scorevision: push artifact

chute_config.yml

@@ -0,0 +1,36 @@
+# deploy/chute_config.yml — SN44 road-signs miner (tatjr13/rs1) Chutes runtime config.
+#
+# This file is UPLOADED INTO THE HF REPO alongside weights.onnx + miner.py (01_hf_push.sh
+# stages it). The turbovision chute template loads it FROM the HF repo snapshot at deploy
+# time (turbovision_chute.py.j2: CHUTE_CONFIG_FILENAME = "chute_config.yml";
+# load_chute_config_from_hf_repo(...)) and feeds the three sections to
+# chutes.image.Image / chutes.chute.NodeSelector / chutes.chute.Chute via
+# safe_instantiate() — unknown keys are silently dropped, so keep names exact.
+#
+# Mirrored VERBATIM from the live car-wash winner Realfencer/ScoreVision@d2b7d836
+# (same runtime class the current road-signs winner uses: onnxruntime-gpu image,
+# 1x GPU >= 16 GB, pro_6000 node, tee: true) — fetched + verified 2026-08-25.
+# Only difference vs Realfencer: none (config is model-file agnostic; our repo/file
+# names live in the HF repo + template variables, not here).
+
+Image:
+  from_base: parachutes/python:3.12
+  run_command:
+    - pip install --upgrade setuptools wheel
+    - pip install 'numpy>=1.23' 'onnxruntime-gpu[cuda,cudnn]>=1.16' 'opencv-python>=4.7' 'pillow>=9.5' 'huggingface_hub>=0.19.4' 'pydantic>=2.0' 'pyyaml>=6.0' 'aiohttp>=3.9'
+    - pip install torch torchvision
+
+NodeSelector:
+  gpu_count: 1
+  min_vram_gb_per_gpu: 16
+  max_hourly_price_per_gpu: 2
+  include:
+    - pro_6000
+
+Chute:
+  timeout_seconds: 900
+  concurrency: 4
+  max_instances: 5
+  scaling_threshold: 0.5
+  shutdown_after_seconds: 288000
+  tee: true