dev0524/ScoreVision

Detect-Person miner (element manak0/Detect-Person)

Public-track TurboVision miner: single-class person detection. Base model: YOLO11n (COCO-pretrained, ~5.6 MB — well under the 30 MB element cap), filtered to the person class, emitted with cls_id=0.

Element constraints (from the live manifest):

• pillars: map50 x0.6 + false_positive x0.4 (false_positive = 1 - FPs-per-image/10)
• baseline theta to beat: ~0.368
• p95 latency <= 100 ms/frame on 2 vCPU (automated compliance loop)
• max model size 30 MB; validator preproc: 5 fps, long side 1280, rgb-01

Files

• miner.py — required entrypoint (Miner.predict_batch), prefers person.onnx over yolo11n.pt
• chute_config.yml — Chutes image/runtime config
• yolo11n.pt — base weights (replace with fine-tuned weights to beat other miners)
• export_onnx.py — exports person.onnx for faster CPU inference
• benchmark_latency.py — local replica of the 2 vCPU / 100 ms p95 latency gate

Workflow

# from the repo root, with the uv venv active (uv sync already done)
cd my_miners/detect_person

# 1. ONNX export (required for CPU speed; .pt alone fails the latency gate)
python export_onnx.py --imgsz 480

# 2. latency gate check, pinned to 2 CPUs like the compliance loop
taskset -c 0,1 python benchmark_latency.py --frames 100 --imgsz 480

# 3. deploy: upload to HF, build chute, warm + health-check, commit on-chain
cd ../..
sv -v deploy-os-miner --model-path my_miners/detect_person --element-id manak0/Detect-Person

# dry-run variants
sv -v deploy-os-miner --model-path my_miners/detect_person --element-id manak0/Detect-Person --no-commit

Required .env (see repo README.md): BITTENSOR_WALLET_COLD, BITTENSOR_WALLET_HOT, CHUTES_API_KEY, HF_USER, HF_TOKEN, CHUTES_HF_TOKEN (read-only fine-grained token), SCOREVISION_NETUID=44. Hotkey must be registered on netuid 44.

Measured latency (this machine, taskset 2 CPUs, 60 frames)

Model	imgsz	p50	p95	Gate (<=100 ms p95)
yolo11n.pt (torch CPU)	640	131 ms	150 ms	FAIL
person.onnx	640	98 ms	145 ms	FAIL
person.onnx	512	57 ms	92 ms	pass (thin margin)
person.onnx	480	52 ms	78 ms	PASS (default)

The compliance CPU model is unknown, so the 480 export is the default for headroom. Re-export at 512 only if you accept the thinner margin.

Tuning notes

• SV_CONF_THRESHOLD (default 0.35): raise to cut false positives (each FP/image costs 0.1 on the 0.4-weighted FP pillar), lower to lift recall/mAP.
• The dataset is synthetic (SAM3-annotated, 302 images). COCO-pretrained YOLO11n should clear the ~0.368 baseline; to win the element, fine-tune on person data matching the synthetic distribution and drop the weights in as yolo11n.pt (or re-export person.onnx).
• Commit early: on-chain commit block is the tie-breaker under model-copy protection.