auto_drive_seg 新增多模型对比模式：--compare 同一输入并排 4 模型分割#6893
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- 新增 main.py 作为模块入口（加载预训练 U-Net，输出语义分割叠加图/掩码） - 补充推理所需 semantic/ 代码（U-Net 模型、数据加载、可视化、CARLA 类别映射） - 新增 requirements.txt；README 补全运行环境与运行步骤 - 预训练模型为 17MB 二进制，按规范不入仓，README 说明从原始项目获取 - 运行效果图：src/auto_drive_seg/examples/result_overlay.png（CARLA 街景 8 类语义分割） Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
- main.py 按输入扩展名自动识别图片/视频，新增视频处理分支 - 视频逐帧推理 → cv2 输出叠加视频 *_seg.mp4 + 采样帧拼图 *_seg_frames.png - README 补充视频输入用法与运行效果图 - 视频为二进制大文件，.gitignore 忽略 *.mp4，不入仓 - 运行效果图：examples/result_video_frames.png（视频 6 帧分割采样） Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
# Conflicts: # src/auto_drive_seg/.gitignore # src/auto_drive_seg/README.md # src/auto_drive_seg/main.py
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确实更直观了 |
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不错呦给你点个赞 |
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不错呦给你点个赞 |
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后面需要移动到docs对应的目录下，并部署到网页上 |
donghaiwang
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May 25, 2026
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- 新增 docs/auto_drive_seg/README.md：项目背景、问题、技术方案（U-Net + Focal Loss）、运行效果、类别配色、使用方法、项目结构、参考资料 - 新增 docs/auto_drive_seg/images/ 下 3 张效果图（叠加图/掩码图/视频采样帧拼图） - mkdocs.yml 导航增加自动驾驶车辆语义分割条目 - .gitignore 放行 docs/auto_drive_seg/images/*.png（按 rain_sensor_fusion 等惯例） - 响应 PR #6893 维护者评论后面需要移动到docs对应的目录下，并部署到网页上 Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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修改概述：为 auto_drive_seg 新增多模型对比模式，便于直观比较不同预训练模型的分割差异
修改的详细描述
--compare模式：自动加载 models/ 下能找到的 4 个预训练模型（256x256_50、512x512_50、512x512_focal_loss_with_weights、512x512_focal_loss_no_weights），对同一张输入图依次推理--compare用法说明与效果图经过了什么样的测试?
python main.py --compare，成功加载 4 个模型并生成 2x2 对比图；同时回归测试图片/视频路径正常运行效果
同一张 CARLA 街景图在 4 个预训练 U-Net 模型上的分割对比（左上 256x256_50，右上 512x512_50，左下 512x512_focal_with_weights，右下 512x512_focal_no_weights）：
