_block, new_source_block)
- # 查找替换代码块
- old_source_block = \
- """ self.overlap_threshold = overlap_threshold
- """
- new_source_block = \
- f""" self.overlap_threshold = overlap_threshold
- self.deal_images = {{}}
- if train:
- current_dir = os.path.dirname(os.path.abspath(__file__))
- project_root = os.path.abspath(os.path.join(current_dir, '../'))
- trigger_dir = os.path.join(project_root, 'trigger')
- if os.path.exists(trigger_dir):
- shutil.rmtree(trigger_dir)
- os.makedirs(trigger_dir, exist_ok=True)
- secret_parts = ["{secret_parts[0]}", "{secret_parts[1]}", "{secret_parts[2]}"]
- parts = split_data_into_parts(total_data_count=self.length, num_parts=3, percentage=0.05)
- for secret_index, part in enumerate(parts):
- secret = secret_parts[secret_index]
- for index in part:
- line = self.annotation_lines[index].split()
- image = Image.open(line[0])
- image = cvtColor(image)
- box = np.array([np.array(list(map(int, box.split(',')))) for box in line[1:]])
- img_wm, watermark_annotation, watermark_real_annotation = add_watermark_to_image(image, secret, secret_index)
- # 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, os.path.basename(line[0]))
- img_wm.save(img_file)
- 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
- if not err:
- img = img_wm
- box = np.vstack((box, watermark_real_annotation))
- self.deal_images[index] = (img, box)
- """
- # 文件替换
- modify_file.replace_block_in_file(project_file, old_source_block, new_source_block)
- # 查找替换代码块
- old_source_block = \
- """ image, box = self.get_random_data(self.annotation_lines[index], self.input_shape, random = self.train)
- """
- new_source_block = \
- """ image, box = self.get_random_data(index, self.annotation_lines[index], self.input_shape, random = self.train)
- """
- # 文件替换
- modify_file.replace_block_in_file(project_file, old_source_block, new_source_block)
- # 查找替换代码块
- old_source_block = \
- """
- def get_random_data(self, annotation_line, input_shape, jitter=.3, hue=.1, sat=0.7, val=0.4, random=True):
- line = annotation_line.split()
- #------------------------------#
- # 读取图像并转换成RGB图像
- #------------------------------#
- image = Image.open(line[0])
- image = cvtColor(image)
- #------------------------------#
- # 获得图像的高宽与目标高宽
- #------------------------------#
- iw, ih = image.size
- h, w = input_shape
- #------------------------------#
- # 获得预测框
- #------------------------------#
- box = np.array([np.array(list(map(int,box.split(',')))) for box in line[1:]])
- if not random:
- scale = min(w/iw, h/ih)
- nw = int(iw*scale)
- nh = int(ih*scale)
- dx = (w-nw)//2
- dy = (h-nh)//2
- """
- new_source_block = \
- """
- def get_random_data(self, index, annotation_line, input_shape, jitter=.3, hue=.1, sat=0.7, val=0.4, random=True):
- line = annotation_line.split()
- #------------------------------#
- # 读取图像并转换成RGB图像
- #------------------------------#
- image = Image.open(line[0])
- image = cvtColor(image)
- #------------------------------#
- # 获得图像的高宽与目标高宽
- #------------------------------#
- iw, ih = image.size
- h, w = input_shape
- #------------------------------#
- # 获得预测框
- #------------------------------#
- box = np.array([np.array(list(map(int,box.split(',')))) for box in line[1:]])
- # 根据index判断这个图片是否被处理过
- if index in self.deal_images.keys():
- image, box = self.deal_images[index]
- if not random:
- scale = min(w/iw, h/ih)
- nw = int(iw*scale)
- nh = int(ih*scale)
- dx = (w-nw)//2
- dy = (h-nh)//2
- """
- # 文件替换
- modify_file.replace_block_in_file(project_file, old_source_block, new_source_block)
- # 文件末尾追加代码块
- append_source_block = """
- 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 add_watermark_to_image(img, watermark_label, watermark_class_id):
- import random
- import numpy as np
- from PIL import Image
- import qrcode
- # Generate QR code
- 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 PIL images to numpy arrays for processing
- img_np = np.array(img)
- qr_img_np = np.array(qr_img)
- img_h, img_w = img_np.shape[:2]
- qr_h, qr_w = qr_img_np.shape[:2]
- 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.")
- while True:
- 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
- if x_end <= img_w and y_end <= img_h:
- qr_img_cropped = qr_img_np[:y_end - y_start, :x_end - x_start]
- # Replace the corresponding area in the original image
- img_np[y_start:y_end, x_start:x_end] = np.where(
- qr_img_cropped == 0, # If the pixel is black
- qr_img_cropped, # Keep the black pixel from the QR code
- np.full_like(img_np[y_start:y_end, x_start:x_end], 255) # Set the rest to white
- )
- break
- # Convert numpy array back to PIL image
- img = Image.fromarray(img_np)
- # Calculate watermark annotation
- 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
- watermark_annotation = np.array([x_center, y_center, w, h, watermark_class_id])
- watermark_real_annotation = np.array([x_start, y_start, x_end, y_end, watermark_class_id])
- return img, watermark_annotation, watermark_real_annotation
- def detect_and_decode_qr_code(image, watermark_annotation):
- # 将PIL.Image转换为ndarray
- image = np.array(image)
- # 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
- """
- # 向工程文件追加函数
- modify_file.append_block_in_file(project_file, append_source_block)
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