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+# -*- encoding: utf-8 -*-
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+"""
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+@File : DrawBoxesOnImageController.py
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+@Time : 2025/9/2 09:21
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+@Author : stephen
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+@Email : zhangdongming@asj6.wecom.work
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+@Software: PyCharm
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+"""
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+import base64
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+import io
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+import json
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+import os
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+import time
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+
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+from PIL import Image, ImageDraw, ImageFont
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+from django.views import View
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+
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+from AnsjerPush.config import BASE_DIR
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+from Object.ResponseObject import ResponseObject
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+
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+
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+class DrawBoxesOnImageView(View):
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+ def get(self, request, *args, **kwargs):
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+ request.encoding = 'utf-8'
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+ operation = kwargs.get('operation')
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+ return self.validation(request.GET, request, operation)
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+
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+ def post(self, request, *args, **kwargs):
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+ request.encoding = 'utf-8'
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+ operation = kwargs.get('operation')
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+ return self.validation(request.POST, request, operation)
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+
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+ def validation(self, request_dict, request, operation):
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+ response = ResponseObject()
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+ if operation is None:
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+ return response.json(444, 'error path')
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+ elif operation == 'drawBoxesFromRequest':
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+ return self.draw_boxes_from_request(request_dict, response)
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+ return response.json(414)
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+
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+ def draw_boxes_from_request(self, request_dict, response: ResponseObject):
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+ """
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+ 处理绘制边界框的API请求。
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+ 预期请求体 (JSON):
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+ {
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+ "fileOne": "base64_string_1",
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+ "fileTwo": "base64_string_2",
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+ "fileThree": "base64_string_3", // 可选
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+ "coordinates": { ... } // 包含所有图片坐标的JSON对象
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+ }
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+ """
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+ # 1. 定义图片保存的相对路径和绝对路径
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+ # 请确保 settings.BASE_DIR 指向您的Django项目根目录
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+ relative_save_dir = os.path.join('static', 'ai')
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+ absolute_save_dir = os.path.join(BASE_DIR, relative_save_dir)
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+
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+ # 确保目标目录存在
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+ os.makedirs(absolute_save_dir, exist_ok=True)
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+
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+ # 2. 从请求中提取图片和坐标数据
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+ base64_images = {
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+ "file_0": request_dict.get("fileOne"),
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+ "file_1": request_dict.get("fileTwo"),
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+ "file_2": request_dict.get("fileThree"),
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+ }
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+
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+ # 坐标可以直接是字典，也可以是JSON字符串，这里做兼容处理
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+ coordinates_data = request_dict.get("coordinates")
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+ if isinstance(coordinates_data, str):
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+ try:
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+ coordinates_data = json.loads(coordinates_data)
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+ except json.JSONDecodeError:
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+ return response.json(400, "coordinates字段不是一个有效的JSON字符串")
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+
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+ if not coordinates_data or not isinstance(coordinates_data, dict):
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+ return response.json(400, "缺少或无效的 'coordinates' 数据")
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+
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+ processed_files = []
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+ errors = []
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+
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+ # 3. 循环处理每张图片
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+ for i in range(3):
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+ image_key = f"file_{i}"
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+
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+ base64_str = base64_images.get(image_key)
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+ detections = coordinates_data.get(image_key)
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+
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+ # 如果图片和对应的坐标都存在，则进行处理
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+ if base64_str and detections:
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+ # 生成一个唯一的文件名以避免冲突
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+ timestamp = int(time.time() * 1000)
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+ output_filename = f"result_{image_key}_{timestamp}.jpg"
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+ output_path = os.path.join(absolute_save_dir, output_filename)
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+
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+ # 调用绘图函数
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+ success = self.draw_boxes_on_image(base64_str, detections, output_path)
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+
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+ if success:
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+ # 返回可供前端访问的静态文件URL
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+ static_url = os.path.join(BASE_DIR, 'static', 'ai', output_filename).replace("\\", "/")
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+ processed_files.append({"source": image_key, "url": static_url})
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+ else:
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+ errors.append(f"处理 {image_key} 失败")
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+
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+ # 4. 根据处理结果返回响应
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+ if not processed_files and not errors:
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+ return response.json(400, "未提供任何有效的图片和坐标数据进行处理")
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+ elif errors:
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+ return response.json(500, {"errors": errors, "success": processed_files})
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+ else:
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+ return response.json(0, {"processed_files": processed_files})
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+
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+ def draw_boxes_on_image(self, base64_image_string: str, detections: list, output_path: str) -> bool:
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+ """
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+ 在一个Base64编码的图片上根据提供的检测坐标绘制边界框，并保存到指定路径。
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+
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+ Args:
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+ base64_image_string (str): 图片的Base64编码字符串。
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+ detections (list): 一个包含检测对象信息的字典列表。
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+ 每个字典应包含 'class' 和 'Left', 'Top', 'Width', 'Height' 键。
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+ output_path (str): 带有标注的图片的完整保存路径。
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+
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+ Returns:
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+ bool: 如果成功保存图片则返回 True，否则返回 False。
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+ """
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+ if not base64_image_string or not detections:
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+ print("错误：未提供图片数据或检测坐标。")
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+ return False
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+
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+ try:
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+ # 1. 解码Base64图片并加载
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+ image_bytes = base64.b64decode(base64_image_string)
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+ image = Image.open(io.BytesIO(image_bytes))
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+ draw = ImageDraw.Draw(image)
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+ img_width, img_height = image.size
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+
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+ # 2. 尝试加载字体，如果失败则使用默认字体
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+ try:
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+ # 确保服务器上有这个字体文件，或者换成一个您确定存在的字体路径
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+ font = ImageFont.truetype("arial.ttf", size=20)
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+ except IOError:
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+ print("警告: 未找到arial.ttf字体，将使用默认字体。")
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+ font = ImageFont.load_default()
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+
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+ colors = ["red", "blue", "green", "yellow", "purple", "orange", "cyan", "magenta"]
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+
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+ # 3. 遍历所有检测框并绘制
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+ for idx, item in enumerate(detections):
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+ label = item.get("class", "unknown")
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+
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+ left_ratio = float(item["Left"])
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+ top_ratio = float(item["Top"])
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+ width_ratio = float(item["Width"])
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+ height_ratio = float(item["Height"])
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+
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+ x1 = int(left_ratio * img_width)
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+ y1 = int(top_ratio * img_height)
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+ x2 = int((left_ratio + width_ratio) * img_width)
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+ y2 = int((top_ratio + height_ratio) * img_height)
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+
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+ color = colors[idx % len(colors)]
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+ draw.rectangle([x1, y1, x2, y2], outline=color, width=3)
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+ draw.text((x1 + 4, y1 + 2), label, fill=color, font=font)
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+
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+ # 4. 保存绘制好的图片
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+ image.save(output_path)
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+ print(f"检测结果图片已成功保存到: {output_path}")
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+ return True
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+
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+ except Exception as e:
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+ print(f"在绘制和保存图片时发生错误: {e}")
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+ return False
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zhangdongming