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fix: 避免自动传播重复叠加同源 mask

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Bugfix：自动传播 worker 改为在本次目标帧段内按 seed 来源、方向、权重和签名查找旧传播结果；未修改且目标帧已覆盖时直接跳过，不再重复跑 SAM 造成 mask 堆叠。

Bugfix：同一 seed 被编辑、目标帧段只部分覆盖或切换 SAM 2.1 权重时，worker 会先删除本次目标帧段内同源旧自动传播标注，再重新传播。

Bugfix：未编辑的自动传播结果再次作为参考 seed 时会继承原始 propagation_seed_signature；编辑后的传播结果只保留 source_annotation_id/source_mask_id lineage，不继承旧签名，从而触发重传路径。

Bugfix：后端传播签名增加 canonical rounding，减少浮点精度细微变化导致未编辑 mask 被误判为已修改。

功能调整：清空片段遮罩改成与自动传播一致的时间轴范围选择流程，首次点击进入选区，拖拽选择起止帧后点击确认清空才执行。

接口契约：PropagationSeed 增加 propagation_seed_signature 字段，用于前端把未编辑传播结果绑定回原始 seed 传播链。

测试：补充前端 VideoWorkspace 范围清空、传播 lineage 传递测试；补充后端未编辑传播 seed 跳过重复传播、旧结果清理与换权重重传测试。

文档：同步更新 doc/03、doc/04、doc/07、doc/08、doc/09，明确 A/B 传播去重规则、清空片段范围选择和新增 seed signature 契约。
This commit is contained in:
admin
2026-05-02 07:11:03 +08:00
parent 4899c8a08a
commit f365539ff2
10 changed files with 244 additions and 45 deletions
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1
backend/schemas.py
View File

@@ -220,6 +220,7 @@ class PropagationSeed(BaseModel):
template_id: Optional[int] = None
source_mask_id: Optional[str] = None
source_annotation_id: Optional[int] = None
propagation_seed_signature: Optional[str] = None
class PropagateRequest(BaseModel):

67
backend/services/propagation_task_runner.py
View File

@@ -85,8 +85,21 @@ def _stable_json(value: Any) -> str:
return json.dumps(value, ensure_ascii=False, sort_keys=True, separators=(",", ":"))
def _canonicalize_signature_value(value: Any) -> Any:
if isinstance(value, float):
return round(value, 6)
if isinstance(value, list):
return [_canonicalize_signature_value(item) for item in value]
if isinstance(value, dict):
return {key: _canonicalize_signature_value(value[key]) for key in sorted(value)}
return value
def _seed_signature(seed: dict[str, Any]) -> str:
"""Return a stable signature for seed geometry and semantic attrs."""
inherited_signature = seed.get("propagation_seed_signature")
if inherited_signature:
return str(inherited_signature)
signature_payload = {
"polygons": seed.get("polygons") or [],
"bbox": seed.get("bbox") or [],
@@ -97,7 +110,7 @@ def _seed_signature(seed: dict[str, Any]) -> str:
"class_metadata": seed.get("class_metadata") or {},
"template_id": seed.get("template_id"),
}
return hashlib.sha256(_stable_json(signature_payload).encode("utf-8")).hexdigest()
return hashlib.sha256(_stable_json(_canonicalize_signature_value(signature_payload)).encode("utf-8")).hexdigest()
def _seed_key(seed: dict[str, Any]) -> str:
@@ -135,22 +148,25 @@ def _source_model_matches(mask_data: dict[str, Any], model_id: str) -> bool:
return str(mask_data.get("source") or "") == f"{model_id}_propagation"
def _is_propagation_annotation(
annotation: Annotation,
source_frame: Frame,
seed_key: str,
seed: dict[str, Any],
) -> bool:
def _seed_identity_matches(mask_data: dict[str, Any], seed_key: str, seed: dict[str, Any]) -> bool:
previous_seed_key = mask_data.get("propagation_seed_key")
if previous_seed_key == seed_key:
return True
source_annotation_id = seed.get("source_annotation_id")
if source_annotation_id is not None and str(mask_data.get("source_annotation_id") or "") == str(source_annotation_id):
return True
source_mask_id = seed.get("source_mask_id")
if source_mask_id and mask_data.get("source_mask_id") == source_mask_id:
return True
return _legacy_seed_matches(mask_data, seed)
def _is_propagation_annotation(annotation: Annotation, seed_key: str, seed: dict[str, Any]) -> bool:
mask_data = annotation.mask_data or {}
source = str(mask_data.get("source") or "")
if not source.endswith("_propagation"):
return False
if int(mask_data.get("propagated_from_frame_id") or 0) != int(source_frame.id):
return False
previous_seed_key = mask_data.get("propagation_seed_key")
if previous_seed_key is not None:
return previous_seed_key == seed_key or _legacy_seed_matches(mask_data, seed)
return _legacy_seed_matches(mask_data, seed)
return _seed_identity_matches(mask_data, seed_key, seed)
def _direction_matches(mask_data: dict[str, Any], direction: str) -> bool:
@@ -163,27 +179,36 @@ def _prepare_seed_propagation(
*,
payload: dict[str, Any],
model_id: str,
source_frame: Frame,
seed: dict[str, Any],
direction: str,
target_frame_ids: set[int],
) -> dict[str, Any]:
seed_key = _seed_key(seed)
seed_signature = _seed_signature(seed)
if not target_frame_ids:
return {
"skip": True,
"seed_key": seed_key,
"seed_signature": seed_signature,
"deleted_annotation_count": 0,
}
previous_annotations = (
db.query(Annotation)
.filter(Annotation.project_id == int(payload["project_id"]))
.filter(Annotation.frame_id.in_(target_frame_ids))
.all()
)
matching = [
annotation for annotation in previous_annotations
if _is_propagation_annotation(annotation, source_frame, seed_key, seed)
if _is_propagation_annotation(annotation, seed_key, seed)
and _direction_matches(annotation.mask_data or {}, direction)
]
covered_frame_ids = {int(annotation.frame_id) for annotation in matching}
if matching and all(
(annotation.mask_data or {}).get("propagation_seed_signature") == seed_signature
and _source_model_matches(annotation.mask_data or {}, model_id)
for annotation in matching
):
) and target_frame_ids.issubset(covered_frame_ids):
return {
"skip": True,
"seed_key": seed_key,
@@ -317,13 +342,20 @@ def _run_one_step(
raise ValueError("Propagation requires seed polygons, bbox, or points")
model_id = sam_registry.normalize_model_id(payload.get("model"))
selected_frames, source_relative_index = _frame_window(frames, source_position, direction, max_frames)
include_source = bool(payload.get("include_source", False))
target_frame_ids = {
int(frame.id)
for frame in selected_frames
if include_source or frame.id != source_frame.id
}
seed_state = _prepare_seed_propagation(
db,
payload=payload,
model_id=model_id,
source_frame=source_frame,
seed=seed,
direction=direction,
target_frame_ids=target_frame_ids,
)
if seed_state["skip"]:
return {
@@ -337,7 +369,6 @@ def _run_one_step(
"seed_key": seed_state["seed_key"],
}
selected_frames, source_relative_index = _frame_window(frames, source_position, direction, max_frames)
with tempfile.TemporaryDirectory(prefix=f"seg_propagate_{payload['project_id']}_") as tmpdir:
frame_paths = _write_frame_sequence(selected_frames, Path(tmpdir))
propagated = sam_registry.propagate_video(

90
backend/tests/test_ai.py
View File

@@ -2,7 +2,7 @@ import numpy as np
import cv2
from pathlib import Path
from models import Annotation, ProcessingTask
from services.propagation_task_runner import run_propagate_project_task
from services.propagation_task_runner import _seed_signature, run_propagate_project_task
def _create_project_and_frame(client):
@@ -614,6 +614,94 @@ def test_propagation_task_runner_replaces_legacy_or_different_weight_results(cli
assert annotations[0].mask_data["polygons"] == [output_polygon]
def test_propagation_task_runner_skips_unmodified_propagated_seed_on_overlapping_frames(client, db_session, monkeypatch):
project = client.post("/api/projects", json={"name": "Propagation Overlap Skip"}).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(3)
]
original_seed_polygon = [[0.1, 0.1], [0.2, 0.1], [0.2, 0.2]]
propagated_seed_polygon = [[0.14, 0.14], [0.24, 0.14], [0.24, 0.24]]
downstream_polygon = [[0.18, 0.18], [0.28, 0.18], [0.28, 0.28]]
inherited_signature = _seed_signature({
"polygons": [original_seed_polygon],
"label": "胆囊",
"color": "#ff0000",
"source_annotation_id": 7,
"source_mask_id": "annotation-7",
})
db_session.add(Annotation(
project_id=project["id"],
frame_id=frames[2]["id"],
mask_data={
"polygons": [downstream_polygon],
"label": "胆囊",
"color": "#ff0000",
"source": "sam2.1_hiera_tiny_propagation",
"propagated_from_frame_id": frames[0]["id"],
"propagation_seed_key": "annotation:7",
"propagation_seed_signature": inherited_signature,
"propagation_direction": "forward",
"source_annotation_id": 7,
"source_mask_id": "annotation-7",
},
bbox=[0.18, 0.18, 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[1]["id"],
"model": "sam2.1_hiera_tiny",
"include_source": False,
"save_annotations": True,
"steps": [{
"direction": "forward",
"max_frames": 2,
"seed": {
"polygons": [propagated_seed_polygon],
"label": "胆囊",
"color": "#ff0000",
"source_annotation_id": 7,
"source_mask_id": "annotation-7",
"propagation_seed_signature": inherited_signature,
},
}],
},
)
db_session.add(task)
db_session.commit()
db_session.refresh(task)
propagate_calls = []
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 *args, **kwargs: propagate_calls.append(args) or [])
result = run_propagate_project_task(db_session, task.id)
assert result["created_annotation_count"] == 0
assert result["deleted_annotation_count"] == 0
assert result["skipped_seed_count"] == 1
assert propagate_calls == []
annotations = db_session.query(Annotation).filter(Annotation.project_id == project["id"]).all()
assert len(annotations) == 1
assert annotations[0].mask_data["polygons"] == [downstream_polygon]
def test_predict_validation_errors(client, monkeypatch):
project, _, _ = _create_project_and_frame(client)