feat: add video detection and robot alerts

README.md

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+# Smoke and Fire YOLO
+
+Ultralytics YOLO training, validation, prediction, and export pipeline for the Smoke-Fire-Detection-YOLO dataset.
+
+## Project layout
+
+```text
+configs/datasets/smoke_fire.yaml  Dataset configuration
+models/pretrained/yolo11s.pt      Default pretrained model
+src/yolo/cli.py                   Command-line entry point
+src/yolo/config.py                Training configuration
+src/yolo/defaults.py              Project defaults
+src/yolo/engine.py                Train, validate, predict, and export
+src/yolo/checkpoints.py           Checkpoint discovery and resume support
+src/yolo/reporting.py             Training result reporting
+```
+
+## Setup
+
+```bash
+uv sync
+```
+
+## Commands
+
+Fine-tune from the current best YOLO11s checkpoint:
+
+```bash
+uv run fire-yolo train
+```
+
+Resume from the newest checkpoint:
+
+```bash
+uv run fire-yolo train --resume
+```
+
+Validate a trained model:
+
+```bash
+uv run fire-yolo val --weights runs/detect/<run-name>/weights/best.pt
+```
+
+Run inference:
+
+```bash
+uv run fire-yolo predict --weights runs/detect/<run-name>/weights/best.pt --source path/to/image-or-video
+```
+
+Export a model:
+
+```bash
+uv run fire-yolo export --weights runs/detect/<run-name>/weights/best.pt --format onnx
+```
+
+## Default training settings
+
+- Model: `runs/detect/smoke_fire_yolo11s_v1-4/weights/best.pt`
+- Dataset: `configs/datasets/smoke_fire.yaml`
+- Epochs: 80
+- Image size: 768
+- Batch: 24
+- Workers: 0
+- Optimizer: AdamW
+- Initial learning rate: 0.0002
+- Mosaic/MixUp: disabled
+- Prediction confidence: 0.40
+- Checkpoint interval: every 5 epochs
+- Output: `runs/detect`
+
+Training writes `last.pt`, `best.pt`, periodic checkpoints, and `best_point.json` to the run directory.
+## Web Detection Service
+
+After training finishes, install the web dependencies and run the integrated frontend and inference API:
+
+```bash
+uv sync
+uv run uvicorn backend.main:app --host 127.0.0.1 --port 8000
+```
+
+Open `http://127.0.0.1:8000`, select a local video, and start continuous detection. The browser plays the video locally and sends sequential JPEG frames to `POST /api/detect`; requests do not overlap.
+
+The local `.env` file contains optional robot settings. Set `WECHAT_WEBHOOK_URL` for an Enterprise WeChat group robot, `FEISHU_WEBHOOK_URL` for a Feishu custom group robot, or both. If Feishu signature verification is enabled, also set `FEISHU_SECRET`. Alerts require three consecutive positive frames by default and use separate 60-second cooldowns for fire and smoke. `ALERT_CONFIRM_FRAMES` and `ALERT_COOLDOWN_SECONDS` override these settings. Without a webhook, video detection still works and the UI reports that notifications are disabled.