intial commit

src/chicken_counter/batch_runner.py

@@ -0,0 +1,111 @@
+"""Run CC1–CC4 sequentially, then compress videos and write the JSON report."""
+
+from __future__ import annotations
+
+from datetime import date as date_type
+from pathlib import Path
+
+from chicken_counter.batch_discovery import discover_camera_videos
+from chicken_counter.compress import compress_video_to_target
+from chicken_counter.config import BatchSettings, build_camera_config_from_batch
+from chicken_counter.pipeline import run_pipeline
+from chicken_counter.report import build_batch_report, persist_batch_reports
+from chicken_counter.tracking import DetectionTracker
+from chicken_counter.types import CameraBatchResult
+
+
+def run_daily_batch(settings: BatchSettings, date: str | None = None) -> Path:
+    run_date = date or date_type.today().isoformat()
+    day_dir = Path(settings.batch.root_dir) / run_date
+    output_dir = day_dir / settings.batch.output_subdir
+    output_dir.mkdir(parents=True, exist_ok=True)
+
+    print(f"[batch] starting daily run for {run_date}")
+    print(f"[batch] input folder: {day_dir}")
+    print(f"[batch] output folder: {output_dir}")
+
+    discovery = discover_camera_videos(day_dir, settings)
+    camera_order = sorted(settings.cameras.items(), key=lambda item: item[1].camera_num)
+
+    first_camera_id = next(
+        camera_id for camera_id, _preset in camera_order if camera_id in discovery.found
+    )
+    first_source = discovery.found[first_camera_id]
+    init_config = build_camera_config_from_batch(
+        settings,
+        first_camera_id,
+        source=first_source,
+        output_path=output_dir / f"{first_camera_id}_vis.mp4",
+        checkpoint_dir=output_dir / "checkpoints" / first_camera_id,
+    )
+    shared_tracker = DetectionTracker(init_config)
+
+    camera_results: list[CameraBatchResult] = []
+    report_path = output_dir / f"counts_{run_date}.json"
+
+    for camera_id, _preset in camera_order:
+        if camera_id in discovery.skipped:
+            skip_reason = discovery.skipped[camera_id]
+            print(f"[batch] skipping {camera_id}: {skip_reason}")
+            camera_results.append(
+                CameraBatchResult(
+                    camera_id=camera_id,
+                    skipped=True,
+                    skip_reason=skip_reason,
+                )
+            )
+            persist_batch_reports(run_date, camera_results, output_dir)
+            continue
+
+        source_path = discovery.found[camera_id]
+        vis_path = output_dir / f"{camera_id}_vis.mp4"
+        checkpoint_dir = output_dir / "checkpoints" / camera_id
+
+        print(f"[batch] processing {camera_id} from {source_path.name}")
+        camera_config = build_camera_config_from_batch(
+            settings,
+            camera_id,
+            source=source_path,
+            output_path=vis_path,
+            checkpoint_dir=checkpoint_dir,
+        )
+        pipeline_result = run_pipeline(camera_config, tracker=shared_tracker)
+        camera_results.append(
+            CameraBatchResult(
+                camera_id=camera_id,
+                pipeline=pipeline_result,
+            )
+        )
+        print(
+            f"[batch] finished {camera_id}: total_entered={pipeline_result.total_entered_count} "
+            f"frames={pipeline_result.frames_processed} reason={pipeline_result.stopped_reason}"
+        )
+        persist_batch_reports(run_date, camera_results, output_dir)
+
+    print("[batch] all cameras complete; starting compression")
+    for item in camera_results:
+        if item.skipped or item.pipeline is None:
+            continue
+        vis_path = item.pipeline.vis_video_path
+        if not vis_path:
+            continue
+        compressed_path = output_dir / f"{item.camera_id}_compressed.mp4"
+        size_mb = compress_video_to_target(
+            vis_path,
+            compressed_path,
+            max_mb=settings.batch.compress_max_mb,
+        )
+        item.compressed_video_path = str(compressed_path)
+        item.compressed_size_mb = size_mb
+
+        if settings.batch.delete_intermediate:
+            Path(vis_path).unlink(missing_ok=True)
+
+        persist_batch_reports(run_date, camera_results, output_dir)
+
+    report = build_batch_report(run_date, camera_results, output_dir=output_dir)
+    print(
+        f"[batch] complete for {run_date}: total_entered_sum={report.total_entered_sum} "
+        f"report={report_path}"
+    )
+    return report_path