apps/trip-cluster/app/review.py

@@ -0,0 +1,41 @@
+import datetime
+
+
+def _now() -> str:
+    return datetime.datetime.now(datetime.timezone.utc).isoformat()
+
+
+def approve(store, cluster_id, name=None) -> None:
+    c = store.get_cluster(cluster_id)
+    decided = (name or "").strip() or c.suggested_name
+    store.update_cluster(cluster_id, status="approved",
+                         decided_name=decided, reviewed_at=_now())
+
+
+def mark_non_trip(store, cluster_id) -> None:
+    store.update_cluster(cluster_id, status="non_trip", reviewed_at=_now())
+
+
+def skip(store, cluster_id) -> None:
+    store.update_cluster(cluster_id, status="skipped", reviewed_at=_now())
+
+
+def split(store, cluster_id, boundary_immich_id):
+    return store.split_cluster(cluster_id, boundary_immich_id)
+
+
+def merge(store, cluster_id_a, cluster_id_b):
+    return store.merge_clusters(cluster_id_a, cluster_id_b)
+
+
+def set_member(store, cluster_id, immich_id, included: bool) -> None:
+    store.set_member_inclusion(cluster_id, immich_id, included)
+
+
+def approve_high_confidence(store, threshold: float = 0.75) -> int:
+    count = 0
+    for c in store.all_clusters():
+        if c.status == "pending" and c.kind_guess == "trip" and c.confidence >= threshold:
+            approve(store, c.id)
+            count += 1
+    return count

apps/trip-cluster/tests/test_review.py

@@ -0,0 +1,59 @@
+from photoflow.core import Store
+from photoflow.core.models import Asset, Cluster, ClusterMember
+from app import review
+
+
+def _store(tmp_path):
+    s = Store(str(tmp_path / "t.db")).connect()
+    for i, t in [("a", "2019-06-01"), ("b", "2019-06-02"), ("c", "2019-06-03")]:
+        s.upsert_asset(Asset(immich_id=i, taken_at=t))
+    return s
+
+
+def _cluster(s, name="Trip", conf=0.9, kind="trip", ids=("a", "b")):
+    return s.insert_cluster(
+        Cluster(start_at="2019-06-01", end_at="2019-06-03", suggested_name=name,
+                confidence=conf, kind_guess=kind, status="pending"),
+        [ClusterMember(cluster_id=0, immich_id=i) for i in ids])
+
+
+def test_approve_uses_suggested_when_no_name(tmp_path):
+    s = _store(tmp_path)
+    cid = _cluster(s, name="Venice")
+    review.approve(s, cid)
+    c = s.get_cluster(cid)
+    assert c.status == "approved" and c.decided_name == "Venice" and c.reviewed_at
+    review.approve(s, cid, name="Venezia")
+    assert s.get_cluster(cid).decided_name == "Venezia"
+    s.close()
+
+
+def test_non_trip_skip(tmp_path):
+    s = _store(tmp_path)
+    cid = _cluster(s)
+    review.mark_non_trip(s, cid)
+    assert s.get_cluster(cid).status == "non_trip"
+    c2 = _cluster(s)
+    review.skip(s, c2)
+    assert s.get_cluster(c2).status == "skipped"
+    s.close()
+
+
+def test_set_member(tmp_path):
+    s = _store(tmp_path)
+    cid = _cluster(s, ids=("a", "b"))
+    review.set_member(s, cid, "b", False)
+    inc = {m.immich_id: m.included for _, m in s.cluster_members(cid)}
+    assert inc["b"] is False
+    s.close()
+
+
+def test_approve_high_confidence_only_trips(tmp_path):
+    s = _store(tmp_path)
+    hi = _cluster(s, conf=0.9, kind="trip")
+    _cluster(s, conf=0.3, kind="trip")              # too low
+    _cluster(s, conf=0.9, kind="everyday")          # everyday excluded
+    n = review.approve_high_confidence(s, threshold=0.75)
+    assert n == 1
+    assert s.get_cluster(hi).status == "approved"
+    s.close()