Cleanup (#168)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Kalen Michael <kalenmike@gmail.com>

ultralytics/__init__.py

@@ -1,6 +1,9 @@
-__version__ = "8.0.0.dev0"
+# Ultralytics YOLO 🚀, GPL-3.0 license
 
+__version__ = "8.0.0"
+
+from ultralytics.hub import checks
 from ultralytics.yolo.engine.model import YOLO
 from ultralytics.yolo.utils import ops
 
-__all__ = ["__version__", "YOLO", "hub"]  # allow simpler import
+__all__ = ["__version__", "YOLO", "hub", "checks"]  # allow simpler import

ultralytics/hub/__init__.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import os
 import shutil
 

ultralytics/hub/auth.py

@@ -1,7 +1,8 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import requests
 
-from ultralytics.hub.config import HUB_API_ROOT
-from ultralytics.hub.utils import request_with_credentials
+from ultralytics.hub.utils import HUB_API_ROOT, request_with_credentials
 from ultralytics.yolo.utils import is_colab
 
 API_KEY_PATH = "https://hub.ultralytics.com/settings?tab=api+keys"

ultralytics/hub/config.py

@@ -1,12 +0,0 @@
-import os
-
-# Global variables
-REPO_URL = "https://github.com/ultralytics/yolov5.git"
-REPO_BRANCH = "ultralytics/HUB"  # "master"
-
-ENVIRONMENT = os.environ.get("ULTRALYTICS_ENV", "production")
-if ENVIRONMENT == 'production':
-    HUB_API_ROOT = "https://api.ultralytics.com"
-else:
-    HUB_API_ROOT = "http://127.0.0.1:8000"
-    print(f'Connected to development server on {HUB_API_ROOT}')

ultralytics/hub/session.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import signal
 import sys
 from pathlib import Path
@@ -6,8 +8,7 @@ from time import sleep
 import requests
 
 from ultralytics import __version__
-from ultralytics.hub.config import HUB_API_ROOT
-from ultralytics.hub.utils import check_dataset_disk_space, smart_request
+from ultralytics.hub.utils import HUB_API_ROOT, check_dataset_disk_space, smart_request
 from ultralytics.yolo.utils import LOGGER, is_colab, threaded
 
 AGENT_NAME = f'python-{__version__}-colab' if is_colab() else f'python-{__version__}-local'

ultralytics/hub/utils.py

@@ -1,14 +1,17 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
+import os
 import shutil
 import threading
 import time
 
 import requests
 
-from ultralytics.hub.config import HUB_API_ROOT
-from ultralytics.yolo.utils import DEFAULT_CONFIG_DICT, LOGGER, RANK, SETTINGS, colorstr, emojis
+from ultralytics.yolo.utils import DEFAULT_CONFIG_DICT, LOGGER, RANK, SETTINGS, TryExcept, colorstr, emojis
 
 PREFIX = colorstr('Ultralytics: ')
 HELP_MSG = 'If this issue persists please visit https://github.com/ultralytics/hub/issues for assistance.'
+HUB_API_ROOT = os.environ.get("ULTRALYTICS_HUB_API", "https://api.ultralytics.com")
 
 
 def check_dataset_disk_space(url='https://github.com/ultralytics/yolov5/releases/download/v1.0/coco128.zip', sf=2.0):
@@ -90,7 +93,6 @@ def smart_request(*args, retry=3, timeout=30, thread=True, code=-1, method="post
         requests.Response: The HTTP response object. If the request is executed in a separate thread, returns None.
     """
     retry_codes = (408, 500)  # retry only these codes
-    methods = {'post': requests.post, 'get': requests.get}  # request methods
 
     def func(*func_args, **func_kwargs):
         r = None  # response
@@ -98,7 +100,10 @@ def smart_request(*args, retry=3, timeout=30, thread=True, code=-1, method="post
         for i in range(retry + 1):
             if (time.time() - t0) > timeout:
                 break
-            r = methods[method](*func_args, **func_kwargs)  # i.e. post(url, data, json, files)
+            if method == 'post':
+                r = requests.post(*func_args, **func_kwargs)  # i.e. post(url, data, json, files)
+            elif method == 'get':
+                r = requests.get(*func_args, **func_kwargs)  # i.e. get(url, data, json, files)
             if r.status_code == 200:
                 break
             try:
@@ -125,7 +130,8 @@ def smart_request(*args, retry=3, timeout=30, thread=True, code=-1, method="post
         return func(*args, **kwargs)
 
 
-def sync_analytics(cfg, all_keys=False, enabled=False):
+@TryExcept()
+def sync_analytics(cfg, all_keys=False, enabled=True):
     """
    Sync analytics data if enabled in the global settings
 
@@ -137,8 +143,8 @@ def sync_analytics(cfg, all_keys=False, enabled=False):
     if SETTINGS['sync'] and RANK in {-1, 0} and enabled:
         cfg = dict(cfg)  # convert type from DictConfig to dict
         if not all_keys:
-            cfg = {k: v for k, v in cfg.items() if v != DEFAULT_CONFIG_DICT[k]}  # retain only non-default values
+            cfg = {k: v for k, v in cfg.items() if v != DEFAULT_CONFIG_DICT.get(k, None)}  # retain non-default values
         cfg['uuid'] = SETTINGS['uuid']  # add the device UUID to the configuration data
 
-        # Send a request to the HUB API to sync the analytics data
-        smart_request(f'{HUB_API_ROOT}/v1/usage/anonymous', data=cfg, headers=None, code=3, retry=0, verbose=False)
+        # Send a request to the HUB API to sync analytics
+        smart_request(f'{HUB_API_ROOT}/v1/usage/anonymous', json=cfg, headers=None, code=3, retry=0, verbose=False)

ultralytics/nn/autobackend.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import json
 import platform
 from collections import OrderedDict, namedtuple
@@ -65,6 +67,7 @@ class AutoBackend(nn.Module):
             names = model.module.names if hasattr(model, 'module') else model.names  # get class names
             model.half() if fp16 else model.float()
             self.model = model  # explicitly assign for to(), cpu(), cuda(), half()
+            pt = True
         elif pt:  # PyTorch
             from ultralytics.nn.tasks import attempt_load_weights
             model = attempt_load_weights(weights if isinstance(weights, list) else w,

ultralytics/nn/modules.py

@@ -1,4 +1,4 @@
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+# Ultralytics YOLO 🚀, GPL-3.0 license
 """
 Common modules
 """

ultralytics/nn/tasks.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import contextlib
 from copy import deepcopy
 

ultralytics/yolo/__init__.py

@@ -1 +1,3 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 from . import v8

ultralytics/yolo/cli.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import shutil
 from pathlib import Path
 

ultralytics/yolo/configs/__init__.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 from pathlib import Path
 from typing import Dict, Union
 

ultralytics/yolo/configs/default.yaml

@@ -1,4 +1,4 @@
-# YOLO 🚀 by Ultralytics, GPL-3.0 license
+# Ultralytics YOLO 🚀, GPL-3.0 license
 # Default training settings and hyperparameters for medium-augmentation COCO training
 
 task: "detect" # choices=['detect', 'segment', 'classify', 'init'] # init is a special case. Specify task to run.

ultralytics/yolo/configs/hydra_patch.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import sys
 from difflib import get_close_matches
 from textwrap import dedent

ultralytics/yolo/data/__init__.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 from .base import BaseDataset
 from .build import build_classification_dataloader, build_dataloader
 from .dataset import ClassificationDataset, SemanticDataset, YOLODataset

ultralytics/yolo/data/augment.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import math
 import random
 from copy import deepcopy

ultralytics/yolo/data/base.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import glob
 import math
 import os

ultralytics/yolo/data/build.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import os
 import random
 

ultralytics/yolo/data/dataloaders/stream_loaders.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import glob
 import math
 import os

ultralytics/yolo/data/dataloaders/v5augmentations.py

@@ -1,4 +1,4 @@
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+# Ultralytics YOLO 🚀, GPL-3.0 license
 """
 Image augmentation functions
 """

ultralytics/yolo/data/dataloaders/v5loader.py

@@ -1,4 +1,4 @@
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+# Ultralytics YOLO 🚀, GPL-3.0 license
 """
 Dataloaders and dataset utils
 """

ultralytics/yolo/data/dataset.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 from itertools import repeat
 from multiprocessing.pool import Pool
 from pathlib import Path

ultralytics/yolo/data/dataset_wrappers.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import collections
 from copy import deepcopy
 

ultralytics/yolo/data/datasets/coco.yaml

@@ -1,4 +1,4 @@
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+# Ultralytics YOLO 🚀, GPL-3.0 license
 # COCO 2017 dataset http://cocodataset.org by Microsoft
 # Example usage: python train.py --data coco.yaml
 # parent

ultralytics/yolo/data/datasets/coco128-seg.yaml

@@ -1,4 +1,4 @@
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+# Ultralytics YOLO 🚀, GPL-3.0 license
 # COCO128-seg dataset https://www.kaggle.com/ultralytics/coco128 (first 128 images from COCO train2017) by Ultralytics
 # Example usage: python train.py --data coco128.yaml
 # parent

ultralytics/yolo/data/datasets/coco128.yaml

@@ -1,4 +1,4 @@
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+# Ultralytics YOLO 🚀, GPL-3.0 license
 # COCO128 dataset https://www.kaggle.com/ultralytics/coco128 (first 128 images from COCO train2017) by Ultralytics
 # Example usage: python train.py --data coco128.yaml
 # parent

ultralytics/yolo/data/scripts/download_weights.sh

@@ -1,5 +1,5 @@
 #!/bin/bash
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+# Ultralytics YOLO 🚀, GPL-3.0 license
 # Download latest models from https://github.com/ultralytics/yolov5/releases
 # Example usage: bash data/scripts/download_weights.sh
 # parent

ultralytics/yolo/data/scripts/get_coco.sh

@@ -1,5 +1,5 @@
 #!/bin/bash
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+# Ultralytics YOLO 🚀, GPL-3.0 license
 # Download COCO 2017 dataset http://cocodataset.org
 # Example usage: bash data/scripts/get_coco.sh
 # parent

ultralytics/yolo/data/scripts/get_coco128.sh

@@ -1,5 +1,5 @@
 #!/bin/bash
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+# Ultralytics YOLO 🚀, GPL-3.0 license
 # Download COCO128 dataset https://www.kaggle.com/ultralytics/coco128 (first 128 images from COCO train2017)
 # Example usage: bash data/scripts/get_coco128.sh
 # parent

ultralytics/yolo/data/scripts/get_imagenet.sh

@@ -1,5 +1,5 @@
 #!/bin/bash
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+# Ultralytics YOLO 🚀, GPL-3.0 license
 # Download ILSVRC2012 ImageNet dataset https://image-net.org
 # Example usage: bash data/scripts/get_imagenet.sh
 # parent

ultralytics/yolo/data/utils.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import contextlib
 import hashlib
 import os

ultralytics/yolo/engine/exporter.py

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

ultralytics/yolo/engine/model.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 from pathlib import Path
 
 from ultralytics import yolo  # noqa

ultralytics/yolo/engine/predictor.py

@@ -1,4 +1,4 @@
-# predictor engine by Ultralytics
+# Ultralytics YOLO 🚀, GPL-3.0 license
 """
 Run prediction on images, videos, directories, globs, YouTube, webcam, streams, etc.
 Usage - sources:

ultralytics/yolo/engine/trainer.py

@@ -1,3 +1,4 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
 """
 Simple training loop; Boilerplate that could apply to any arbitrary neural network,
 """

ultralytics/yolo/engine/validator.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import json
 from collections import defaultdict
 from pathlib import Path
@@ -86,6 +88,7 @@ class BaseValidator:
             self.model = model
             self.loss = torch.zeros_like(trainer.loss_items, device=trainer.device)
             self.args.plots = trainer.epoch == trainer.epochs - 1  # always plot final epoch
+            model.eval()
         else:
             callbacks.add_integration_callbacks(self)
             self.run_callbacks('on_val_start')
@@ -106,17 +109,17 @@ class BaseValidator:
                         f'Forcing --batch-size 1 square inference (1,3,{imgsz},{imgsz}) for non-PyTorch models')
 
             if isinstance(self.args.data, str) and self.args.data.endswith(".yaml"):
-                data = check_dataset_yaml(self.args.data)
+                self.data = check_dataset_yaml(self.args.data)
             else:
-                data = check_dataset(self.args.data)
+                self.data = check_dataset(self.args.data)
 
             if self.device.type == 'cpu':
                 self.args.workers = 0  # faster CPU val as time dominated by inference, not dataloading
             self.dataloader = self.dataloader or \
-                              self.get_dataloader(data.get("val") or data.set("test"), self.args.batch)
-            self.data = data
+                              self.get_dataloader(self.data.get("val") or self.data.set("test"), self.args.batch)
 
-        model.eval()
+            model.eval()
+            model.warmup(imgsz=(1 if pt else self.args.batch, 3, imgsz, imgsz))  # warmup
 
         dt = Profile(), Profile(), Profile(), Profile()
         n_batches = len(self.dataloader)

ultralytics/yolo/utils/__init__.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import contextlib
 import inspect
 import logging.config

ultralytics/yolo/utils/autobatch.py

@@ -1,4 +1,4 @@
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+# Ultralytics YOLO 🚀, GPL-3.0 license
 """
 Auto-batch utils
 """

ultralytics/yolo/utils/callbacks/base.py

@@ -1,4 +1,7 @@
-# Ultralytics YOLO base callbacks
+# Ultralytics YOLO 🚀, GPL-3.0 license
+"""
+Base callbacks
+"""
 
 
 # Trainer callbacks ----------------------------------------------------------------------------------------------------

ultralytics/yolo/utils/callbacks/clearml.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 from ultralytics.yolo.utils.torch_utils import get_flops, get_num_params
 
 try:

ultralytics/yolo/utils/callbacks/comet.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 from ultralytics.yolo.utils.torch_utils import get_flops, get_num_params
 
 try:

ultralytics/yolo/utils/callbacks/hub.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import json
 from time import time
 

ultralytics/yolo/utils/callbacks/tensorboard.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 from torch.utils.tensorboard import SummaryWriter
 
 writer = None  # TensorBoard SummaryWriter instance

ultralytics/yolo/utils/callbacks/wb.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 from ultralytics.yolo.utils.torch_utils import get_flops, get_num_params
 
 try:

ultralytics/yolo/utils/checks.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import glob
 import inspect
 import math
@@ -62,8 +64,7 @@ def check_imgsz(imgsz, stride=32, min_dim=1, floor=0):
         LOGGER.warning(f'WARNING ⚠️ --img-size {imgsz} must be multiple of max stride {stride}, updating to {sz}')
 
     # Add missing dimensions if necessary
-    if min_dim == 2 and len(sz) == 1:
-        sz = [sz[0], sz[0]]
+    sz = [sz[0], sz[0]] if min_dim == 2 and len(sz) == 1 else sz[0] if min_dim == 1 and len(sz) == 1 else sz
 
     return sz
 

ultralytics/yolo/utils/dist.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import os
 import shutil
 import socket

ultralytics/yolo/utils/downloads.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import logging
 import os
 import subprocess

ultralytics/yolo/utils/files.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import contextlib
 import glob
 import os

ultralytics/yolo/utils/instance.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 from collections import abc
 from itertools import repeat
 from numbers import Number

ultralytics/yolo/utils/loss.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import torch
 import torch.nn as nn
 import torch.nn.functional as F

ultralytics/yolo/utils/metrics.py

@@ -1,4 +1,4 @@
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+# Ultralytics YOLO 🚀, GPL-3.0 license
 """
 Model validation metrics
 """

ultralytics/yolo/utils/ops.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import contextlib
 import math
 import re

ultralytics/yolo/utils/plotting.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import contextlib
 import math
 from pathlib import Path

ultralytics/yolo/utils/tal.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import torch
 import torch.nn as nn
 import torch.nn.functional as F

ultralytics/yolo/utils/torch_utils.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import math
 import os
 import platform
@@ -59,7 +61,7 @@ def DDP_model(model):
 def select_device(device='', batch_size=0, newline=False):
     # device = None or 'cpu' or 0 or '0' or '0,1,2,3'
     ver = git_describe() or ultralytics.__version__  # git commit or pip package version
-    s = f'Ultralytics YOLO 🚀 {ver} Python-{platform.python_version()} torch-{torch.__version__} '
+    s = f'Ultralytics YOLOv{ver} 🚀 Python-{platform.python_version()} torch-{torch.__version__} '
     device = str(device).strip().lower().replace('cuda:', '').replace('none', '')  # to string, 'cuda:0' to '0'
     cpu = device == 'cpu'
     mps = device == 'mps'  # Apple Metal Performance Shaders (MPS)

ultralytics/yolo/v8/__init__.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 from pathlib import Path
 
 from ultralytics.yolo.v8 import classify, detect, segment

ultralytics/yolo/v8/classify/__init__.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 from ultralytics.yolo.v8.classify.predict import ClassificationPredictor, predict
 from ultralytics.yolo.v8.classify.train import ClassificationTrainer, train
 from ultralytics.yolo.v8.classify.val import ClassificationValidator, val

ultralytics/yolo/v8/classify/predict.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import hydra
 import torch
 

ultralytics/yolo/v8/classify/train.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import hydra
 import torch
 import torchvision

ultralytics/yolo/v8/classify/val.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import hydra
 
 from ultralytics.yolo.data import build_classification_dataloader

ultralytics/yolo/v8/detect/__init__.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 from .predict import DetectionPredictor, predict
 from .train import DetectionTrainer, train
 from .val import DetectionValidator, val

ultralytics/yolo/v8/detect/predict.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import hydra
 import torch
 

ultralytics/yolo/v8/detect/train.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 from copy import copy
 
 import hydra

ultralytics/yolo/v8/detect/val.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import os
 from pathlib import Path
 

ultralytics/yolo/v8/models/cls/yolov8l-cls.yaml

@@ -1,4 +1,4 @@
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+# Ultralytics YOLO 🚀, GPL-3.0 license
 
 # Parameters
 nc: 1000  # number of classes

ultralytics/yolo/v8/models/cls/yolov8m-cls.yaml

@@ -1,4 +1,4 @@
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+# Ultralytics YOLO 🚀, GPL-3.0 license
 
 # Parameters
 nc: 1000  # number of classes

ultralytics/yolo/v8/models/cls/yolov8n-cls.yaml

@@ -1,4 +1,4 @@
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+# Ultralytics YOLO 🚀, GPL-3.0 license
 
 # Parameters
 nc: 1000  # number of classes

ultralytics/yolo/v8/models/cls/yolov8s-cls.yaml

@@ -1,4 +1,4 @@
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+# Ultralytics YOLO 🚀, GPL-3.0 license
 
 # Parameters
 nc: 1000  # number of classes

ultralytics/yolo/v8/models/cls/yolov8x-cls.yaml

@@ -1,4 +1,4 @@
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+# Ultralytics YOLO 🚀, GPL-3.0 license
 
 # Parameters
 nc: 1000  # number of classes

ultralytics/yolo/v8/models/seg/yolov8l-seg.yaml

@@ -1,4 +1,4 @@
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+# Ultralytics YOLO 🚀, GPL-3.0 license
 
 # Parameters
 nc: 80  # number of classes

ultralytics/yolo/v8/models/seg/yolov8m-seg.yaml

@@ -1,4 +1,4 @@
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+# Ultralytics YOLO 🚀, GPL-3.0 license
 
 # Parameters
 nc: 80  # number of classes

ultralytics/yolo/v8/models/seg/yolov8n-seg.yaml

@@ -1,4 +1,4 @@
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+# Ultralytics YOLO 🚀, GPL-3.0 license
 
 # Parameters
 nc: 80  # number of classes

ultralytics/yolo/v8/models/seg/yolov8s-seg.yaml

@@ -1,4 +1,4 @@
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+# Ultralytics YOLO 🚀, GPL-3.0 license
 
 # Parameters
 nc: 80  # number of classes

ultralytics/yolo/v8/models/seg/yolov8x-seg.yaml

@@ -1,4 +1,4 @@
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+# Ultralytics YOLO 🚀, GPL-3.0 license
 
 # Parameters
 nc: 80  # number of classes

ultralytics/yolo/v8/models/yolov8l.yaml

@@ -1,4 +1,4 @@
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+# Ultralytics YOLO 🚀, GPL-3.0 license
 
 # Parameters
 nc: 80  # number of classes

ultralytics/yolo/v8/models/yolov8m.yaml

@@ -1,4 +1,4 @@
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+# Ultralytics YOLO 🚀, GPL-3.0 license
 
 # Parameters
 nc: 80  # number of classes

ultralytics/yolo/v8/models/yolov8n.yaml

@@ -1,4 +1,4 @@
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+# Ultralytics YOLO 🚀, GPL-3.0 license
 
 # Parameters
 nc: 80  # number of classes

ultralytics/yolo/v8/models/yolov8s.yaml

@@ -1,4 +1,4 @@
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+# Ultralytics YOLO 🚀, GPL-3.0 license
 
 # Parameters
 nc: 80  # number of classes

ultralytics/yolo/v8/models/yolov8x.yaml

@@ -1,4 +1,4 @@
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+# Ultralytics YOLO 🚀, GPL-3.0 license
 
 # Parameters
 nc: 80  # number of classes

ultralytics/yolo/v8/models/yolov8x6.yaml

@@ -1,4 +1,4 @@
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+# Ultralytics YOLO 🚀, GPL-3.0 license
 
 # Parameters
 nc: 80  # number of classes

ultralytics/yolo/v8/segment/__init__.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 from .predict import SegmentationPredictor, predict
 from .train import SegmentationTrainer, train
 from .val import SegmentationValidator, val

ultralytics/yolo/v8/segment/predict.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import hydra
 import torch
 

ultralytics/yolo/v8/segment/train.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 from copy import copy
 
 import hydra

ultralytics/yolo/v8/segment/val.py

@@ -1,3 +1,5 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
 import os
 from multiprocessing.pool import ThreadPool
 from pathlib import Path