Standardize license headers in Python files (#13490)

* Refactor code for speed and clarity

* Auto-format by https://ultralytics.com/actions

---------

Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>

benchmarks.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """
 Run YOLOv5 benchmarks on all supported export formats.
 

classify/predict.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """
 Run YOLOv5 classification inference on images, videos, directories, globs, YouTube, webcam, streams, etc.
 

classify/train.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """
 Train a YOLOv5 classifier model on a classification dataset.
 

classify/val.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """
 Validate a trained YOLOv5 classification model on a classification dataset.
 

detect.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """
 Run YOLOv5 detection inference on images, videos, directories, globs, YouTube, webcam, streams, etc.
 

export.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """
 Export a YOLOv5 PyTorch model to other formats. TensorFlow exports authored by https://github.com/zldrobit.
 

hubconf.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """
 PyTorch Hub models https://pytorch.org/hub/ultralytics_yolov5.
 

models/__init__.py

@@ -0,0 +1 @@
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license

models/common.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """Common modules."""
 
 import ast
@@ -750,9 +750,8 @@ class DetectMultiBackend(nn.Module):
                         scale, zero_point = output["quantization"]
                         x = (x.astype(np.float32) - zero_point) * scale  # re-scale
                     y.append(x)
-            if len(y) == 2:  # segment with (det, proto) output order reversed
-                if len(y[1].shape) != 4:
-                    y = list(reversed(y))  # should be y = (1, 116, 8400), (1, 160, 160, 32)
+            if len(y) == 2 and len(y[1].shape) != 4:
+                y = list(reversed(y))
             y = [x if isinstance(x, np.ndarray) else x.numpy() for x in y]
             y[0][..., :4] *= [w, h, w, h]  # xywh normalized to pixels
 

models/experimental.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """Experimental modules."""
 
 import math

models/tf.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """
 TensorFlow, Keras and TFLite versions of YOLOv5
 Authored by https://github.com/zldrobit in PR https://github.com/ultralytics/yolov5/pull/1127.

models/yolo.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """
 YOLO-specific modules.
 

segment/predict.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """
 Run YOLOv5 segmentation inference on images, videos, directories, streams, etc.
 

segment/train.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """
 Train a YOLOv5 segment model on a segment dataset Models and datasets download automatically from the latest YOLOv5
 release.

segment/val.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """
 Validate a trained YOLOv5 segment model on a segment dataset.
 

train.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """
 Train a YOLOv5 model on a custom dataset. Models and datasets download automatically from the latest YOLOv5 release.
 

utils/__init__.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """utils/initialization."""
 
 import contextlib

utils/activations.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """Activation functions."""
 
 import torch

utils/augmentations.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """Image augmentation functions."""
 
 import math

utils/autoanchor.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """AutoAnchor utils."""
 
 import random

utils/autobatch.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """Auto-batch utils."""
 
 from copy import deepcopy

utils/aws/__init__.py

@@ -0,0 +1 @@
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license

utils/aws/resume.py

@@ -1,4 +1,5 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # Resume all interrupted trainings in yolov5/ dir including DDP trainings
 # Usage: $ python utils/aws/resume.py
 

utils/callbacks.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """Callback utils."""
 
 import threading

utils/dataloaders.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """Dataloaders and dataset utils."""
 
 import contextlib
@@ -355,9 +355,9 @@ class LoadImages:
             self._new_video(videos[0])  # new video
         else:
             self.cap = None
-        assert (
-            self.nf > 0
-        ), f"No images or videos found in {p}. Supported formats are:\nimages: {IMG_FORMATS}\nvideos: {VID_FORMATS}"
+        assert self.nf > 0, (
+            f"No images or videos found in {p}. Supported formats are:\nimages: {IMG_FORMATS}\nvideos: {VID_FORMATS}"
+        )
 
     def __iter__(self):
         """Initializes iterator by resetting count and returns the iterator object itself."""

utils/downloads.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """Download utils."""
 
 import logging

utils/flask_rest_api/example_request.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """Perform test request."""
 
 import pprint

utils/flask_rest_api/restapi.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """Run a Flask REST API exposing one or more YOLOv5s models."""
 
 import argparse

utils/general.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """General utils."""
 
 import contextlib
@@ -495,9 +495,9 @@ def check_file(file, suffix=""):
             assert Path(file).exists() and Path(file).stat().st_size > 0, f"File download failed: {url}"  # check
         return file
     elif file.startswith("clearml://"):  # ClearML Dataset ID
-        assert (
-            "clearml" in sys.modules
-        ), "ClearML is not installed, so cannot use ClearML dataset. Try running 'pip install clearml'."
+        assert "clearml" in sys.modules, (
+            "ClearML is not installed, so cannot use ClearML dataset. Try running 'pip install clearml'."
+        )
         return file
     else:  # search
         files = []

utils/loggers/__init__.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """Logging utils."""
 
 import json

utils/loggers/clearml/README.md

@@ -4,7 +4,7 @@
 
 ## About ClearML
 
-[ClearML](https://clear.ml/) is an [open-source](https://github.com/allegroai/clearml) toolbox designed to save you time ⏱️.
+[ClearML](https://clear.ml/) is an [open-source](https://github.com/clearml/clearml) toolbox designed to save you time ⏱️.
 
 🔨 Track every YOLOv5 training run in the <b>experiment manager</b>
 

utils/loggers/clearml/__init__.py

@@ -0,0 +1 @@
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license

utils/loggers/clearml/clearml_utils.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """Main Logger class for ClearML experiment tracking."""
 
 import glob
@@ -41,11 +41,9 @@ def construct_dataset(clearml_info_string):
     with open(yaml_filenames[0]) as f:
         dataset_definition = yaml.safe_load(f)
 
-    assert set(
-        dataset_definition.keys()
-    ).issuperset(
-        {"train", "test", "val", "nc", "names"}
-    ), "The right keys were not found in the yaml file, make sure it at least has the following keys: ('train', 'test', 'val', 'nc', 'names')"
+    assert set(dataset_definition.keys()).issuperset({"train", "test", "val", "nc", "names"}), (
+        "The right keys were not found in the yaml file, make sure it at least has the following keys: ('train', 'test', 'val', 'nc', 'names')"
+    )
 
     data_dict = {
         "train": (

utils/loggers/clearml/hpo.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 
 from clearml import Task
 

utils/loggers/comet/__init__.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 
 import glob
 import json

utils/loggers/comet/comet_utils.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 
 import logging
 import os

utils/loggers/comet/hpo.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 
 import argparse
 import json

utils/loggers/wandb/__init__.py

@@ -0,0 +1 @@
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license

utils/loggers/wandb/wandb_utils.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 
 # WARNING ⚠️ wandb is deprecated and will be removed in future release.
 # See supported integrations at https://github.com/ultralytics/yolov5#integrations

utils/loss.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """Loss functions."""
 
 import torch

utils/metrics.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """Model validation metrics."""
 
 import math

utils/plots.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """Plotting utils."""
 
 import contextlib

utils/segment/__init__.py

@@ -0,0 +1 @@
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license

utils/segment/augmentations.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """Image augmentation functions."""
 
 import math

utils/segment/dataloaders.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """Dataloaders."""
 
 import os

utils/segment/general.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 
 import cv2
 import numpy as np

utils/segment/loss.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 
 import torch
 import torch.nn as nn

utils/segment/metrics.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """Model validation metrics."""
 
 import numpy as np

utils/segment/plots.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 
 import contextlib
 import math

utils/torch_utils.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """PyTorch utils."""
 
 import math
@@ -121,9 +121,9 @@ def select_device(device="", batch_size=0, newline=True):
         os.environ["CUDA_VISIBLE_DEVICES"] = "-1"  # force torch.cuda.is_available() = False
     elif device:  # non-cpu device requested
         os.environ["CUDA_VISIBLE_DEVICES"] = device  # set environment variable - must be before assert is_available()
-        assert torch.cuda.is_available() and torch.cuda.device_count() >= len(
-            device.replace(",", "")
-        ), f"Invalid CUDA '--device {device}' requested, use '--device cpu' or pass valid CUDA device(s)"
+        assert torch.cuda.is_available() and torch.cuda.device_count() >= len(device.replace(",", "")), (
+            f"Invalid CUDA '--device {device}' requested, use '--device cpu' or pass valid CUDA device(s)"
+        )
 
     if not cpu and not mps and torch.cuda.is_available():  # prefer GPU if available
         devices = device.split(",") if device else "0"  # range(torch.cuda.device_count())  # i.e. 0,1,6,7

utils/triton.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """Utils to interact with the Triton Inference Server."""
 
 import typing

val.py

@@ -1,4 +1,4 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
 """
 Validate a trained YOLOv5 detection model on a detection dataset.