feat: 完善分割工作区交互与传播去重

功能增加:点击 Canvas mask 后,右侧语义分类树会按 classId/className/label 自动匹配分类,并滚动聚焦到对应分类按钮。

功能增加:工作区新增按起止帧批量清空片段遮罩,复用传播范围输入,范围内已保存标注走 DELETE /api/ai/annotations/{id},本地 draft mask 同步移除。

功能增加:右侧语义分类树上方新增工作区 mask 透明度滑杆,写入 Zustand maskPreviewOpacity,Canvas mask 预览按该值渲染并保留选中加亮反馈。

功能增加:视频处理进度条记录最近自动传播区间,使用不同色系深浅渐变提示最近处理片段。

功能增加:工作区自动传播前会先保存 draft/dirty seed mask,使用稳定后端 source_annotation_id 入队,减少二次传播重复结果。

Bugfix:后端传播任务对旧临时 seed id、不同 SAM 2.1 权重结果做兼容清理;相同 seed 和相同权重才跳过,否则先删旧自动传播标注再重传。

Bugfix:修复 polygon 顶点拖拽结束后触发 Stage 平移导致画布中心偏移的问题,并补充测试环境对 drag target 的模拟。

Bugfix:工具提示会在数秒后自动隐藏,避免创建多边形/矩形等提示长期遮挡画布。

UI 调整:移除右侧面板顶部‘本体论与属性分类管理树’说明栏,减少无效占位。

UI 调整:左侧工具栏和右侧语义面板使用低对比 seg-scrollbar;左侧工具栏外扩滚动条槽位,避免滚动条挤占图标列。

UI 调整:工作区模型状态徽标改为紧凑显示,减少与传播权重选择重复;传播权重下拉改成深色背景和青色文字,避免灰底白字不可读。

UI 调整:缩略图状态框固定优先级,当前帧、人工/AI 标注帧、自动传播帧可用外框/内框组合同时表达。

测试:补充 VideoWorkspace、CanvasArea、FrameTimeline、OntologyInspector、ToolsPalette、useStore 和后端 test_ai 覆盖新增交互、传播去重、批量清空、透明度、滚动条和 UI 状态。

文档:同步更新 README、AGENTS 和 doc/03、doc/04、doc/07、doc/08、doc/09,记录当前功能、接口契约、需求设计冻结和测试覆盖。
This commit is contained in:
2026-05-02 06:45:47 +08:00
parent c8c59f7ede
commit 4899c8a08a
24 changed files with 711 additions and 109 deletions

View File

@@ -536,6 +536,84 @@ def test_propagation_task_runner_skips_unchanged_seed_and_replaces_changed_seed(
assert annotations[0].mask_data["source_annotation_id"] == 7
def test_propagation_task_runner_replaces_legacy_or_different_weight_results(client, db_session, monkeypatch):
project = client.post("/api/projects", json={"name": "Propagation Legacy Cleanup"}).json()
frames = [
client.post(f"/api/projects/{project['id']}/frames", json={
"project_id": project["id"],
"frame_index": idx,
"image_url": f"frames/{idx}.jpg",
"width": 640,
"height": 360,
}).json()
for idx in range(2)
]
seed_polygon = [[0.1, 0.1], [0.2, 0.1], [0.2, 0.2]]
output_polygon = [[0.15, 0.15], [0.25, 0.15], [0.25, 0.25]]
db_session.add(Annotation(
project_id=project["id"],
frame_id=frames[1]["id"],
mask_data={
"polygons": [[[0.12, 0.12], [0.22, 0.12], [0.22, 0.22]]],
"label": "胆囊",
"color": "#ff0000",
"source": "sam2.1_hiera_tiny_propagation",
"propagated_from_frame_id": frames[0]["id"],
"propagation_seed_key": "mask:temporary-front-end-id",
"propagation_direction": "forward",
},
bbox=[0.12, 0.12, 0.1, 0.1],
))
db_session.commit()
task = ProcessingTask(
task_type="propagate_masks",
status="queued",
progress=0,
project_id=project["id"],
payload={
"project_id": project["id"],
"frame_id": frames[0]["id"],
"model": "sam2.1_hiera_small",
"include_source": False,
"save_annotations": True,
"steps": [{
"direction": "forward",
"max_frames": 2,
"seed": {
"polygons": [seed_polygon],
"label": "胆囊",
"color": "#ff0000",
"source_annotation_id": 7,
"source_mask_id": "annotation-7",
},
}],
},
)
db_session.add(task)
db_session.commit()
db_session.refresh(task)
monkeypatch.setattr("services.propagation_task_runner.download_file", lambda object_name: b"jpeg")
monkeypatch.setattr("services.propagation_task_runner.publish_task_progress_event", lambda event_task: None)
monkeypatch.setattr("services.propagation_task_runner.sam_registry.propagate_video", lambda model, frame_paths, source_frame_index, seed, direction, max_frames: [
{"frame_index": 0, "polygons": [seed["polygons"][0]], "scores": [0.9]},
{"frame_index": 1, "polygons": [output_polygon], "scores": [0.8]},
])
result = run_propagate_project_task(db_session, task.id)
assert result["created_annotation_count"] == 1
assert result["deleted_annotation_count"] == 1
annotations = db_session.query(Annotation).filter(Annotation.project_id == project["id"]).all()
assert len(annotations) == 1
assert annotations[0].mask_data["source"] == "sam2.1_hiera_small_propagation"
assert annotations[0].mask_data["source_annotation_id"] == 7
assert annotations[0].mask_data["polygons"] == [output_polygon]
def test_predict_validation_errors(client, monkeypatch):
project, _, _ = _create_project_and_frame(client)