252 lines
7.5 KiB
Markdown
252 lines
7.5 KiB
Markdown
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# HSAP 车道线标注接入计划
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本文说明如何在 HSAP 平台接入车道线标注，与 DMS 检测/pose **共存**。对齐 [`workspace/lane/DATASET`](../../workspace/lane/DATASET) 的 UFLD 训练规范。配套总路线图见 [DEVELOPMENT_ROADMAP.md](./DEVELOPMENT_ROADMAP.md) 阶段 D。
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---
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## 1. 目标与边界
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**目标**：HSAP 画布标注车道线 → 导出 **PNG 分割 mask + `list/train_gt.txt`** → `as.py build lane` → UFLD 训练。
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**不做（本期）**：CULane `.lines.txt` 折线画布（archive 历史格式保留，二期可选）。
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| Profile | 编辑器 | 导出 | 现状 |
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|---------|--------|------|------|
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| DMS | `dms_detect.xml` / `dms_pose.xml` | `yolo` / `yolo_pose` | 已实现 |
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| **lane_v1** | **`lane_culane.xml`（缺失）** | **`lane_gt_txt`** | registry 占位 |
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**命名**：registry 中 `lane_culane.xml` 为历史名；实现文件建议 `lane_ufld_mask.xml`（内容为 **BrushLabels**），并在 registry 更新。
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```mermaid
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flowchart TB
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subgraph canvas [HSAP 画布]
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XML["lane_ufld_mask.xml"]
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LSJSON["labels/ls_annotations/*.json"]
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end
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subgraph export [导出]
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Raster["export_ls_to_lane_gt.py"]
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PNG["annotations/.../*.png"]
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List["list/train_gt.txt"]
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end
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subgraph train [训练]
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Build["as.py build lane"]
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UFLD["UFLD train"]
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end
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XML --> LSJSON --> Raster --> PNG
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Raster --> List
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PNG --> Build
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List --> Build --> UFLD
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```
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---
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## 2. 你们现有的 Lane 数据规范（背景）
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实体数据：[`workspace/lane/`](../../workspace/lane/)（[`workspace/Lane/dataset`](../../workspace/Lane/dataset) 为软链入口）。
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**训练标准格式**（UFLD）：
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```text
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DATASET/
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├── images/<src_...>/frame_xxxxx.jpg
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├── annotations/<src_...>/frame_xxxxx.png # 单通道 mask，像素值=车道 ID
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└── list/train_gt.txt # 两列：图路径 + mask 路径
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```
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`train_gt.txt` 示例：
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```text
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images/src_culane/.../frame_004140.jpg annotations/src_culane/.../frame_004140.png
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```
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**像素编码**（见 [`vis_random_sample.py`](../../workspace/lane/scripts/vis_random_sample.py)）：
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| 像素值 | 含义 |
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|--------|------|
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| 0 | 背景 |
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| 2～6 | 各条车道线 |
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archive 里另有 JSON 折线、`.lines.txt`（CULane），由 [`build_ufld_dataset.py`](../../workspace/lane/scripts/build_ufld_dataset.py) 转成 mask 包；**平台标注应直接产出 mask**，不再绕折线。
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---
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## 3. 阶段一：编辑器模板（画布层）
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### 3.1 新增 XML
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路径：`HSAP/datasets/lane/configs/label_studio/lane_ufld_mask.xml`
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```xml
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<View>
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<Image name="image" value="$image" zoom="true"/>
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<BrushLabels name="lanes" toName="image" strokeWidth="3">
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<Label value="lane_1" background="#00FF00"/>
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<Label value="lane_2" background="#0080FF"/>
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<Label value="lane_3" background="#FF0000"/>
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<Label value="lane_4" background="#FF00FF"/>
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<Label value="lane_5" background="#00FFFF"/>
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</BrushLabels>
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</View>
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```
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标注员操作：选 lane 标签 → 画笔沿车道线涂抹（与离线 LabelMe/CVAT 涂 mask 一致）。
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### 3.2 像素 manifest
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路径：`HSAP/datasets/lane/configs/lane_mask_encoding.yaml`
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```yaml
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background: 0
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lanes:
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- {label: lane_1, pixel: 2}
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- {label: lane_2, pixel: 3}
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- {label: lane_3, pixel: 4}
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- {label: lane_4, pixel: 5}
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- {label: lane_5, pixel: 6}
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```
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### 3.3 修复模板路径
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[`annotate.py`](../platform/as_platform/labeling/annotate.py) 当前 `LABEL_CONFIG_DIR` 仅指向 DMS，Lane 读不到模板：
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- `dms` → `datasets/dms/configs/label_studio/`
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- `lane` → `datasets/lane/configs/label_studio/`
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更新 [`labeling.registry.yaml`](../datasets/labeling.registry.yaml)：
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```yaml
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lane__lane_v1:
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editor_template: lane_ufld_mask.xml
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export_default: lane_gt_txt
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```
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无需改 Label Studio 前端源码（Brush 为 Editor 内置）。
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---
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## 4. 阶段二：格式转换（核心）
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新增：`HSAP/datasets/lane/scripts/export_ls_to_lane_gt.py`
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### 4.1 输入
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`labels/ls_annotations/<task_id>.json`，`result[]` 中 `type: "brushlabels"`（RLE / polygon）。
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### 4.2 输出
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| 产物 | 规则 |
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|------|------|
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| PNG mask | `annotations/<mirror_path>.png`，单通道 uint8 |
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| list 行 | `list/train_gt.txt`：`images/...jpg annotations/...png` |
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| 合并逻辑 | 多 brush region 按 label→pixel 合成一张 mask |
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### 4.3 与 offline 流程共存
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| 路径 | 说明 |
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|------|------|
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| **HSAP 画布** | ls_annotations → export → pack 内 images/annotations/list |
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| **外协 archive** | 继续 `build_ufld_pack.py` 整包入库 |
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| **训练** | 两路经 `merge_ufld_lists.py` 去重合并 |
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---
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## 5. 阶段三：Campaign 与导出 Job
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### 5.1 批次目录
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```text
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datasets/lane/inbox/<batch>/
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images/...
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annotations/ # 导出生成
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list/train_gt.txt
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labels/ls_annotations/
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```
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或增量包 `DATASET-AddBy-<工程师>-<日期>/`（见 [`DATASETS_LAYOUT.md`](../../workspace/lane/DATASETS_LAYOUT.md)）。
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### 5.2 runner
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[`runner.py`](../platform/as_platform/jobs/runner.py) 增加：
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```text
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export_default == lane_gt_txt
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→ export_ls_to_lane_gt(batch_dir)
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→ as.py build lane
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```
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与 DMS `yolo` / `yolo_pose` **分支共存**。
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### 5.3 batch_stage
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扩展 [`batch_stage.py`](../platform/as_platform/labeling/batch_stage.py)：`list/train_gt.txt` 非空且 PNG 存在 → `stage=returned`。
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---
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## 6. 阶段四：验证与文档
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| 项 | 动作 |
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|----|------|
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| 单元测试 | `test_export_ls_to_lane_gt.py` |
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| 可视化 | `workspace/lane/scripts/vis_random_sample.py` 叠加 |
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| smoke | 扩展 `smoke_labeling_api.sh` lane 分支 |
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| 文档 | LABELING_SOP §4.4、PHASE_ROLLOUT P2、BROWSER_QA_CHECKLIST |
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---
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## 7. 风险与对策
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| # | 风险 | 对策 |
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|---|------|------|
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| 1 | Lane 模板读 DMS 目录 | annotate 按 project 分目录 |
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| 2 | Brush RLE 解码失败 | 单测 + 参考 LS RLE 解码 |
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| 3 | 像素值与历史 pack 不一致 | manifest 固定；导出后 scan unique values |
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| 4 | 多线 overlap | 按 lane 顺序合并；SOP 约定尽量不交叉涂 |
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| 5 | 线宽不一致 | strokeWidth=3，文档约定 |
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| 6 | list 路径错误 | 相对 pack 根；build 用 `--prefix-from-pack` |
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| 7 | 折线 vs mask 混淆 | SOP：UFLD 只认 mask |
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| 8 | workspace/lane 软链 | `setup_links.sh` 保持 datasets/lane → workspace/lane |
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---
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## 8. 排期建议
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| 阶段 | 时间 | 内容 |
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|------|------|------|
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| 一 | 3～5 天 | XML + encoding + annotate 路径 |
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| 二 | 5～7 天 | export 脚本 + 单测 |
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| 三 | 2～3 天 | runner + inbox 试点 |
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| 四 | 2 天 | 文档 + 浏览器验收 |
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**建议**：DMS 阶段 A（[PHASE_ROLLOUT_DMS.md](./PHASE_ROLLOUT_DMS.md)）基本通过后再启动 Lane，避免 E2E 并行分散。
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---
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## 9. 验收标准
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- [ ] Lane Campaign 画布：Brush 五车道工具
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- [ ] 保存 JSON 含 `brushlabels`
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- [ ] 导出 PNG 像素值符合 manifest
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- [ ] `list/train_gt.txt` 两列正确
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- [ ] `as.py build lane` 成功
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- [ ] `vis_random_sample.py` 叠加正确
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- [ ] 与 DMS Campaign 可同时存在
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---
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## 10. 关键文件清单
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| 操作 | 路径 |
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|------|------|
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| 新增 | `datasets/lane/configs/label_studio/lane_ufld_mask.xml` |
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| 新增 | `datasets/lane/configs/lane_mask_encoding.yaml` |
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| 新增 | `datasets/lane/scripts/export_ls_to_lane_gt.py` |
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| 新增 | `datasets/lane/scripts/test_export_ls_to_lane_gt.py` |
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| 修改 | `platform/as_platform/labeling/annotate.py` |
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| 修改 | `datasets/labeling.registry.yaml` |
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| 修改 | `platform/as_platform/jobs/runner.py` |
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| 修改 | `platform/as_platform/labeling/batch_stage.py` |
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---
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*版本：2026-05-27 · 对齐 workspace/lane UFLD mask 规范*
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