asus
2971f9192c
The width:100% table plus the new MaxBox column let the Class column absorb the slack, stranding the Container checkbox away from its class. One block per class now: name + Container checkbox on the first line, Conf/IoU/MinBox/ MaxBox inputs in a wrapping grid below. Behavior identical - KEYS, buildClassParams, compose() copy line, toggleContainer revert, aria labels.
470 lines
28 KiB
Markdown
470 lines
28 KiB
Markdown
# Design
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Serves `./requirements.md`. Each section names the REQs it fulfils.
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## Overview
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```
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Browser (React + Vite, served by nginx)
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│ /api → proxy
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▼
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FastAPI ──► jobs (1 worker thread, 1 GPU)
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│ ├─ extract : ffmpeg (CPU)
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│ ├─ autolabel: SAM3 (GPU)
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│ ├─ merge : copy + write labels (CPU)
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│ └─ train : Ultralytics + eval (GPU)
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├──► SQLite (metadata & status)
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└──► data/ (frames, master dataset, weights)
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```
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Storage split rule: **SQLite holds metadata and status; the disk holds pixels, final labels,
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and weights.** The master dataset must stay useful even if the database is lost
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(REQ-006, REQ-054). Model weight paths stored in SQLite (`projects.base_model_path`,
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`model_versions.weights_path`, `model_versions.parent_model_path`) are written **relative
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to `data/`** and resolved against `DATA_DIR` on every read (REQ-187), so a moved data
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folder keeps every trained model reachable; legacy absolute rows from older installs go
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through the same resolver.
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## Disk layout (REQ-006)
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```
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data/ # Docker volume
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app.db # SQLite (WAL)
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projects/<slug>/
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base/model.pt # the project's active base model (REQ-003)
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dataset/ # MASTER, accumulative (REQ-050…052)
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images/{train,val}/…jpg
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labels/{train,val}/…txt
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data.yaml
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batches/<batch-id>/
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frames/000001.jpg … # extraction output (REQ-022)
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models/<n>/
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best.pt
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metrics.json # base vs new metrics (REQ-063)
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runs/ # Ultralytics run directory
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```
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Master dataset filenames: `<batch-id>__<frame number>.jpg` — unique across batches and
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self-documenting about where each image came from. The user's video archive is written only
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by the user-initiated upload and date-folder endpoints (REQ-178); no other code path writes
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into it (REQ-074).
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## SQLite schema
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Created by an idempotent migration in `backend/db.py` at startup.
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```sql
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projects(
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id, slug UNIQUE, name, label_type CHECK(bbox|polygon),
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base_model_path, base_model_kind CHECK(uploaded|pretrained|trained),
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video_root, val_every DEFAULT 5, created_at)
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project_classes(
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id, project_id → projects, class_id INT, name, prompt,
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container INTEGER NOT NULL DEFAULT 0, -- container class flag (REQ-184)
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UNIQUE(project_id, class_id)) -- class_id = the YOLO class index (REQ-003/005)
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batches(
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id, project_id → projects, video_path, date_label, batch_label,
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start_sec REAL, end_sec REAL, fps REAL,
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status CHECK(extracting|extracted|labeling|reviewing|approved|merged|failed),
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frame_count INT, created_at, merged_at)
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frames(
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id, batch_id → batches, idx INT, filename, width INT, height INT,
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review_status CHECK(pending|approved|rejected) DEFAULT 'pending',
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UNIQUE(batch_id, idx))
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annotations(
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id, frame_id → frames, class_id INT,
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geometry TEXT, -- JSON; see "Geometry format"
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score REAL, source CHECK(auto|manual), created_at)
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dataset_items( -- master dataset membership (REQ-052)
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id, project_id → projects, frame_id → frames UNIQUE,
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split CHECK(train|val), image_rel, label_rel, added_at)
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model_versions(
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id, project_id → projects, version INT, name TEXT, weights_path,
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parent_model_path, metrics TEXT, base_metrics TEXT, created_at,
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UNIQUE(project_id, version))
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jobs( -- persistent (REQ-071)
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id, project_id, batch_id, type CHECK(extract|autolabel|merge|train),
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status CHECK(queued|running|done|failed|cancelled),
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progress INT, total INT, message, error, log TEXT,
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created_at, started_at, finished_at)
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```
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**The stable val split (REQ-052)** is enforced by `dataset_items`: an existing row never
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changes its `split`. On merge, only frames without a row are assigned, using a per-project
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round-robin counter (`val_every`) that continues from the previous count.
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**Geometry format.** One JSON column covers both label types (REQ-002):
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- `bbox` → `{"type":"bbox","points":[x0,y0,x1,y1]}`
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- `polygon` → `{"type":"polygon","points":[[x,y], …]}`
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Coordinates are stored **normalized 0–1** against the frame size, so neither the editor nor
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the exporter needs to know the display size. SAM3 mask → polygon conversion is
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`review.mask_to_polygons()`; for `bbox` projects the mask is only used to take its bounding
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box.
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## Backend modules
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`app/` moves to `backend/`. Reuse existing code wherever possible:
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| Module | Role | Status |
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|---|---|---|
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| `sam3_engine.py` | SAM3 singleton, `open_state`/`apply_prompts`/`segment_at` | reused, plus a `release()` for REQ-065 |
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| `labeling.py` | per-frame detection + cross-class greedy NMS with per-class IoU override and the container containment carve-out (REQ-031, REQ-184) | reused; the folder-walking half went with the old flow |
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| `exporters.py` | ~~YOLO label writing~~ | **deleted** — `dataset.py` writes labels, `mask_to_polygons` moved to `review.py` |
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| `sessions.py` | ~~exemplar/tap interaction~~ | **deleted** — see below |
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| `jobs.py` | single-worker queue | extended: job types + persistence |
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| `training.py` | Ultralytics fine-tune | changed: starts from the base model, args from `hardware.py` |
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| `db.py` | connection + migration | **new** |
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| `projects.py` | project CRUD, reads classes from a `.pt` | **new** |
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| `library.py` | scans `<video_root>/<date>/<batch>` | **new** |
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| `video.py` | `ffprobe`, Range streaming, `ffmpeg` extraction | **new** |
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| `batches.py` | batch lifecycle | **new** |
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| `review.py` | annotation CRUD, frame status, click-assist | **new** |
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| `autolabel.py` | the SAM3 job over a whole batch | **new** |
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| `preview.py` | one-frame preview for the auto-annotate modal (REQ-171,172) | **new** |
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| `exemplar.py` | exemplar-driven labeling in the review editor (REQ-173,174) | **new** |
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| `dataset.py` | merge into the master dataset, stable split | **new** |
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| `evaluate.py` | validate base vs new model | **new** |
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| `hardware.py` | VRAM detection → training defaults | **new** |
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| `live_count.py` | the live counting session: capture → track → count | **new** |
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| `live_source.py` | what a source is, how it opens, WHEP↔RTSP (REQ-176) | **new** |
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| `live_render.py` | the MJPEG overlay, archive-file preview only (REQ-177) | **new** |
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| `api/` | the FastAPI routes, one module per domain | **new** |
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Removed: `uploads.py`, `static/index.html`, and the old flow's endpoints.
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`sessions.py` was meant to be reused for click-assist, but it existed to hold GPU-resident
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state for an interactive session — a whole eviction policy, an undo stack, and a per-session
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annotation store, all of which the database and the stateless `review.assist` now cover.
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Adapting 357 lines to do what 60 lines do was not worth it, so the module is gone. The one
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thing it knew that mattered — SAM3 wants exemplar boxes as normalized centre-x, centre-y,
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width, height — moved with it.
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The 400-line file limit (see `../AGENTS.md`) applies to all of the above. It is why the
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routes live in `backend/api/{projects,batches,review,models,jobs}.py` rather than in
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`main.py`, which now only builds the app and owns startup. Route modules import their
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domain module under an alias (`from backend import projects as project_store`) so the two
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namespaces stay distinguishable.
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## API contract
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```
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GET /api/health REQ-073
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GET /api/projects REQ-001
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POST /api/projects REQ-001,002,004,005
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GET /api/projects/{id} # includes label_type_locked: bool (REQ-002), video_root_linux/video_root_windows (REQ-179)
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DELETE /api/projects/{id}
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PATCH /api/projects/{id} # { prompts: {classId: text}, containers: {classId: bool} }, val_every (REQ-005, REQ-184)
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POST /api/projects/{id}/classes # add new class {name, prompt} (REQ-008)
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DELETE /api/projects/{id}/classes/{class_id} # delete class, delete shapes, reindex classes (REQ-007)
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POST /api/projects/{id}/base-model # upload .pt, read classes (REQ-003)
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GET /api/projects/{id}/dataset # master dataset summary (REQ-053)
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GET /api/projects/{id}/dataset/download # zip (REQ-054)
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GET /api/projects/{id}/library # list of dates (REQ-011)
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GET /api/projects/{id}/library/{date} # videos + duration/resolution (REQ-012)
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POST /api/projects/{id}/library/dates?date= # create YYYY-MM-DD folder → {date}; 409 if it exists, 400 bad format (REQ-178)
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POST /api/projects/{id}/library/upload?date= # multipart `file`, streamed to disk → {rel}; 409 dup, 400 bad ext/missing date (REQ-178)
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GET /api/projects/{id}/video?rel=… # Range streaming (REQ-013)
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POST /api/projects/{id}/batches # {rel, start_sec, end_sec, fps} → extract job
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GET /api/batches/{id} # status + review progress (REQ-045)
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GET /api/batches/{id}/frames # frames + statuses
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POST /api/batches/{id}/autolabel # {threshold, class_params} → job (REQ-030,032,034,181)
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POST /api/batches/{id}/preview # one frame, run now, nothing written;
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# +class_params {name: {threshold?, iou_threshold?, min_box_frac?, max_box_frac?}}
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# empty override = global value, keys are class names (REQ-181)
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# +exemplars[] {box:[cx,cy,w,h], positive} — the touched class's own pool only
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# +exemplar_class_name, +target_class_names; per-class, accumulating
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# on the client (REQ-171,172,182)
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DELETE /api/batches/{id}/classes/{class_id}/annotations # clear all shapes of class in batch (REQ-046);
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# frame-scoped clear = client filters this frame → bulk-delete (REQ-180)
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POST /api/batches/{ids}/approve # one or many, comma-separated → one merge job (REQ-131)
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GET /api/batches/{ids}/triage/summary # one or many, comma-separated (REQ-130)
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GET /api/batches/{ids}/triage/shapes
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GET /api/batches/{ids}/triage/suggest
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POST /api/batches/{ids}/triage/simulate
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GET /api/frames/{id}/image?w=… # frame image / thumbnail
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GET /api/frames/{id}/annotations
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POST /api/frames/{id}/annotations # add a manual shape (REQ-042)
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PATCH /api/annotations/{id} # move/resize/reclass
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DELETE /api/annotations/{id}
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POST /api/annotations/bulk-delete # {ids[]} → N deletes (REQ-180 frame-clear uses it)
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POST /api/frames/{id}/assist # click/box → SAM3 shape (REQ-043)
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POST /api/frames/{id}/exemplar-label # drawn pool → re-detect one class (REQ-173,174)
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POST /api/frames/{id}/status # approved | rejected | pending (REQ-041)
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POST /api/projects/{id}/train # → train job (REQ-060,061,062)
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GET /api/projects/{id}/models # versions + metrics (REQ-063,064)
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GET /api/models/{id}/weights # download best.pt
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POST /api/models/{id}/promote # make it the project's base model (REQ-064)
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PATCH /api/models/{id}/rename # update model display name { name }
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GET /api/projects/{id}/live-count/models # weights this project can count with
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POST /api/projects/{id}/live-count/start # {source|source_rel, model_path, dials}
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# source must be a WHEP URL (REQ-176)
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POST /api/live-count/stop
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PATCH /api/live-count/line # move the line mid-session
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GET /api/live-count/status # counts + preview: "webrtc" | "mjpeg"
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GET /api/live-count/overlay # boxes/line/counts for the canvas (REQ-177)
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GET /api/live-count/stream # MJPEG; 409 on a WebRTC session (REQ-177)
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GET /api/jobs?project_id=… REQ-070,071
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GET /api/jobs/{id}
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POST /api/jobs/{id}/cancel
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```
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### Live counting (REQ-176, REQ-177)
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One camera, one ingest on the streaming server, two consumers:
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```
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camera ──▶ MediaMTX ──┬── WHEP :8889/cam/whep ──▶ browser <video> + <canvas> overlay
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└── RTSP :8554/cam ──▶ backend decode → YOLO → counter
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└─▶ GET /api/live-count/overlay
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```
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The user types only the WHEP URL; `live_source.whep_to_rtsp` derives the RTSP one, with the
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ports coming from `MEDIAMTX_RTSP_PORT` / `MEDIAMTX_WHEP_PATH`. Because the browser plays the
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camera directly, a live session encodes no JPEG at all — `live_render.py` runs only for
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archive files, which have no WebRTC leg. The canvas draws exactly what `live_render.py`
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would have burned in, so both previews describe the same session.
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## Job flows
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**extract (REQ-020…023).** `ffmpeg -ss <start> -to <end> -i <video> -vf fps=<n> -q:v 2
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frames/%06d.jpg`. `frames` rows are written once the files exist; the batch's frame count is
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updated. Range and fps live on the batch, so one video can be used repeatedly.
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**autolabel (REQ-030…034).** Per frame: one `set_image`, then loop each class's prompt (see
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the domain invariants in `../AGENTS.md`), cross-class greedy NMS (REQ-031), write `annotations` rows with
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`source='auto'`. `class_params` (REQ-181) is consulted per class: a numeric
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`threshold` / `iou_threshold` / `min_box_frac` / `max_box_frac` entry replaces the job's global for that class
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only; classes without an entry — and a run with `class_params` empty or absent — take the
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exact global path. The YOLO confidence floor uses `min([global] + overrides)`, the SAM3
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threshold/dedup/min-box/max-box lists are built only from classes that actually override that key,
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and `/preview` applies the same overrides so the preview and the job cannot disagree.
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The job and `/preview` also read `project_classes.container` per class when building the
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container-id set for the NMS containment carve-out — same stored flag for both (REQ-184,
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amended REQ-031).
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A re-run deletes only `source='auto'` rows — manual corrections
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(`source='manual'`) survive — and returns already-approved frames to `pending`, because
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that approval was given against labels that no longer exist. No overlay images are written:
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the review canvas draws the shapes from the annotation rows, so a second rendering of the
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same data on the server would only be a second thing to keep in sync.
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**Deleting a class (REQ-007).** `projects.delete_class` removes the class's annotations,
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decrements every `class_id` above it in `annotations` and `project_classes`, then calls
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`dataset.drop_class_from_labels` to do the same edit to every `.txt` already written to
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disk, and rewrites `data.yaml`. The renumbering is the whole job: a YOLO label is an integer
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index, so a class list and a set of label files that disagree do not fail loudly — they
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train a model on the wrong names. Refused for a project's last class.
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**merge (REQ-050…053, REQ-131…132).** One job covers the whole selected set of batches, and
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`datasets.rules_json` holds the triage rules frozen at the moment the merge was confirmed —
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the resolver is built from that snapshot, never from the project's live rules. For every
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`approved` frame not yet in `dataset_items`: assign a
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split (continuing the round-robin), copy the JPEG to `dataset/images/<split>/`, write the
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YOLO `.txt` from the frame's annotations, record the row. Finally rewrite `data.yaml`.
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Frames with no annotations produce an empty `.txt` (REQ-033).
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**train (REQ-060…065).** Release the SAM3 engine → `YOLO(base/model.pt)` (or pretrained if
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the project has no base yet) → `.train(data=dataset/data.yaml, **hardware.defaults())` →
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`evaluate.py` runs `.val()` for both the base model and the new one against the same
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`data.yaml` → store `models/<n>/best.pt` + `metrics.json`. Each version is auto-named
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`{arch}-{labelType}-{epochs}ep-{classNames}-{YYYYMMDD}` (e.g. `yolo11n-bbox-100ep-sack+box-20260909`).
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`hardware.py` picks defaults from the detected VRAM:
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| VRAM | batch | imgsz |
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|---|---|---|
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| < 8 GB | 8 | 640 |
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| 8–16 GB | 16 | 640 |
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| > 16 GB | 32 | 768 |
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CPU-only: `batch=4`, `imgsz=512`, with a warning that training will be very slow. These are
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form defaults only (REQ-062).
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## Frontend
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React + Vite, no heavy UI library; plain `fetch`, job polling once a second as today.
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Design system and validation checklist follow ui-ux-pro-max — see `../AGENTS.md` §7.
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Design constraints specific to this app:
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- **Dense tool, not a landing page.** Neutral surface, one accent colour, tight spacing.
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The frame and the canvas own the screen; panels are chrome.
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- **Dark by default** — annotation work happens on video stills, and a bright surround
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distorts the judgement of what's in the frame. Light mode is a toggle, not an afterthought.
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- **Class colours are data, not decoration.** One fixed, colour-blind-safe hue per class
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index, identical in the filmstrip, the canvas, and the class panel.
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- **Keyboard first in Review.** Every action there has a shortcut and a visible focus state;
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the mouse is for drawing shapes, not for navigating.
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- **Progress is always visible.** Long jobs (extraction, auto-annotation, training) show
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progress, elapsed time, and a cancel affordance — never a spinner with no end.
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Layout Architecture:
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- **Roboflow-Replica Layout**: Dense left sidebar (`Sidebar.jsx`) with Workspace switcher, navigation sections:
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- **WORKSPACE**: Projects (`/projects`)
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- **DATA**: Video Archive (`/projects/{id}`), Annotate / Review (`/batches/{id}`), Master Dataset (`/projects/{id}/dataset`)
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- **MODELS**: Train & Select Engine (`/projects/{id}/models`), Model Monitoring & Analytics
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- **DEPLOY**: Model Deployments & Base Model Promotion (`/projects/{id}/deploy`)
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- **System Health Footer**: Hardware GPU, Free VRAM, SAM3 readiness, and ffmpeg status.
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Pages:
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1. **Projects** — workspace project cards + new project form (name, label type, base model, video root, classes & prompts).
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2. **Library** — dates column → videos/batches with duration, resolution, used marker.
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3. **Trim** — `<video>` + in/out timeline, fps input, estimated frame count, extract button.
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4. **Review** — status-coloured filmstrip, canvas editor, class panel, shortcuts
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(`←`/`→` frame, `A` approve, `X` reject, `Del` delete shape), *Approve batch* button.
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5. **Models** — model engine selection cards (Custom Training vs NAS/Pretrained), train button, job progress, base-vs-new mAP comparison table, download & *promote*.
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The canvas editor is hand-written; the normalized-coordinate conventions already exist in
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`sessions.py` (`annotations_payload`, `detections_payload`) as a reference.
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**Auto-annotate modal (REQ-171, REQ-172, REQ-182, REQ-184, REQ-186).** `AutoAnnotateModal.jsx` splits into
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`PreviewShapes.jsx` (the result overlay, shared with the mass modal),
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`ClassPromptPanel.jsx` (class chips + the editable SAM3 prompt) and `ExemplarCanvas.jsx`
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(the drag-to-draw layer). All three overlays and the `<img>` share one shrink-wrapped
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`position: relative` wrapper — they are sized to it, so nothing else may sit inside it or
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every box shifts off the pixels it describes.
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With SAM3 one selected chip is *active*: it owns the prompt field and any exemplars drawn on
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the frame, so its chip is a pair of buttons — the name activates, the `×` deselects.
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Exemplars are normalized `[cx, cy, w, h]`, one pool per class keyed by class name
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(`hooks/useExemplarPools.js`), sent only to `/preview`, and dropped when the frame changes —
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switching the active class swaps pools instead of discarding them (REQ-172). The preview is
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per class and accumulates (REQ-182): exemplar changes share **one 250 ms debounce** that
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re-runs the most recently touched class against its own pool and replaces only that class's
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shapes — rapid alternation between classes re-runs only the last one — while the other
|
||
exemplared classes' results stay on screen and the canvas **merges** (amended REQ-182):
|
||
exemplared classes contribute their pool-conditioned results (replacing their own full-set
|
||
boxes), every other selected class keeps the detections of the last full-set run on that
|
||
frame. Undo is the same re-run with the shortened pool, because SAM3 can
|
||
only append geometric prompts. Clearing a class's last example sends no request and returns
|
||
that class to its full-set detections (blank if no full-set run covered it); clearing all
|
||
examples is then a plain full-set view again. Run Preview always refreshes the full-set for
|
||
every selected class first (with empty exemplars), then re-runs the exemplared classes
|
||
sequentially; drawing an example never triggers a full-set re-run. The
|
||
per-class overrides block (REQ-181) stacks one row per class — name plus **Container**
|
||
checkbox on the first line, the four override inputs in a wrapping grid below — and that
|
||
checkbox toggles
|
||
`project_classes.container` through `PATCH /api/projects/{id} { containers: … }`. The same
|
||
block carries a **Copy** button (REQ-186): one click puts every selected class's effective
|
||
settings (per-class override where set, else the global slider; container = the checkbox
|
||
state) on the clipboard as short lines `class <name> conf … iou … minbox … maxbox … container
|
||
true|false`, through `clipboard.js`'s `copyText` (Clipboard API with an `execCommand`
|
||
fallback for insecure contexts) — read-only, no network, no setting changed. Because
|
||
`ClassParamsTable` is shared, the mass modal carries the button too.
|
||
|
||
**Review sidebar class rows (REQ-180, REQ-183, REQ-185).** Each class row's frame-clear `×`
|
||
(REQ-180) gains an eye toggle in front of it: session-only `Set` state in `ReviewPage`, so it
|
||
survives frame changes, resets when the review page is left, and never touches stored data.
|
||
Hidden shapes are never handed to `AnnotationCanvas` — not drawn, not clickable, not
|
||
marquee-selectable — but they stay listed, dimmed, in "Shapes on this frame". Two session
|
||
Sets drive the hide half: `hiddenShapeIds` (the `H` key, REQ-185, which toggles the single
|
||
selection or all marked shapes) and `overriddenShapeIds` (the row-eye restore and the
|
||
auto-override below); a shape is visible when it is not `H`-hidden and (its class is visible
|
||
or it is overridden). Dimmed rows stay selectable, reclassable and deletable from the list —
|
||
the old "not deletable while hidden" purge invariant is superseded — while the class row
|
||
keeps its real per-frame count. Creating a shape while its class is hidden (draw, assist,
|
||
copy) auto-overrides it so the user sees what they just made; reclassing into a hidden class
|
||
dims it unless it already carries an override; toggling a class eye clears that class's overrides.
|
||
|
||
**Exemplar-driven labeling in review (REQ-173, REQ-174, REQ-175).** In `draw` mode a drag on
|
||
`AnnotationCanvas` is an exemplar, not a rectangle: `onExemplar(box, positive)` where
|
||
`positive` is `!event.shiftKey`. `hooks/useExemplarPool.js` keeps the pool in a ref as well
|
||
as state — the ref is what gets sent, so a drag that lands mid-flight is never lost — and posts
|
||
the **whole pool** to `/exemplar-label` 400 ms after the last drag. One pass runs at a time;
|
||
a drag arriving during a pass sets `rerunWanted` so exactly one rerun follows instead of a
|
||
queue. The pool is cleared by a frame change or a class change, and `Undo example` re-runs
|
||
with the shortened pool.
|
||
|
||
The run is a **dry run by default** (REQ-175). `ExemplarFilterPanel.jsx` is passed to
|
||
`ReviewSidebar` and rendered above the class list — not over the frame, which is where its
|
||
proposals are drawn. It is mounted only while a run is undecided (`pool.active`): the first
|
||
drag opens it, Apply and Discard close it, and the pool outlives it. Its five sliders
|
||
re-preview on a 250 ms debounce. While a preview is up the canvas **hides the stored shapes
|
||
of the class under review** — the run replaces them wholesale, and leaving them on screen made
|
||
a rejected detection look like it had never gone; other classes stay, dimmed
|
||
(`svg.previewing`). Proposals draw dashed on top, green for the boxes the user drew and
|
||
class-colored for what SAM3 found.
|
||
`Apply` re-runs with `apply: true` rather than posting the previewed geometry back — SAM3 is
|
||
deterministic for a pool and a threshold, and the browser should not be the authority on what
|
||
gets stored. `Discard` truncates the pool to `appliedRef`, the length it had at the last
|
||
successful apply, so a rejected run leaves neither shapes nor prompts behind. A successful
|
||
apply drops the negatives it sent and keeps the positives (REQ-174); drags that landed while
|
||
that request was in flight are not part of it and stay at the end of the pool, with a rerun
|
||
queued for them.
|
||
|
||
`.canvas-wrap`'s overlay rules are scoped to its direct child (`> svg`): they set
|
||
`position: absolute; width: 100%`, which any nested SVG — an icon in a panel, say — would
|
||
otherwise inherit and stretch across the whole frame.
|
||
|
||
Request/response:
|
||
|
||
```
|
||
POST /api/frames/{id}/exemplar-label
|
||
{ "exemplars": [{"box": [x0,y0,x1,y1], "positive": true}, …], # normalized xyxy
|
||
"class_id": 0,
|
||
"threshold": 0.5, "iou_threshold": 0.8, # the panel (REQ-175)
|
||
"min_box_frac": 0.002, "max_box_frac": 1.0, "max_detections": 100,
|
||
"apply": false }
|
||
→ { "shapes": [{"geometry": …, "score": …, "source": "manual"|"auto"}, …],
|
||
"applied": false, "redetected": true, "message": null,
|
||
"annotations": null } # the frame, on apply only
|
||
```
|
||
|
||
`backend/exemplar.py` converts each box to SAM3's normalized `[cx, cy, w, h]`, runs one
|
||
`open_state` + `apply_prompts` with the class's stored `prompt` as text plus every exemplar,
|
||
then rewrites the frame **for that class only**:
|
||
|
||
- positives are stored first as `source='manual'` — the literal rectangle in a `bbox`
|
||
project, the mask polygon of whatever SAM3 found inside it (IoU ≥ `SNAP_IOU`) in a
|
||
`polygon` one;
|
||
- detections overlapping a negative by ≥ `NEGATIVE_IOU` (0.3) are dropped, and ones
|
||
overlapping a positive by ≥ `DUPLICATE_IOU` (0.6) are dropped as the user's own shape
|
||
already covers them;
|
||
- what remains is written as `source='auto'`, so a later batch re-run replaces it (REQ-034)
|
||
while the drawn shapes survive.
|
||
|
||
The panel's filters run before any of that, in the order the batch job uses them: area floor,
|
||
then ceiling (REQ-188), then NMS (`labeling.deduplicate`), then the cap on how many survive.
|
||
|
||
The delete-and-reinsert happens in one `db.cursor()` transaction, so the frame is never
|
||
briefly empty. Other classes on the frame are never touched. The GPU lock is taken with a
|
||
**5 s** timeout — shorter than `assist`'s 20 s because this fires from a mouse gesture; on
|
||
timeout the response carries `redetected: false`, a message the panel shows, and the drawn
|
||
boxes alone as the preview. Applying that run **appends** the drawn boxes and honours the
|
||
negatives instead of taking the replace path — with no detections to put back, replacing
|
||
would wipe the class and leave only the drawings.
|
||
|
||
## Docker (REQ-072)
|
||
|
||
- `Dockerfile` — python 3.12, `ffmpeg`, `uv`, CUDA torch, `uv pip install -e sam3/`. The
|
||
known traps still apply: `setuptools<81` (because `sam3` imports `pkg_resources`) and the
|
||
undeclared `einops` + `pycocotools` dependencies of the vendored SAM3.
|
||
- `docker-compose.yml` — a `backend` service (GPU passthrough, `./data` volume, video archive
|
||
mounted read-write (REQ-178), `.env` for `HF_TOKEN`) and a `frontend` service (nginx: static
|
||
files + `/api` proxy, `client_max_body_size 20g`).
|
||
- GPU access uses compose **`gpus: all`** (same path as the `docker run --gpus all` CLI flag).
|
||
The earlier CDI form (`devices: nvidia.com/gpu=all`) fails on Docker Desktop's WSL2 backend
|
||
with `unresolvable CDI devices` because no CDI spec exists there; `gpus: all` works on both
|
||
Docker Desktop and a native engine with the NVIDIA container toolkit.
|
||
The runtime entry in `/etc/docker/daemon.json` is not registered with the daemon here.
|
||
- The frontend pins **Vite 7**. Vite 8's default bundler (Rolldown) ships a native binding
|
||
that dies with a bus error on this machine; Vite 7's Rollup path works.
|