回传数据解析，兼容v5和v10

ultralytics/utils/patches.py

@@ -0,0 +1,88 @@
+# Ultralytics YOLO 🚀, AGPL-3.0 license
+"""Monkey patches to update/extend functionality of existing functions."""
+
+import time
+from pathlib import Path
+
+import cv2
+import numpy as np
+import torch
+
+# OpenCV Multilanguage-friendly functions ------------------------------------------------------------------------------
+_imshow = cv2.imshow  # copy to avoid recursion errors
+
+
+def imread(filename: str, flags: int = cv2.IMREAD_COLOR):
+    """
+    Read an image from a file.
+
+    Args:
+        filename (str): Path to the file to read.
+        flags (int, optional): Flag that can take values of cv2.IMREAD_*. Defaults to cv2.IMREAD_COLOR.
+
+    Returns:
+        (np.ndarray): The read image.
+    """
+    return cv2.imdecode(np.fromfile(filename, np.uint8), flags)
+
+
+def imwrite(filename: str, img: np.ndarray, params=None):
+    """
+    Write an image to a file.
+
+    Args:
+        filename (str): Path to the file to write.
+        img (np.ndarray): Image to write.
+        params (list of ints, optional): Additional parameters. See OpenCV documentation.
+
+    Returns:
+        (bool): True if the file was written, False otherwise.
+    """
+    try:
+        cv2.imencode(Path(filename).suffix, img, params)[1].tofile(filename)
+        return True
+    except Exception:
+        return False
+
+
+def imshow(winname: str, mat: np.ndarray):
+    """
+    Displays an image in the specified window.
+
+    Args:
+        winname (str): Name of the window.
+        mat (np.ndarray): Image to be shown.
+    """
+    _imshow(winname.encode("unicode_escape").decode(), mat)
+
+
+# PyTorch functions ----------------------------------------------------------------------------------------------------
+_torch_save = torch.save  # copy to avoid recursion errors
+
+
+def torch_save(*args, use_dill=True, **kwargs):
+    """
+    Optionally use dill to serialize lambda functions where pickle does not, adding robustness with 3 retries and
+    exponential standoff in case of save failure.
+
+    Args:
+        *args (tuple): Positional arguments to pass to torch.save.
+        use_dill (bool): Whether to try using dill for serialization if available. Defaults to True.
+        **kwargs (any): Keyword arguments to pass to torch.save.
+    """
+    try:
+        assert use_dill
+        import dill as pickle
+    except (AssertionError, ImportError):
+        import pickle
+
+    if "pickle_module" not in kwargs:
+        kwargs["pickle_module"] = pickle
+
+    for i in range(4):  # 3 retries
+        try:
+            return _torch_save(*args, **kwargs)
+        except RuntimeError as e:  # unable to save, possibly waiting for device to flush or antivirus scan
+            if i == 3:
+                raise e
+            time.sleep((2**i) / 2)  # exponential standoff: 0.5s, 1.0s, 2.0s