Bump actions/setup-python from 5 to 6 in /.github/workflows

.github/workflows/ci-testing.yml

@@ -27,7 +27,7 @@ jobs:
         model: [yolov5n]
     steps:
       - uses: actions/checkout@v4
-      - uses: actions/setup-python@v5
+      - uses: actions/setup-python@v6
         with:
           python-version: ${{ matrix.python-version }}
       - uses: astral-sh/setup-uv@v6
@@ -65,7 +65,7 @@ jobs:
             torch: "1.8.0" # min torch version CI https://pypi.org/project/torchvision/
     steps:
       - uses: actions/checkout@v4
-      - uses: actions/setup-python@v5
+      - uses: actions/setup-python@v6
         with:
           python-version: ${{ matrix.python-version }}
       - uses: astral-sh/setup-uv@v6

.github/workflows/merge-main-into-prs.yml

@@ -20,7 +20,7 @@ jobs:
         uses: actions/checkout@v4
         with:
           fetch-depth: 0
-      - uses: actions/setup-python@v5
+      - uses: actions/setup-python@v6
         with:
           python-version: "3.x"
           cache: "pip"

testcode.py

@@ -1,12 +1,12 @@
-import time
-import cv2
-import torch
-import numpy as np
 import sys
 
+import cv2
+import numpy as np
+import torch
 from unitree_sdk2py.core.channel import ChannelFactoryInitialize
 from unitree_sdk2py.go2.video.video_client import VideoClient
 
+
 # ----------------------------
 # Preprocess and detect
 # ----------------------------
@@ -17,6 +17,7 @@ def preprocess(frame):
     img = np.ascontiguousarray(img) / 255.0
     return torch.tensor(img).float().unsqueeze(0)
 
+
 def detect_person(model, frame, conf_thresh=0.5):
     img = preprocess(frame)
     with torch.no_grad():
@@ -28,6 +29,7 @@ def detect_person(model, frame, conf_thresh=0.5):
             boxes.append((x1, y1, x2 - x1, y2 - y1))
     return boxes
 
+
 # ----------------------------
 # Main Camera Loop
 # ----------------------------
@@ -50,7 +52,7 @@ def camera_loop(model):
 
         boxes = detect_person(model, frame)
 
-        for (x, y, w, h) in boxes:
+        for x, y, w, h in boxes:
             cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
             cv2.putText(frame, "Person", (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 255, 0), 2)
 
@@ -61,6 +63,7 @@ def camera_loop(model):
 
     cv2.destroyAllWindows()
 
+
 # ----------------------------
 # Main
 # ----------------------------

utils/triton.py

@@ -29,7 +29,7 @@ def __init__(self, url: str):
             self.model_name = model_repository.models[0].name
             self.metadata = self.client.get_model_metadata(self.model_name, as_json=True)
 
-            def create_input_placeholders() -> typing.List[InferInput]:
+            def create_input_placeholders() -> list[InferInput]:
                 return [
                     InferInput(i["name"], [int(s) for s in i["shape"]], i["datatype"]) for i in self.metadata["inputs"]
                 ]
@@ -42,7 +42,7 @@ def create_input_placeholders() -> typing.List[InferInput]:
             self.model_name = model_repository[0]["name"]
             self.metadata = self.client.get_model_metadata(self.model_name)
 
-            def create_input_placeholders() -> typing.List[InferInput]:
+            def create_input_placeholders() -> list[InferInput]:
                 return [
                     InferInput(i["name"], [int(s) for s in i["shape"]], i["datatype"]) for i in self.metadata["inputs"]
                 ]
@@ -54,7 +54,7 @@ def runtime(self):
         """Returns the model runtime."""
         return self.metadata.get("backend", self.metadata.get("platform"))
 
-    def __call__(self, *args, **kwargs) -> typing.Union[torch.Tensor, typing.Tuple[torch.Tensor, ...]]:
+    def __call__(self, *args, **kwargs) -> typing.Union[torch.Tensor, tuple[torch.Tensor, ...]]:
         """
         Invokes the model.