CLI: Process videos from the command line with any model + class filter
Web UI: Upload videos, select models, download annotated output on port 9000
Multiple Models: Run multiple model configurations on the same video for comparison
Class Filtering: Choose which classes to count (sack, box, truck)
Annotated Output: Download MP4 videos with detection overlays for human review
Async Processing: Background job queue — upload and poll status

Quick Start

pip install -e ".[dev]"

# List available models
recounter --list-models --models-dir ./models

# Process a single video via CLI
recounter --video input.mp4 --model v4-best.pt --filter sack --output-dir ./output

# Start web UI
recounter-web
# Open http://localhost:9000

CLI Reference

recounter --video PATH          Input video file
         --model NAME           Model filename (repeatable for multiple)
         --all-models           Run all discovered models
         --list-models          List available models and exit
         --filter NAME          Class filter (repeatable): sack, box, truck
         --sack-conf FLOAT      Sack confidence threshold (default: 0.4)
         --truck-conf FLOAT     Truck confidence threshold (default: 0.5)
          --output PATH          Output path (single model only)
         --output-dir DIR       Output directory (default: ./output)
         --models-dir DIR       Models directory (default: ./models)

Web UI

Port: 9000 (configurable via WEB_PORT env)
Upload: Select video file
Model Selection: Checkboxes for each model, dropdown for class filter
Job Status: Auto-refreshing progress page
Download: Annotated MP4 per model result

API Endpoints

Endpoint	Method	Description
`/`	GET	Upload form with model selection
`/upload`	POST	Start processing job
`/status/<job_id>`	GET	Job status with results
`/jobs`	GET	All jobs listing
`/download/<job_id>/<filename>`	GET	Download output video
`/api/models`	GET	List available models
`/api/jobs`	GET	List all jobs (JSON)
`/api/jobs/<job_id>`	GET	Job detail (JSON)

Project Structure

src/
├── interfaces.py         # Detection dataclass + protocols
├── detection.py          # YOLO detectors with class filtering
├── tracking.py           # ByteTrack/FastTrack tracker
├── stabilizer.py         # Bbox smoothing + occlusion hold
├── truck_roi.py          # Truck ROI detection + EMA smoothing
├── counting.py           # Line-crossing counter
├── batch.py              # Batch lifecycle state machine
├── dashboard.py          # Frame annotation overlay
├── video_writer.py       # Annotated video writer
├── model_registry.py     # Model discovery + class metadata
├── pipeline.py           # Video processing pipeline
└── job.py                # Async job queue