Standardize license headers in Python files (#18696)

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
This commit is contained in:
Paula Derrenger 2025-01-15 15:36:11 +01:00 committed by GitHub
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commit deb87d8ce3
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165 changed files with 169 additions and 169 deletions

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
""" """
Automates the building and post-processing of MkDocs documentation, particularly for projects with multilingual content. Automates the building and post-processing of MkDocs documentation, particularly for projects with multilingual content.
It streamlines the workflow for generating localized versions of the documentation and updating HTML links to ensure It streamlines the workflow for generating localized versions of the documentation and updating HTML links to ensure

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
""" """
Helper file to build Ultralytics Docs reference section. Recursively walks through ultralytics dir and builds an MkDocs Helper file to build Ultralytics Docs reference section. Recursively walks through ultralytics dir and builds an MkDocs
reference section of *.md files composed of classes and functions, and also creates a nav menu for use in mkdocs.yaml. reference section of *.md files composed of classes and functions, and also creates a nav menu for use in mkdocs.yaml.

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@ -8,7 +8,7 @@ keywords: MobileSAM, image segmentation, lightweight model, fast segmentation, m
# Mobile Segment Anything (MobileSAM) # Mobile Segment Anything (MobileSAM)
The MobileSAM paper is now available on [arXiv](https://arxiv.org/pdf/2306.14289.pdf). The MobileSAM paper is now available on [arXiv](https://arxiv.org/pdf/2306.14289).
A demonstration of MobileSAM running on a CPU can be accessed at this [demo link](https://huggingface.co/spaces/dhkim2810/MobileSAM). The performance on a Mac i5 CPU takes approximately 3 seconds. On the Hugging Face demo, the interface and lower-performance CPUs contribute to a slower response, but it continues to function effectively. A demonstration of MobileSAM running on a CPU can be accessed at this [demo link](https://huggingface.co/spaces/dhkim2810/MobileSAM). The performance on a Mac i5 CPU takes approximately 3 seconds. On the Hugging Face demo, the interface and lower-performance CPUs contribute to a slower response, but it continues to function effectively.

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@ -10,7 +10,7 @@ keywords: ClearML, YOLOv5, machine learning, experiment tracking, data versionin
## About ClearML ## 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> 🔨 Track every YOLOv5 training run in the <b>experiment manager</b>

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# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import argparse import argparse
import cv2 import cv2

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import argparse import argparse
import time import time

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import argparse import argparse

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import argparse import argparse

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import argparse import argparse
from collections import defaultdict from collections import defaultdict

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import argparse import argparse
from pathlib import Path from pathlib import Path

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import argparse import argparse

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import argparse import argparse
from typing import Tuple, Union from typing import Tuple, Union

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from ultralytics.utils import ASSETS, ROOT, WEIGHTS_DIR, checks from ultralytics.utils import ASSETS, ROOT, WEIGHTS_DIR, checks

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import shutil import shutil
from pathlib import Path from pathlib import Path

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import subprocess import subprocess

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from itertools import product from itertools import product
from pathlib import Path from pathlib import Path

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import sys import sys
from unittest import mock from unittest import mock

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import shutil import shutil
import uuid import uuid

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import contextlib import contextlib
import os import os

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import contextlib import contextlib
import csv import csv

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import cv2 import cv2
import pytest import pytest

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
__version__ = "8.3.61" __version__ = "8.3.61"

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import shutil import shutil
import subprocess import subprocess

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from .base import BaseDataset from .base import BaseDataset
from .build import build_dataloader, build_grounding, build_yolo_dataset, load_inference_source from .build import build_dataloader, build_grounding, build_yolo_dataset, load_inference_source

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from pathlib import Path from pathlib import Path

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import math import math
import random import random

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import glob import glob
import math import math

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import os import os
import random import random

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import json import json
import random import random

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import json import json
from collections import defaultdict from collections import defaultdict

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import glob import glob
import math import math

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import itertools import itertools
from glob import glob from glob import glob

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import hashlib import hashlib
import json import json

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license

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

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@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import inspect import inspect
from pathlib import Path from pathlib import Path

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
""" """
Run prediction on images, videos, directories, globs, YouTube, webcam, streams, etc. Run prediction on images, videos, directories, globs, YouTube, webcam, streams, etc.

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
""" """
Ultralytics Results, Boxes and Masks classes for handling inference results. Ultralytics Results, Boxes and Masks classes for handling inference results.

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
""" """
Train a model on a dataset. Train a model on a dataset.

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
""" """
Module provides functionalities for hyperparameter tuning of the Ultralytics YOLO models for object detection, instance Module provides functionalities for hyperparameter tuning of the Ultralytics YOLO models for object detection, instance
segmentation, image classification, pose estimation, and multi-object tracking. segmentation, image classification, pose estimation, and multi-object tracking.

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
""" """
Check a model's accuracy on a test or val split of a dataset. Check a model's accuracy on a test or val split of a dataset.

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import requests import requests

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import requests import requests

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import concurrent.futures import concurrent.futures
import statistics import statistics

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import shutil import shutil
import threading import threading

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import os import os
import platform import platform

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from .fastsam import FastSAM from .fastsam import FastSAM
from .nas import NAS from .nas import NAS

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from .model import FastSAM from .model import FastSAM
from .predict import FastSAMPredictor from .predict import FastSAMPredictor

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from pathlib import Path from pathlib import Path

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import torch import torch
from PIL import Image from PIL import Image

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@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
def adjust_bboxes_to_image_border(boxes, image_shape, threshold=20): def adjust_bboxes_to_image_border(boxes, image_shape, threshold=20):

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from ultralytics.models.yolo.segment import SegmentationValidator from ultralytics.models.yolo.segment import SegmentationValidator
from ultralytics.utils.metrics import SegmentMetrics from ultralytics.utils.metrics import SegmentMetrics

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@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from .model import NAS from .model import NAS
from .predict import NASPredictor from .predict import NASPredictor

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@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
""" """
YOLO-NAS model interface. YOLO-NAS model interface.

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

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

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@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from .model import RTDETR from .model import RTDETR
from .predict import RTDETRPredictor from .predict import RTDETRPredictor

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@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
""" """
Interface for Baidu's RT-DETR, a Vision Transformer-based real-time object detector. RT-DETR offers real-time Interface for Baidu's RT-DETR, a Vision Transformer-based real-time object detector. RT-DETR offers real-time
performance and high accuracy, excelling in accelerated backends like CUDA with TensorRT. It features an efficient performance and high accuracy, excelling in accelerated backends like CUDA with TensorRT. It features an efficient

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

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

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

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@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from .model import SAM from .model import SAM
from .predict import Predictor, SAM2Predictor, SAM2VideoPredictor from .predict import Predictor, SAM2Predictor, SAM2VideoPredictor

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@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import math import math
from itertools import product from itertools import product

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@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
# Copyright (c) Meta Platforms, Inc. and affiliates. # Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved. # All rights reserved.

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@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
""" """
SAM model interface. SAM model interface.

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

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import copy import copy
import math import math

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@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from typing import List, Optional, Tuple, Type from typing import List, Optional, Tuple, Type

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@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from typing import List, Optional, Tuple, Type from typing import List, Optional, Tuple, Type

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@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import copy import copy
from typing import Optional from typing import Optional

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@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
# Copyright (c) Meta Platforms, Inc. and affiliates. # Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved. # All rights reserved.

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@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
# -------------------------------------------------------- # --------------------------------------------------------
# TinyViT Model Architecture # TinyViT Model Architecture

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import math import math
from typing import Tuple, Type from typing import Tuple, Type

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@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from typing import Tuple from typing import Tuple

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@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
""" """
Generate predictions using the Segment Anything Model (SAM). Generate predictions using the Segment Anything Model (SAM).

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

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@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import torch import torch
import torch.nn as nn import torch.nn as nn
@ -243,13 +243,11 @@ class DETRLoss(nn.Module):
if len(gt_bboxes): if len(gt_bboxes):
gt_scores[idx] = bbox_iou(pred_bboxes.detach(), gt_bboxes, xywh=True).squeeze(-1) gt_scores[idx] = bbox_iou(pred_bboxes.detach(), gt_bboxes, xywh=True).squeeze(-1)
loss = { return {
**self._get_loss_class(pred_scores, targets, gt_scores, len(gt_bboxes), postfix), **self._get_loss_class(pred_scores, targets, gt_scores, len(gt_bboxes), postfix),
**self._get_loss_bbox(pred_bboxes, gt_bboxes, postfix), **self._get_loss_bbox(pred_bboxes, gt_bboxes, postfix),
# **(self._get_loss_mask(masks, gt_mask, match_indices, postfix) if masks is not None and gt_mask is not None else {})
} }
# if masks is not None and gt_mask is not None:
# loss.update(self._get_loss_mask(masks, gt_mask, match_indices, postfix))
return loss
def forward(self, pred_bboxes, pred_scores, batch, postfix="", **kwargs): def forward(self, pred_bboxes, pred_scores, batch, postfix="", **kwargs):
""" """

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

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@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from ultralytics.models.yolo import classify, detect, obb, pose, segment, world from ultralytics.models.yolo import classify, detect, obb, pose, segment, world

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from ultralytics.models.yolo.classify.predict import ClassificationPredictor from ultralytics.models.yolo.classify.predict import ClassificationPredictor
from ultralytics.models.yolo.classify.train import ClassificationTrainer from ultralytics.models.yolo.classify.train import ClassificationTrainer

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import cv2 import cv2
import torch import torch

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from copy import copy from copy import copy

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import torch import torch

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from .predict import DetectionPredictor from .predict import DetectionPredictor
from .train import DetectionTrainer from .train import DetectionTrainer

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from ultralytics.engine.predictor import BasePredictor from ultralytics.engine.predictor import BasePredictor
from ultralytics.engine.results import Results from ultralytics.engine.results import Results

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import math import math
import random import random

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import os import os
from pathlib import Path from pathlib import Path

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from pathlib import Path from pathlib import Path

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from .predict import OBBPredictor from .predict import OBBPredictor
from .train import OBBTrainer from .train import OBBTrainer

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import torch import torch

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from copy import copy from copy import copy

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from pathlib import Path from pathlib import Path

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from .predict import PosePredictor from .predict import PosePredictor
from .train import PoseTrainer from .train import PoseTrainer

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from ultralytics.engine.results import Results from ultralytics.engine.results import Results
from ultralytics.models.yolo.detect.predict import DetectionPredictor from ultralytics.models.yolo.detect.predict import DetectionPredictor

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from copy import copy from copy import copy

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from pathlib import Path from pathlib import Path

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from .predict import SegmentationPredictor from .predict import SegmentationPredictor
from .train import SegmentationTrainer from .train import SegmentationTrainer

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from ultralytics.engine.results import Results from ultralytics.engine.results import Results
from ultralytics.models.yolo.detect.predict import DetectionPredictor from ultralytics.models.yolo.detect.predict import DetectionPredictor

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from copy import copy from copy import copy

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# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from multiprocessing.pool import ThreadPool from multiprocessing.pool import ThreadPool
from pathlib import Path from pathlib import Path

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