Update LICENSE to AGPL-3.0 (#2031)

This commit is contained in:
Glenn Jocher
2023-04-14 15:17:41 +02:00
committed by GitHub
parent 5065ca36a8
commit 2c6fc0a444
131 changed files with 200 additions and 213 deletions

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
__version__ = '8.0.77'

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# Argoverse-HD dataset (ring-front-center camera) http://www.cs.cmu.edu/~mengtial/proj/streaming/ by Argo AI
# Example usage: yolo train data=Argoverse.yaml
# parent

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# Global Wheat 2020 dataset http://www.global-wheat.com/ by University of Saskatchewan
# Example usage: yolo train data=GlobalWheat2020.yaml
# parent

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# ImageNet-1k dataset https://www.image-net.org/index.php by Stanford University
# Simplified class names from https://github.com/anishathalye/imagenet-simple-labels
# Example usage: yolo train task=classify data=imagenet

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# Objects365 dataset https://www.objects365.org/ by Megvii
# Example usage: yolo train data=Objects365.yaml
# parent

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# SKU-110K retail items dataset https://github.com/eg4000/SKU110K_CVPR19 by Trax Retail
# Example usage: yolo train data=SKU-110K.yaml
# parent

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# PASCAL VOC dataset http://host.robots.ox.ac.uk/pascal/VOC by University of Oxford
# Example usage: yolo train data=VOC.yaml
# parent

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# VisDrone2019-DET dataset https://github.com/VisDrone/VisDrone-Dataset by Tianjin University
# Example usage: yolo train data=VisDrone.yaml
# parent

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# COCO 2017 dataset http://cocodataset.org by Microsoft
# Example usage: yolo train data=coco-pose.yaml
# parent

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# COCO 2017 dataset http://cocodataset.org by Microsoft
# Example usage: yolo train data=coco.yaml
# parent

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# COCO128-seg dataset https://www.kaggle.com/ultralytics/coco128 (first 128 images from COCO train2017) by Ultralytics
# Example usage: yolo train data=coco128.yaml
# parent

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# COCO128 dataset https://www.kaggle.com/ultralytics/coco128 (first 128 images from COCO train2017) by Ultralytics
# Example usage: yolo train data=coco128.yaml
# parent

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# COCO8-pose dataset (first 8 images from COCO train2017) by Ultralytics
# Example usage: yolo train data=coco8-pose.yaml
# parent

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# COCO8-seg dataset (first 8 images from COCO train2017) by Ultralytics
# Example usage: yolo train data=coco8-seg.yaml
# parent

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# COCO8 dataset (first 8 images from COCO train2017) by Ultralytics
# Example usage: yolo train data=coco8.yaml
# parent

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# DIUx xView 2018 Challenge https://challenge.xviewdataset.org by U.S. National Geospatial-Intelligence Agency (NGA)
# -------- DOWNLOAD DATA MANUALLY and jar xf val_images.zip to 'datasets/xView' before running train command! --------
# Example usage: yolo train data=xView.yaml

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import requests

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import requests

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import signal
import sys
from pathlib import Path

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import os
import platform

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# Parameters
nc: 80 # number of classes

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# Parameters
nc: 80 # number of classes

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# Parameters
nc: 80 # number of classes

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# Parameters
nc: 80 # number of classes

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# Parameters
nc: 80 # number of classes

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# YOLOv8-cls image classification model. For Usage examples see https://docs.ultralytics.com/tasks/classify
# Parameters

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# YOLOv8 object detection model with P2-P5 outputs. For Usage examples see https://docs.ultralytics.com/tasks/detect
# Parameters

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# YOLOv8 object detection model with P3-P6 outputs. For Usage examples see https://docs.ultralytics.com/tasks/detect
# Parameters

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# YOLOv8 object detection model with P3-P6 outputs. For Usage examples see https://docs.ultralytics.com/tasks/detect
# Parameters

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# YOLOv8-pose keypoints/pose estimation model. For Usage examples see https://docs.ultralytics.com/tasks/pose
# Parameters

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# YOLOv8-seg instance segmentation model. For Usage examples see https://docs.ultralytics.com/tasks/segment
# Parameters

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# YOLOv8 object detection model with P3-P5 outputs. For Usage examples see https://docs.ultralytics.com/tasks/detect
# Parameters

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import ast
import contextlib
import json

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
"""
Common modules
"""

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
"""
Common modules
"""

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import contextlib
from copy import deepcopy

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
from .track import register_tracker
from .trackers import BOTSORT, BYTETracker

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# Default YOLO tracker settings for BoT-SORT tracker https://github.com/NirAharon/BoT-SORT
tracker_type: botsort # tracker type, ['botsort', 'bytetrack']

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# Default YOLO tracker settings for ByteTrack tracker https://github.com/ifzhang/ByteTrack
tracker_type: bytetrack # tracker type, ['botsort', 'bytetrack']

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
from functools import partial

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
from .bot_sort import BOTSORT
from .byte_tracker import BYTETracker

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
from collections import OrderedDict

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
from collections import deque

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import numpy as np

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import copy

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import numpy as np
import scipy.linalg

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import numpy as np
import scipy

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
from . import v8

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import contextlib
import re
import shutil

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# Default training settings and hyperparameters for medium-augmentation COCO training
task: detect # YOLO task, i.e. detect, segment, classify, pose

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
from .base import BaseDataset
from .build import build_classification_dataloader, build_dataloader, load_inference_source

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import math
import random

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import glob
import math

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import os
import random

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import glob
import math

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
"""
Image augmentation functions
"""

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
"""
Dataloaders and dataset utils
"""

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
from itertools import repeat
from multiprocessing.pool import ThreadPool

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import collections
from copy import deepcopy

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#!/bin/bash
# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
# Download latest models from https://github.com/ultralytics/assets/releases
# Example usage: bash ultralytics/yolo/data/scripts/download_weights.sh
# parent

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

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#!/bin/bash
# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-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

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

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import contextlib
import hashlib

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
"""
Export a YOLOv8 PyTorch model to other formats. TensorFlow exports authored by https://github.com/zldrobit
@ -213,7 +213,7 @@ class Exporter:
self.metadata = {
'description': description,
'author': 'Ultralytics',
'license': 'GPL-3.0 https://ultralytics.com/license',
'license': 'AGPL-3.0 https://ultralytics.com/license',
'version': __version__,
'stride': int(max(model.stride)),
'task': model.task,

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import sys
from pathlib import Path

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
"""
Run prediction on images, videos, directories, globs, YouTube, webcam, streams, etc.

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
"""
Ultralytics Results, Boxes and Masks classes for handling inference results

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
"""
Train a model on a dataset

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
"""
Check a model's accuracy on a test or val split of a dataset

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import contextlib
import inspect

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
"""
Functions for estimating the best YOLO batch size to use a fraction of the available CUDA memory in PyTorch.
"""

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
"""
Benchmark a YOLO model formats for speed and accuracy

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
"""
Base callbacks
"""

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import re
import matplotlib.image as mpimg

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import os
from pathlib import Path

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import json
from time import time

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import os
import re

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
from ultralytics.yolo.utils import LOGGER, TESTS_RUNNING, colorstr
try:

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
from ultralytics.yolo.utils.torch_utils import get_flops, get_num_params

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import contextlib
import glob
import inspect

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import os
import re

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import contextlib
import subprocess

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
from ultralytics.yolo.utils import emojis

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import contextlib
import glob

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
from collections import abc
from itertools import repeat

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import torch
import torch.nn as nn

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
"""
Model validation metrics
"""

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import contextlib
import math

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import torch
import torch.nn as nn

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import math
import os

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
from ultralytics.yolo.v8 import classify, detect, pose, segment

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
from ultralytics.yolo.v8.classify.predict import ClassificationPredictor, predict
from ultralytics.yolo.v8.classify.train import ClassificationTrainer, train

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import torch

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import torch
import torchvision

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
from ultralytics.yolo.data import build_classification_dataloader
from ultralytics.yolo.engine.validator import BaseValidator

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
from .predict import DetectionPredictor, predict
from .train import DetectionTrainer, train

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import torch

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
from copy import copy
import numpy as np

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# Ultralytics YOLO 🚀, GPL-3.0 license
# Ultralytics YOLO 🚀, AGPL-3.0 license
import os
from pathlib import Path

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