hSrSSKJr SSKrSSKJr SSKJr SSKJr SSK J r SSK r SSK r SSKr\ Rr\ R"4SSjjrSSS jjrSS jr\R(rS rS r\S 5r\SSSjj5rg)zDMonkey patches to update/extend functionality of existing functions.) annotationsN)contextmanager)copy)Path)Anyc[R"U[R5nURS5(ak[R "U[R 5up4U(a<[U5S:XaUSRS:XaUS$[R"USS9$g[R"X!5nUbURS:XaUS$U$) a Read an image from a file with multilanguage filename support. Args: filename (str): Path to the file to read. flags (int, optional): Flag that can take values of cv2.IMREAD_*. Controls how the image is read. Returns: (np.ndarray | None): The read image array, or None if reading fails. Examples: >>> img = imread("path/to/image.jpg") >>> img = imread("path/to/image.jpg", cv2.IMREAD_GRAYSCALE) )z.tiffz.tifr)axisN).N) npfromfileuint8endswithcv2 imdecodemultiIMREAD_UNCHANGEDlenndimstackimdecode)filenameflags file_bytessuccessframesims S/home/james-whalen/.local/lib/python3.13/site-packages/ultralytics/utils/patches.pyimreadrsXrxx0J*++++J8L8LM  #F q 0VAY^^q5H6!9 fbhhW]deNf f \\* , "277a>> import numpy as np >>> img = np.zeros((100, 100, 3), dtype=np.uint8) # Create a black image >>> success = imwrite("output.jpg", img) # Write image to file >>> print(success) True r TF)rimencodersuffixtofile Exception)rimgparamss rimwriter(/sD& T(^**C8;BB8L s>> import numpy as np >>> img = np.zeros((300, 300, 3), dtype=np.uint8) # Create a black image >>> img[:100, :100] = [255, 0, 0] # Add a blue square >>> imshow("Example Window", img) # Display the image unicode_escapeN)_imshowencodedecode)winnamemats rimshowr0Is!$ GNN+ , 3 3 5s;r c^SSKJn U(a SU;aSUS'[R"U0UD6$)a Load a PyTorch model with updated arguments to avoid warnings. This function wraps torch.load and adds the 'weights_only' argument for PyTorch 1.13.0+ to prevent warnings. Args: *args (Any): Variable length argument list to pass to torch.load. **kwargs (Any): Arbitrary keyword arguments to pass to torch.load. Returns: (Any): The loaded PyTorch object. Notes: For PyTorch versions 2.0 and above, this function automatically sets 'weights_only=False' if the argument is not provided, to avoid deprecation warnings. r) TORCH_1_13 weights_onlyF)ultralytics.utils.torch_utilsr2torchload)argskwargsr2s r torch_loadr9bs/"9nF2!&~ ::t &v &&r c[S5Hn[U0UD6s $ g![a/nUS:XaUe[R"SU-S- 5 SnAMHSnAff=f)a Save PyTorch objects with retry mechanism for robustness. This function wraps torch.save with 3 retries and exponential backoff in case of save failures, which can occur due to device flushing delays or antivirus scanning. Args: *args (Any): Positional arguments to pass to torch.save. **kwargs (Any): Keyword arguments to pass to torch.save. Examples: >>> model = torch.nn.Linear(10, 1) >>> torch_save(model.state_dict(), "model.pt") r r N)range _torch_save RuntimeErrortimesleep)r7r8ies r torch_saverC{s\1X #// / #Av JJ1z " " #s  A$AAc#^# UR(aVUR(aEURS:Xa5[RmSS.U4SjjnU[lSv T[lgSv g7f)zp Workaround for ONNX torch.arange incompatibility with FP16. https://github.com/pytorch/pytorch/issues/148041. onnxN)dtypec2>T"U0UD6RU5$)zPReturn a 1-D tensor of size with values from the interval and common difference.)to)rFr7r8funcs rarangearange_patch..aranges((++E2 2r )dynamichalfformatr5rJ)r7rJrIs @r arange_patchrOsL || dkkV&;|| $ 3 3    sA-A0c#,# U(a[[U5nUR5Hup4[XU5 M Uv URR UR5 gUv g!URR UR5 f=f7f)a( Context manager to temporarily override configurations in args. Args: args (IterableSimpleNamespace): Original configuration arguments. overrides (dict[str, Any]): Dictionary of overrides to apply. Yields: (IterableSimpleNamespace): Configuration arguments with overrides applied. N)ritemssetattr__dict__update)r7 overrides original_argskeyvalues roverride_configsrYsrT #//+JC Du %, 9J MM !7!7 8  MM !7!7 8s8BA*+B*'BB)rstrrintreturnznp.ndarray | None)N)rrZr& np.ndarrayr'zlist[int] | Noner\bool)r.rZr/r]r\None)rUzdict[str, Any] | None)__doc__ __future__rr? contextlibrrpathlibrtypingrrnumpyr r5r0r+ IMREAD_COLORrr(saver=r9rCrOrYr rrisJ" %   **(+'7'7H64<,jj '2#0(r