update

kornia/filters/motion.py

@@ -1,5 +1,7 @@
 from __future__ import annotations
 
+from typing import ClassVar
+
 from kornia.core import ImageModule as Module
 from kornia.core import Tensor
 from kornia.core.check import KORNIA_CHECK
@@ -84,8 +86,8 @@ class MotionBlur3D(Module):
         >>> output = motion_blur(input)  # 2x4x5x7x9
     """
 
-    ONNX_DEFAULT_INPUTSHAPE: list[int] = [-1, -1, -1, -1, -1]
-    ONNX_DEFAULT_OUTPUTSHAPE: list[int] = [-1, -1, -1, -1, -1]
+    ONNX_DEFAULT_INPUTSHAPE: ClassVar[list[int]] = [-1, -1, -1, -1, -1]
+    ONNX_DEFAULT_OUTPUTSHAPE: ClassVar[list[int]] = [-1, -1, -1, -1, -1]
 
     def __init__(
         self,

kornia/filters/sobel.py

@@ -1,5 +1,7 @@
 from __future__ import annotations
 
+from typing import ClassVar
+
 import torch
 import torch.nn.functional as F
 
@@ -172,8 +174,8 @@ class SpatialGradient(Module):
         >>> output = SpatialGradient()(input)  # 1x3x2x4x4
     """
 
-    ONNX_DEFAULT_INPUTSHAPE: list[int] = [-1, -1, -1, -1]
-    ONNX_DEFAULT_OUTPUTSHAPE: list[int] = [-1, -1, 2, -1, -1]
+    ONNX_DEFAULT_INPUTSHAPE: ClassVar[list[int]] = [-1, -1, -1, -1]
+    ONNX_DEFAULT_OUTPUTSHAPE: ClassVar[list[int]] = [-1, -1, 2, -1, -1]
 
     def __init__(self, mode: str = "sobel", order: int = 1, normalized: bool = True) -> None:
         super().__init__()
@@ -209,8 +211,8 @@ class SpatialGradient3d(Module):
         torch.Size([1, 4, 3, 2, 4, 4])
     """
 
-    ONNX_DEFAULT_INPUTSHAPE: list[int] = [-1, -1, -1, -1, -1]
-    ONNX_DEFAULT_OUTPUTSHAPE: list[int] = [-1, -1, -1, -1, -1, -1]
+    ONNX_DEFAULT_INPUTSHAPE: ClassVar[list[int]] = [-1, -1, -1, -1, -1]
+    ONNX_DEFAULT_OUTPUTSHAPE: ClassVar[list[int]] = [-1, -1, -1, -1, -1, -1]
 
     def __init__(self, mode: str = "diff", order: int = 1) -> None:
         super().__init__()

kornia/onnx/sequential.py

@@ -39,9 +39,9 @@ class ONNXSequential:
 
     def __init__(
         self,
-        *args: Union[onnx.ModelProto, str],  # type:ignore
+        *args: Union["onnx.ModelProto", str],  # type:ignore
         providers: Optional[list[str]] = None,
-        session_options: Optional[ort.SessionOptions] = None,  # type:ignore
+        session_options: Optional["ort.SessionOptions"] = None,  # type:ignore
         io_maps: Optional[list[tuple[str, str]]] = None,
         cache_dir: Optional[str] = None,
     ) -> None:
@@ -50,7 +50,7 @@ def __init__(
         self._combined_op = self._combine(io_maps)
         self._session = self.create_session()
 
-    def _load_op(self, arg: Union[onnx.ModelProto, str]) -> onnx.ModelProto:  # type:ignore
+    def _load_op(self, arg: Union["onnx.ModelProto", str]) -> "onnx.ModelProto":  # type:ignore
         """Loads an ONNX model, either from a file path or use the provided ONNX ModelProto.
 
         Args:
@@ -63,7 +63,7 @@ def _load_op(self, arg: Union[onnx.ModelProto, str]) -> onnx.ModelProto:  # type
             return self.onnx_loader.load_model(arg)
         return arg
 
-    def _combine(self, io_maps: Optional[list[tuple[str, str]]] = None) -> onnx.ModelProto:  # type:ignore
+    def _combine(self, io_maps: Optional[list[tuple[str, str]]] = None) -> "onnx.ModelProto":  # type:ignore
         """Combine the provided ONNX models into a single ONNX graph. Optionally, map inputs and outputs between
         operators using the `io_map`.
 
@@ -106,8 +106,8 @@ def export(self, file_path: str) -> None:
     def create_session(
         self,
         providers: Optional[list[str]] = None,
-        session_options: Optional[ort.SessionOptions] = None,  # type:ignore
-    ) -> ort.InferenceSession:  # type:ignore
+        session_options: Optional["ort.SessionOptions"] = None,  # type:ignore
+    ) -> "ort.InferenceSession":  # type:ignore
         """Create an optimized ONNXRuntime InferenceSession for the combined model.
 
         Args:
@@ -129,7 +129,7 @@ def create_session(
         )
         return session
 
-    def set_session(self, session: ort.InferenceSession) -> None:  # type: ignore
+    def set_session(self, session: "ort.InferenceSession") -> None:  # type: ignore
         """Set a custom ONNXRuntime InferenceSession.
 
         Args:
@@ -138,15 +138,15 @@ def set_session(self, session: ort.InferenceSession) -> None:  # type: ignore
         """
         self._session = session
 
-    def get_session(self) -> ort.InferenceSession:  # type: ignore
+    def get_session(self) -> "ort.InferenceSession":  # type: ignore
         """Get the current ONNXRuntime InferenceSession.
 
         Returns:
             ort.InferenceSession: The current ONNXRuntime session.
         """
         return self._session
 
-    def __call__(self, *inputs: np.ndarray) -> list[np.ndarray]:  # type:ignore
+    def __call__(self, *inputs: "np.ndarray") -> list["np.ndarray"]:  # type:ignore
         """Perform inference using the combined ONNX model.
 
         Args:

kornia/onnx/utils.py

@@ -50,7 +50,7 @@ def _get_file_path(self, model_name: str, cache_dir: Optional[str]) -> str:
         file_path = os.path.join(cache_dir, "/".join(model_name.split("/")[:-1]), file_name)
         return file_path
 
-    def load_model(self, model_name: str, download: bool = False, **kwargs) -> onnx.ModelProto:  # type:ignore
+    def load_model(self, model_name: str, download: bool = False, **kwargs) -> "onnx.ModelProto":  # type:ignore
         """Loads an ONNX model from the local cache or downloads it from Hugging Face if necessary.
 
         Args:
@@ -108,7 +108,10 @@ def _fetch_repo_contents(folder: str) -> list[dict[str, Any]]:
             List[dict]: A list of all files in the repository as dictionaries containing file details.
         """
         url = f"https://huggingface.co/api/models/kornia/ONNX_models/tree/main/{folder}"
-        response = requests.get(url)
+
+        if not url.startswith(("http:", "https:")):
+            raise ValueError("URL must start with 'http:' or 'https:'")
+        response = requests.get(url, timeout=10)
 
         if response.status_code == 200:
             return response.json()  # Returns the JSON content of the repo