subnet_bridge: copy winning miner repo into library

README.md

@@ -13,17 +13,17 @@ tags:
 manako:
   source: winner_fetch
   manifest_element_name: manak0/Detect-crime
-  winner_repo_id: thomaskk2024/pmodel_630
-  winner_revision: 89943ba2d8face20c570c1d9bfa77dc8310aa3ea
-  note: E=0.11999508 (map50=0.600000, size_mb=5.000205)
+  winner_repo_id: carljurk/ScoreVision
+  winner_revision: 3b0a2a7e45ad080e10ea4219277642640ff78c39
+  note: E=0.06100469 (map50=0.600000, size_mb=9.835309)
 ---
 
 # Detect-crime-winner
 
 Published winning miner converted into a library element.
 
-- Source winner repo: `thomaskk2024/pmodel_630`
-- Source revision: `89943ba2d8face20c570c1d9bfa77dc8310aa3ea`
+- Source winner repo: `carljurk/ScoreVision`
+- Source revision: `3b0a2a7e45ad080e10ea4219277642640ff78c39`
 - Manifest element: `manak0/Detect-crime`
 - Element type: `Detect`
 - Objects: balaclava, hoodie, glove, bat, spray paint, graffiti

chute_config.yml

@@ -2,7 +2,7 @@ Image:
   from_base: parachutes/python:3.12
   run_command:
     - pip install --upgrade setuptools wheel
-    - pip install 'numpy>=1.23' 'onnxruntime-gpu>=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 'numpy>=1.23' 'onnxruntime-gpu==1.20.1' 'opencv-python>=4.7' 'pillow>=9.5' 'huggingface_hub>=0.19.4' 'pydantic>=2.0' 'pyyaml>=6.0' 'aiohttp>=3.9'
     - pip install torch==2.8.0 torchvision==0.23.0 torchaudio==2.8.0 --index-url https://download.pytorch.org/whl/cu128
 
 NodeSelector:

miner.py

@@ -34,7 +34,7 @@ class Miner:
     # (ships inside weights.onnx), so a retrained model with a different class
     # order is remapped correctly without code changes. This static list is used
     # only when that metadata is missing or unparsable.
-    model_class_names = ["balaclava", "bat", "glove", "graffiti", "hoodie", "spray paint"]
+    model_class_names = ["balaclava", "hoodie", "glove", "bat", "spray paint", "graffiti"]
 
     input_size = 1280
 
@@ -50,10 +50,10 @@ class Miner:
     max_det = 150
     
     _conf_thres_array = np.array(
-        [0.38, 0.58, 0.22, 0.25, 0.23, 0.22], dtype=np.float32,
+        [0.33, 0.53, 0.32, 0.29, 0.46, 0.34], dtype=np.float32,
     )
     _bonus_array = np.array(
-        [0.18, 0.25, 0.12, 0.09, 0.07, 0.10], dtype=np.float32,
+        [0.02, 0.03, 0.04, 0.07, 0.06, 0.05], dtype=np.float32,
     )
 
     def __init__(self, path_hf_repo: Path) -> None:

pyproject.toml

@@ -5,7 +5,7 @@ requires-python = ">=3.9"
 
 dependencies = [
   "numpy>=1.23",
-  "onnxruntime>=1.16",
+  "onnxruntime==1.20.1",
   "opencv-python>=4.7",
   "pillow>=9.5",
   "huggingface_hub>=0.19.4",

weights.onnx

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:230d840c86bfde7e7b0ecff6d8114ebe88cfe67a8e6e51bce757075053470321
-size 4974021
+oid sha256:fe133b628068ddf780a7e94f9bbee73ff8abcd1b4dc1cc2f866b8bb2eeb14229
+size 9809123