|hu dZddlZddlmZddlmZddlmZddlmZm Z m Z m Z ddl Z ddl ZddlZe j Ze j$fdeded e ej*fd Zdded ej*d e e ed efd Zdedej*d dfdZej2ZdZdZedZedde e eeffdZy)zDMonkey patches to update/extend functionality of existing functions.N)contextmanager)copy)Path)AnyDictListOptionalfilenameflagsreturnctj|tj}|jdrft j |tj \}}|r>> img = imread("path/to/image.jpg") >>> img = imread("path/to/image.jpg", cv2.IMREAD_GRAYSCALE) )z.tiffz.tifr)axisN).N) npfromfileuint8endswithcv2 imdecodemultiIMREAD_UNCHANGEDlenndimstackimdecode)r r file_bytessuccessframesims X/var/www/html/test/engine/venv/lib/python3.12/site-packages/ultralytics/utils/patches.pyimreadr"sXrxx0J*+++J8L8LM  #F q 0VAY^^q5H6!9 fbhhW]deNf f \\*e , "1 r)}4"4imgparamsc tjt|j||dj |y#t $rYywxYw)aI Write an image to a file with multilanguage filename support. Args: filename (str): Path to the file to write. img (np.ndarray): Image to write. params (List[int], optional): Additional parameters for image encoding. Returns: (bool): True if the file was written successfully, False otherwise. Examples: >>> import numpy as np >>> img = np.zeros((100, 100, 3), dtype=np.uint8) # Create a black image >>> success = imwrite("output.jpg", img) # Write image to file >>> print(success) True rTF)rimencodersuffixtofile Exception)r r$r%s r!imwriter+-sF& 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)r,r-s r!imshowr3Gs!$ GNN+ , 3 3 5s;r#cNddlm}|r d|vrd|d<tj|i|S)aH 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_utilsr5torchload)argskwargsr5s r! torch_loadr<`s/"9nF2!&~ ::t &v &&r#ctdD]} t|i|cSy#t$r,}|dk(r|tjd|zdz Yd}~Cd}~wwxYw)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") rrN)range _torch_save RuntimeErrortimesleep)r:r;ies r! torch_saverFysa1X# #// /# #Av JJ1z " " #s  A"AAc#K|jrN|jrB|jdk(r3tjddfd }|t_dt_ydyw)z| Workaround for ONNX torch.arange incompatibility with FP16. https://github.com/pytorch/pytorch/issues/148041. onnxN)dtypec2|i|j|S)zPReturn a 1-D tensor of size with values from the interval and common difference.)to)rIr:r;funcs r!arangezarange_patch..aranges((++E2 2r#)dynamichalfformatr8rM)r:rMrLs @r! arange_patchrQsH || dkkV&;|| $ 3    sA A# overridesc#"K|r[t|}|jD]\}}t||| ||jj |jy|y#|jj |jwxYww)aD 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)r:rR original_argskeyvalues r!override_configsr[s|T #//+ &JC D#u % & 9J MM !7!7 8  MM !7!7 8s3BA%+B%'B  B)N)__doc__rB contextlibrrpathlibrtypingrrrr rnumpyrr8r3r0 IMREAD_COLORstrintndarrayr"boolr+saver@r<rFrQr[r#r!rhsJ %,,   **(+'7'75S55HRZZr#