instruction stringclasses 100
values | code stringlengths 78 193k | response stringlengths 259 170k | file stringlengths 59 203 |
|---|---|---|---|
Generate missing documentation strings | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import ast
import shutil
import subprocess
import sys
from pathlib import Path
from types import SimpleNamespace
from typing import Any
from ultralytics import __version__
from ultralytics.utils import (
ASSETS... | --- +++ @@ -244,6 +244,32 @@
def cfg2dict(cfg: str | Path | dict | SimpleNamespace) -> dict:
+ """Convert a configuration object to a dictionary.
+
+ Args:
+ cfg (str | Path | dict | SimpleNamespace): Configuration object to be converted. Can be a file path, a string, a
+ dictionary, or a Si... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/cfg/__init__.py |
Write reusable docstrings | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
from __future__ import annotations
import torch
import torch.nn.functional as F
from torch import nn
from torch.nn.init import trunc_normal_
from ultralytics.nn.modules imp... | --- +++ @@ -23,6 +23,32 @@
class SAMModel(nn.Module):
+ """Segment Anything Model (SAM) for object segmentation tasks.
+
+ This class combines image encoders, prompt encoders, and mask decoders to predict object masks from images and input
+ prompts.
+
+ Attributes:
+ mask_threshold (float): Thre... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/sam/modules/sam.py |
Write reusable docstrings | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import json
from collections import defaultdict
from itertools import repeat
from multiprocessing.pool import ThreadPool
from pathlib import Path
from typing import Any
import cv2
import numpy as np
import torch
fr... | --- +++ @@ -47,8 +47,39 @@
class YOLODataset(BaseDataset):
+ """Dataset class for loading object detection and/or segmentation labels in YOLO format.
+
+ This class supports loading data for object detection, segmentation, pose estimation, and oriented bounding box
+ (OBB) tasks using the YOLO format.
+
+ ... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/data/dataset.py |
Add inline docstrings for readability | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import copy
import torch
from torch import nn
from .blocks import RoPEAttention
class MemoryAttentionLayer(nn.Module):
def __init__(
self,
d_model: int = 256,
dim_feedforward: int = ... | --- +++ @@ -11,6 +11,45 @@
class MemoryAttentionLayer(nn.Module):
+ """Implements a memory attention layer with self-attention and cross-attention mechanisms for neural networks.
+
+ This class combines self-attention, cross-attention, and feedforward components to process input tensors and
+ generate memo... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/sam/modules/memory_attention.py |
Document all endpoints with docstrings | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import json
import time
from pathlib import Path
import numpy as np
import torch
import torch.distributed as dist
from ultralytics.cfg import get_cfg, get_save_dir
from ultralytics.data.utils import check_cls_data... | --- +++ @@ -1,4 +1,27 @@ # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+"""
+Check a model's accuracy on a test or val split of a dataset.
+
+Usage:
+ $ yolo mode=val model=yolo26n.pt data=coco8.yaml imgsz=640
+
+Usage - formats:
+ $ yolo mode=val model=yolo26n.pt # PyTorch
+... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/engine/validator.py |
Provide docstrings following PEP 257 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from pathlib import Path
from typing import Any
import numpy as np
import torch
from ultralytics.models.yolo.detect import DetectionValidator
from ultralytics.utils import LOGGER, ops
from ultralytics.utils.metric... | --- +++ @@ -16,31 +16,114 @@
class OBBValidator(DetectionValidator):
+ """A class extending the DetectionValidator class for validation based on an Oriented Bounding Box (OBB) model.
+
+ This validator specializes in evaluating models that predict rotated bounding boxes, commonly used for aerial and
+ sate... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/yolo/obb/val.py |
Write docstrings describing functionality | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from ultralytics.models.yolo.segment import SegmentationValidator
class FastSAMValidator(SegmentationValidator):
def __init__(self, dataloader=None, save_dir=None, args=None, _callbacks: dict | None = None):
... | --- +++ @@ -6,8 +6,35 @@
class FastSAMValidator(SegmentationValidator):
+ """Custom validation class for FastSAM (Segment Anything Model) segmentation in the Ultralytics YOLO framework.
+
+ Extends the SegmentationValidator class, customizing the validation process specifically for FastSAM. This class
+ se... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/fastsam/val.py |
Create docstrings for each class method | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
# Based on https://github.com/IDEA-Research/GroundingDINO
from __future__ import annotations
import torch
from torch import nn
from ultralytics.nn.modules.utils import _get_clo... | --- +++ @@ -13,6 +13,15 @@
class TransformerEncoderLayer(nn.Module):
+ """Transformer encoder layer that performs self-attention followed by cross-attention.
+
+ This layer was previously called TransformerDecoderLayer but was renamed to better reflect its role in the
+ architecture. It processes input seq... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/sam/sam3/encoder.py |
Replace inline comments with docstrings | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
from __future__ import annotations
from copy import deepcopy
import torch
from ultralytics.nn.modules.utils import inverse_sigmoid
from ultralytics.utils.ops import xywh2xyxy... | --- +++ @@ -17,6 +17,7 @@
def _update_out(out, out_name, out_value, auxiliary=True, update_aux=True):
+ """Helper function to update output dictionary with main and auxiliary outputs."""
out[out_name] = out_value[-1] if auxiliary else out_value
if auxiliary and update_aux:
if "aux_outputs" not... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/sam/sam3/sam3_image.py |
Generate docstrings with parameter types | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
from __future__ import annotations
import math
import numpy as np
import torch
from torch import Tensor, nn
class DotProductScoring(torch.nn.Module):
def __init__(
... | --- +++ @@ -2,6 +2,7 @@
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
+"""Various utility models."""
from __future__ import annotations
@@ -13,6 +14,7 @@
class DotProductScoring(torch.nn.Module):
+ """A module that computes dot-product scores between query features and pooled ... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/sam/sam3/model_misc.py |
Add inline docstrings for readability | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import itertools
from pathlib import Path
from typing import Any
import torch
from ultralytics.data import build_yolo_dataset
from ultralytics.models.yolo.detect import DetectionTrainer
from ultralytics.nn.tasks i... | --- +++ @@ -16,6 +16,7 @@
def on_pretrain_routine_end(trainer) -> None:
+ """Set up model classes and text encoder at the end of the pretrain routine."""
if RANK in {-1, 0}:
# Set class names for evaluation
names = [name.split("/", 1)[0] for name in list(trainer.test_loader.dataset.data["n... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/yolo/world/train.py |
Document all endpoints with docstrings | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import torch
import torch.nn as nn
import torch.nn.functional as F
from ultralytics.nn.modules import LayerNorm2d
from .blocks import (
Block,
CXBlock,
Fuser,
MaskDownSampler,
MultiScaleBlock,
... | --- +++ @@ -21,6 +21,28 @@
class ImageEncoderViT(nn.Module):
+ """An image encoder using Vision Transformer (ViT) architecture for encoding images into a compact latent space.
+
+ This class processes images by splitting them into patches, applying transformer blocks, and generating a final
+ encoded repre... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/sam/modules/encoders.py |
Generate docstrings for script automation | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import math
from collections.abc import Generator
from itertools import product
from typing import Any
import numpy as np
import torch
def is_box_near_crop_edge(
boxes: torch.Tensor, crop_box: list[int], orig... | --- +++ @@ -14,6 +14,23 @@ def is_box_near_crop_edge(
boxes: torch.Tensor, crop_box: list[int], orig_box: list[int], atol: float = 20.0
) -> torch.Tensor:
+ """Determine if bounding boxes are near the edge of a cropped image region using a specified tolerance.
+
+ Args:
+ boxes (torch.Tensor): Boundi... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/sam/amg.py |
Add docstrings to my Python code | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from pathlib import Path
from typing import Any
import numpy as np
import torch
import torch.nn.functional as F
from ultralytics.models.yolo.detect import DetectionValidator
from ultralytics.utils import LOGGER, o... | --- +++ @@ -16,19 +16,58 @@
class SegmentationValidator(DetectionValidator):
+ """A class extending the DetectionValidator class for validation based on a segmentation model.
+
+ This validator handles the evaluation of segmentation models, processing both bounding box and mask predictions to
+ compute met... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/yolo/segment/val.py |
Improve documentation using docstrings | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
from __future__ import annotations
from copy import deepcopy
import torch
import torch.nn as nn
class Sam3DualViTDetNeck(nn.Module):
def __init__(
self,
... | --- +++ @@ -2,6 +2,7 @@
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
+"""Necks are the interface between a vision backbone and the rest of the detection model."""
from __future__ import annotations
@@ -12,6 +13,7 @@
class Sam3DualViTDetNeck(nn.Module):
+ """A neck that implem... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/sam/sam3/necks.py |
Add docstrings including usage examples | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import math
import random
from copy import deepcopy
from typing import Any
import cv2
import numpy as np
import torch
from PIL import Image
from torch.nn import functional as F
from ultralytics.data.utils import p... | --- +++ @@ -26,46 +26,230 @@
class BaseTransform:
+ """Base class for image transformations in the Ultralytics library.
+
+ This class serves as a foundation for implementing various image processing operations, designed to be compatible
+ with both classification and semantic segmentation tasks.
+
+ Me... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/data/augment.py |
Write docstrings describing each step | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from ultralytics.hub.utils import HUB_API_ROOT, HUB_WEB_ROOT, PREFIX, request_with_credentials
from ultralytics.utils import IS_COLAB, LOGGER, SETTINGS, emojis
API_KEY_URL = f"{HUB_WEB_ROOT}/settings?tab=api+keys"
... | --- +++ @@ -9,10 +9,44 @@
class Auth:
+ """Manages authentication processes including API key handling, cookie-based authentication, and header generation.
+
+ The class supports different methods of authentication:
+ 1. Directly using an API key.
+ 2. Authenticating using browser cookies (specifically ... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/hub/auth.py |
Write clean docstrings for readability | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import asyncio
import hashlib
import json
import random
import shutil
from collections import defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
from pathlib import Path
import cv2
import n... | --- +++ @@ -22,6 +22,12 @@
def coco91_to_coco80_class() -> list[int]:
+ """Convert 91-index COCO class IDs to 80-index COCO class IDs.
+
+ Returns:
+ (list[int | None]): A list of 91 elements where the index represents the 91-index class ID and the value is the
+ corresponding 80-index class... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/data/converter.py |
Generate docstrings with parameter types | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import math
import torch
from torch import Tensor, nn
from ultralytics.nn.modules import MLPBlock
class TwoWayTransformer(nn.Module):
def __init__(
self,
depth: int,
embedding_dim: i... | --- +++ @@ -11,6 +11,31 @@
class TwoWayTransformer(nn.Module):
+ """A Two-Way Transformer module for simultaneous attention to image and query points.
+
+ This class implements a specialized transformer decoder that attends to an input image using queries with supplied
+ positional embeddings. It's useful ... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/sam/modules/transformer.py |
Auto-generate documentation strings for this file | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from copy import copy
from pathlib import Path
from ultralytics.models import yolo
from ultralytics.nn.tasks import OBBModel
from ultralytics.utils import DEFAULT_CFG, RANK
class OBBTrainer(yolo.detect.DetectionT... | --- +++ @@ -11,8 +11,36 @@
class OBBTrainer(yolo.detect.DetectionTrainer):
+ """A class extending the DetectionTrainer class for training based on an Oriented Bounding Box (OBB) model.
+
+ This trainer specializes in training YOLO models that detect oriented bounding boxes, which are useful for detecting
+ ... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/yolo/obb/train.py |
Add docstrings for production code | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import torch
from torch import nn
from ultralytics.nn.modules import MLP, LayerNorm2d
class MaskDecoder(nn.Module):
def __init__(
self,
transformer_dim: int,
transformer: nn.Module,
... | --- +++ @@ -9,6 +9,33 @@
class MaskDecoder(nn.Module):
+ """Decoder module for generating masks and their associated quality scores using a transformer architecture.
+
+ This class predicts masks given image and prompt embeddings, utilizing a transformer to process the inputs and
+ generate mask prediction... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/sam/modules/decoders.py |
Write docstrings for algorithm functions | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import os
import threading
import time
from typing import Any
from ultralytics.utils import (
IS_COLAB,
LOGGER,
TQDM,
TryExcept,
colorstr,
)
HUB_API_ROOT = os.environ.get("ULTRALYTICS_HUB_API", "https://api.ultralytics.com")
HUB_... | --- +++ @@ -21,6 +21,17 @@
def request_with_credentials(url: str) -> Any:
+ """Make an AJAX request with cookies attached in a Google Colab environment.
+
+ Args:
+ url (str): The URL to make the request to.
+
+ Returns:
+ (Any): The response data from the AJAX request.
+
+ Raises:
+ ... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/hub/utils.py |
Add docstrings for better understanding | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from pathlib import Path
from typing import Any
import numpy as np
import torch
from ultralytics.models.yolo.detect import DetectionValidator
from ultralytics.utils import ops
from ultralytics.utils.metrics import... | --- +++ @@ -14,8 +14,56 @@
class PoseValidator(DetectionValidator):
+ """A class extending the DetectionValidator class for validation based on a pose model.
+
+ This validator is specifically designed for pose estimation tasks, handling keypoints and implementing specialized
+ metrics for pose evaluation.... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/yolo/pose/val.py |
Write documentation strings for class attributes | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from pathlib import Path
from typing import Any
from ultralytics.engine.model import Model
from .predict import FastSAMPredictor
from .val import FastSAMValidator
class FastSAM(Model):
def __init__(self, mo... | --- +++ @@ -12,8 +12,31 @@
class FastSAM(Model):
+ """FastSAM model interface for Segment Anything tasks.
+
+ This class extends the base Model class to provide specific functionality for the FastSAM (Fast Segment Anything
+ Model) implementation, allowing for efficient and accurate image segmentation with... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/fastsam/model.py |
Add docstrings explaining edge cases | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import torch
from ultralytics.models.yolo.detect import DetectionValidator
from ultralytics.utils import ops
__all__ = ["NASValidator"]
class NASValidator(DetectionValidator):
def postprocess(self, preds_in):
boxes = ops.xyxy2xywh(pre... | --- +++ @@ -9,8 +9,30 @@
class NASValidator(DetectionValidator):
+ """Ultralytics YOLO NAS Validator for object detection.
+
+ Extends DetectionValidator from the Ultralytics models package and is designed to post-process the raw predictions
+ generated by YOLO NAS models. It performs non-maximum suppressi... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/nas/val.py |
Add docstrings that explain inputs and outputs | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import torch
from ultralytics.models.yolo.detect.predict import DetectionPredictor
from ultralytics.utils import ops
class NASPredictor(DetectionPredictor):
def postprocess(self, preds_in, img, orig_imgs):
boxes = ops.xyxy2xywh(preds_i... | --- +++ @@ -7,8 +7,50 @@
class NASPredictor(DetectionPredictor):
+ """Ultralytics YOLO NAS Predictor for object detection.
+
+ This class extends the DetectionPredictor from Ultralytics engine and is responsible for post-processing the raw
+ predictions generated by the YOLO NAS models. It applies operatio... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/nas/predict.py |
Include argument descriptions in docstrings | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import json
import os
import re
import shutil
import subprocess
import time
from copy import deepcopy
from datetime import datetime
from pathlib import Path
import numpy as np
import torch
from ultralytics import ... | --- +++ @@ -1,4 +1,64 @@ # 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.
+
+Format | `format=argument` | Model
+--- | --- ... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/engine/exporter.py |
Generate consistent documentation across files | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import inspect
from pathlib import Path
from typing import Any
import numpy as np
import torch
from PIL import Image
from ultralytics.cfg import TASK2DATA, get_cfg, get_save_dir
from ultralytics.engine.results imp... | --- +++ @@ -27,6 +27,56 @@
class Model(torch.nn.Module):
+ """A base class for implementing YOLO models, unifying APIs across different model types.
+
+ This class provides a common interface for various operations related to YOLO models, such as training, validation,
+ prediction, exporting, and benchmark... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/engine/model.py |
Add docstrings for better understanding | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import glob
import math
import os
import random
from copy import deepcopy
from multiprocessing.pool import ThreadPool
from pathlib import Path
from typing import Any
import cv2
import numpy as np
from torch.utils.d... | --- +++ @@ -21,6 +21,53 @@
class BaseDataset(Dataset):
+ """Base dataset class for loading and processing image data.
+
+ This class provides core functionality for loading images, caching, and preparing data for training and inference in
+ object detection tasks.
+
+ Attributes:
+ img_path (str ... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/data/base.py |
Expand my code with proper documentation strings | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import torch
from ultralytics.engine.results import Results
from ultralytics.models.yolo.detect.predict import DetectionPredictor
from ultralytics.utils import DEFAULT_CFG, ops
class OBBPredictor(DetectionPredict... | --- +++ @@ -10,13 +10,49 @@
class OBBPredictor(DetectionPredictor):
+ """A class extending the DetectionPredictor class for prediction based on an Oriented Bounding Box (OBB) model.
+
+ This predictor handles oriented bounding box detection tasks, processing images and returning results with rotated
+ boun... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/yolo/obb/predict.py |
Generate consistent documentation across files | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import torch
from ultralytics.data.augment import LetterBox
from ultralytics.engine.predictor import BasePredictor
from ultralytics.engine.results import Results
from ultralytics.utils import ops
class RTDETRPredictor(BasePredictor):
def postp... | --- +++ @@ -9,8 +9,45 @@
class RTDETRPredictor(BasePredictor):
+ """RT-DETR (Real-Time Detection Transformer) Predictor extending the BasePredictor class for making predictions.
+
+ This class leverages Vision Transformers to provide real-time object detection while maintaining high accuracy. It
+ supports... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/rtdetr/predict.py |
Generate documentation strings for clarity | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
from __future__ import annotations
from copy import copy
import torch
import torch.nn as nn
from torch.nn.attention import SDPBackend, sdpa_kernel
from .necks import Sam3Dua... | --- +++ @@ -2,6 +2,7 @@
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
+"""Provides utility to combine a vision backbone with a language backbone."""
from __future__ import annotations
@@ -15,6 +16,11 @@
class SAM3VLBackbone(nn.Module):
+ """This backbone combines a vision back... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/sam/sam3/vl_combiner.py |
Add docstrings following best practices | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import os
from pathlib import Path
from typing import Any
import numpy as np
import torch
import torch.distributed as dist
from ultralytics.data import build_dataloader, build_yolo_dataset, converter
from ultralyt... | --- +++ @@ -19,8 +19,38 @@
class DetectionValidator(BaseValidator):
+ """A class extending the BaseValidator class for validation based on a detection model.
+
+ This class implements validation functionality specific to object detection tasks, including metrics calculation,
+ prediction processing, and vi... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/yolo/detect/val.py |
Add docstrings to incomplete code | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import glob
import math
import os
import time
import urllib
from dataclasses import dataclass
from pathlib import Path
from threading import Thread
from typing import Any
import cv2
import numpy as np
import torch
... | --- +++ @@ -25,6 +25,24 @@
@dataclass
class SourceTypes:
+ """Class to represent various types of input sources for predictions.
+
+ This class uses dataclass to define boolean flags for different types of input sources that can be used for making
+ predictions with YOLO models.
+
+ Attributes:
+ ... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/data/loaders.py |
Create documentation for each function signature | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import concurrent.futures
import statistics
import time
class GCPRegions:
def __init__(self):
self.regions = {
"asia-east1": (1, "Taiwan", "China"),
"asia-east2": (2, "Hong Kon... | --- +++ @@ -8,8 +8,28 @@
class GCPRegions:
+ """A class for managing and analyzing Google Cloud Platform (GCP) regions.
+
+ This class provides functionality to initialize, categorize, and analyze GCP regions based on their geographical
+ location, tier classification, and network latency.
+
+ Attribute... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/hub/google/__init__.py |
Create docstrings for API functions | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
from __future__ import annotations
import numpy as np
import torch
from torch import nn
from torchvision.ops.roi_align import RoIAlign
from ultralytics.nn.modules.transformer ... | --- +++ @@ -1,6 +1,10 @@ # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
+"""
+Transformer decoder.
+Inspired from Pytorch's version, adds the pre-norm variant.
+"""
from __future__ import annotations
@@ -17,6 +21,7 @@ ... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/sam/sam3/decoder.py |
Generate docstrings with examples | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
__version__ = "8.4.23"
import importlib
import os
from typing import TYPE_CHECKING
# Set ENV variables (place before imports)
if not os.environ.get("OMP_NUM_THREADS"):
os.environ["OMP_NUM_THREADS"] = "1" # default for reduced CPU utilization du... | --- +++ @@ -33,14 +33,16 @@
def __getattr__(name: str):
+ """Lazy-import model classes on first access."""
if name in MODELS:
return getattr(importlib.import_module("ultralytics.models"), name)
raise AttributeError(f"module {__name__} has no attribute {name}")
def __dir__():
+ """Exten... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/__init__.py |
Add structured docstrings to improve clarity | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import math
from typing import Any
import torch
import torch.nn.functional as F
def select_closest_cond_frames(frame_idx: int, cond_frame_outputs: dict[int, Any], max_cond_frame_num: int):
if max_cond_frame_n... | --- +++ @@ -10,6 +10,27 @@
def select_closest_cond_frames(frame_idx: int, cond_frame_outputs: dict[int, Any], max_cond_frame_num: int):
+ """Select the closest conditioning frames to a given frame index.
+
+ Args:
+ frame_idx (int): Current frame index.
+ cond_frame_outputs (dict[int, Any]): Dic... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/sam/modules/utils.py |
Write reusable docstrings | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from functools import partial
import torch
from ult... | --- +++ @@ -22,6 +22,7 @@
def _load_checkpoint(model, checkpoint):
+ """Load checkpoint into model from file path."""
if checkpoint is None:
return model
@@ -36,6 +37,7 @@
def build_sam_vit_h(checkpoint=None):
+ """Build and return a Segment Anything Model (SAM) h-size model with specified... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/sam/build.py |
Create docstrings for each class method | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import copy
import math
from functools import partial
import numpy as np
import torch
import torch.nn.functional as F
from torch import Tensor, nn
from ultralytics.nn.modules import MLP, LayerNorm2d, MLPBlock
from... | --- +++ @@ -17,13 +17,29 @@
class DropPath(nn.Module):
+ """Implements stochastic depth regularization for neural networks during training.
+
+ Attributes:
+ drop_prob (float): Probability of dropping a path during training.
+ scale_by_keep (bool): Whether to scale the output by the keep probabi... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/sam/modules/blocks.py |
Add minimal docstrings for each function | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from ultralytics.engine.model import Model
from ultralytics.nn.tasks import RTDETRDetectionModel
from ultralytics.utils.torch_utils import TORCH_1_11
from .predict import RTDETRPredictor
from .train import RTDETRTrainer
from .val import RTDETRValidat... | --- +++ @@ -1,4 +1,13 @@ # 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 performance and high accuracy, excelling in accelerated backends like CUDA with TensorRT.
+It features an ef... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/rtdetr/model.py |
Create docstrings for each class method | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from copy import deepcopy
from functools import lru_cache
from pathlib import Path
from typing import Any
import numpy as np
import torch
from ultralytics.data.augment import LetterBox
from ultralytics.utils impor... | --- +++ @@ -1,4 +1,9 @@ # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+"""
+Ultralytics Results, Boxes, Masks, Keypoints, Probs, and OBB classes for handling inference results.
+
+Usage: See https://docs.ultralytics.com/modes/predict/
+"""
from __future__ import annotations
@@ -16,36 +21,204 ... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/engine/results.py |
Add detailed docstrings explaining each function | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import json
import os
import random
import subprocess
import time
import zipfile
from multiprocessing.pool import ThreadPool
from pathlib import Path
from tarfile import is_tarfile
from typing import Any
import cv2... | --- +++ @@ -58,6 +58,7 @@
def img2label_paths(img_paths: list[str]) -> list[str]:
+ """Convert image paths to label paths by replacing 'images' with 'labels' and extension with '.txt'."""
sa, sb = f"{os.sep}images{os.sep}", f"{os.sep}labels{os.sep}" # /images/, /labels/ substrings
return [sb.join(x.rs... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/data/utils.py |
Document this code for team use | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import ast
import html
import re
import subprocess
import textwrap
from collections import defaultdict
from collections.abc import Iterable
from dataclasses import dataclass, field
from pathlib import Path
from typi... | --- +++ @@ -1,4 +1,12 @@ # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+"""
+Helper file to build Ultralytics Docs reference section.
+
+This script recursively walks through the ultralytics directory and builds a MkDocs reference section of *.md files
+composed of classes and functions, and also ... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/docs/build_reference.py |
Write docstrings for this repository | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import gc
import math
import os
import subprocess
import time
import warnings
from copy import copy, deepcopy
from datetime import datetime, timedelta
from functools import partial
from pathlib import Path
import n... | --- +++ @@ -1,4 +1,10 @@ # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+"""
+Train a model on a dataset.
+
+Usage:
+ $ yolo mode=train model=yolo26n.pt data=coco8.yaml imgsz=640 epochs=100 batch=16
+"""
from __future__ import annotations
@@ -59,8 +65,63 @@
class BaseTrainer:
+ """A ... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/engine/trainer.py |
Write docstrings for utility functions | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
# --------------------------------------------------------
# TinyViT Model Architecture
# Copyright (c) 2022 Microsoft
# Adapted from LeViT and Swin Transformer
# LeViT: (https://github.com/facebookresearch/levit)
# Swin: (https://github.com/micro... | --- +++ @@ -22,6 +22,23 @@
class Conv2d_BN(torch.nn.Sequential):
+ """A sequential container that performs 2D convolution followed by batch normalization.
+
+ This module combines a 2D convolution layer with batch normalization, providing a common building block for
+ convolutional neural networks. The bat... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/sam/modules/tiny_encoder.py |
Add missing documentation to my Python functions | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
import torch.nn as nn
from ultralytics.nn.modules.transformer import MLP
from ultralytics.utils.patches import torch_load
from .modules.blocks import PositionEmbeddingSine, Ro... | --- +++ @@ -24,6 +24,7 @@
def _create_vision_backbone(compile_mode=None, enable_inst_interactivity=True) -> Sam3DualViTDetNeck:
+ """Create SAM3 visual backbone with ViT and neck."""
# Position encoding
position_encoding = PositionEmbeddingSine(
num_pos_feats=256,
@@ -69,6 +70,7 @@
def _cr... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/sam/build_sam3.py |
Add inline docstrings for readability | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import torch
from PIL import Image
from ultralytics.models.yolo.segment import SegmentationPredictor
from ultralytics.utils import DEFAULT_CFG
from ultralytics.utils.metrics import box_iou
from ultralytics.utils.op... | --- +++ @@ -15,12 +15,49 @@
class FastSAMPredictor(SegmentationPredictor):
+ """FastSAMPredictor is specialized for fast SAM (Segment Anything Model) segmentation prediction tasks.
+
+ This class extends the SegmentationPredictor, customizing the prediction pipeline specifically for fast SAM. It
+ adjusts ... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/fastsam/predict.py |
Create docstrings for reusable components | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from pathlib import Path
from ultralytics.data import YOLOConcatDataset, build_grounding, build_yolo_dataset
from ultralytics.data.utils import check_det_dataset
from ultralytics.models.yolo.world import WorldTrain... | --- +++ @@ -13,13 +13,76 @@
class WorldTrainerFromScratch(WorldTrainer):
+ """A class extending the WorldTrainer for training a world model from scratch on open-set datasets.
+
+ This trainer specializes in handling mixed datasets including both object detection and grounding datasets,
+ supporting trainin... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/yolo/world/train_world.py |
Fully document this Python code with docstrings | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from copy import copy
from typing import Any
import torch
from ultralytics.data import ClassificationDataset, build_dataloader
from ultralytics.engine.trainer import BaseTrainer
from ultralytics.models import yolo... | --- +++ @@ -17,8 +17,46 @@
class ClassificationTrainer(BaseTrainer):
+ """A trainer class extending BaseTrainer for training image classification models.
+
+ This trainer handles the training process for image classification tasks, supporting both YOLO classification models
+ and torchvision models with co... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/yolo/classify/train.py |
Add structured docstrings to improve clarity | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
from __future__ import annotations
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.checkpoint as checkpoint
from ultralytics... | --- +++ @@ -15,22 +15,28 @@
class LinearPresenceHead(nn.Sequential):
+ """Linear presence head for predicting the presence of classes in an image."""
def __init__(self, d_model):
+ """Initializes the LinearPresenceHead."""
# a hack to make `LinearPresenceHead` compatible with old checkpoin... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/sam/sam3/maskformer_segmentation.py |
Create docstrings for reusable components | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import random
import shutil
from pathlib import Path
from ultralytics.data.utils import IMG_FORMATS, img2label_paths
from ultralytics.utils import DATASETS_DIR, LOGGER, TQDM
def split_classify_dataset(source_dir:... | --- +++ @@ -11,6 +11,55 @@
def split_classify_dataset(source_dir: str | Path, train_ratio: float = 0.8) -> Path:
+ """Split classification dataset into train and val directories in a new directory.
+
+ Creates a new directory '{source_dir}_split' with train/val subdirectories, preserving the original class st... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/data/split.py |
Write reusable docstrings | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
from __future__ import annotations
import math
from functools import partial
from typing import Callable
import torch
import torch.nn as nn
import torch.nn.functional as F
im... | --- +++ @@ -2,6 +2,15 @@
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
+"""
+ViTDet backbone adapted from Detectron2.
+This module implements Vision Transformer (ViT) backbone for object detection.
+
+Rope embedding code adopted from:
+1. https://github.com/meta-llama/codellama/blob/main/... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/sam/sam3/vitdet.py |
Generate documentation strings for clarity | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import math
import random
from copy import copy
from typing import Any
import numpy as np
import torch
import torch.nn as nn
from ultralytics.data import build_dataloader, build_yolo_dataset
from ultralytics.engin... | --- +++ @@ -22,15 +22,72 @@
class DetectionTrainer(BaseTrainer):
+ """A class extending the BaseTrainer class for training based on a detection model.
+
+ This trainer specializes in object detection tasks, handling the specific requirements for training YOLO models for
+ object detection including dataset... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/yolo/detect/train.py |
Add documentation for all methods | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from copy import copy
from ultralytics.models.yolo.detect import DetectionTrainer
from ultralytics.nn.tasks import RTDETRDetectionModel
from ultralytics.utils import RANK, colorstr
from .val import RTDETRDataset, ... | --- +++ @@ -12,14 +12,62 @@
class RTDETRTrainer(DetectionTrainer):
+ """Trainer class for the RT-DETR model developed by Baidu for real-time object detection.
+
+ This class extends the DetectionTrainer class for YOLO to adapt to the specific features and architecture of
+ RT-DETR. The model leverages Visi... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/rtdetr/train.py |
Write beginner-friendly docstrings | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from ultralytics.engine.results import Results
from ultralytics.models.yolo.detect.predict import DetectionPredictor
from ultralytics.utils import DEFAULT_CFG, ops
class SegmentationPredictor(DetectionPredictor):
... | --- +++ @@ -8,23 +8,94 @@
class SegmentationPredictor(DetectionPredictor):
+ """A class extending the DetectionPredictor class for prediction based on a segmentation model.
+
+ This class specializes in processing segmentation model outputs, handling both bounding boxes and masks in the
+ prediction result... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/yolo/segment/predict.py |
Document all public functions with docstrings | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from ultralytics.engine.predictor import BasePredictor
from ultralytics.engine.results import Results
from ultralytics.utils import nms, ops
class DetectionPredictor(BasePredictor):
def postprocess(self, preds, img, orig_imgs, **kwargs):
... | --- +++ @@ -6,8 +6,50 @@
class DetectionPredictor(BasePredictor):
+ """A class extending the BasePredictor class for prediction based on a detection model.
+
+ This predictor specializes in object detection tasks, processing model outputs into meaningful detection results
+ with bounding boxes and class pr... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/yolo/detect/predict.py |
Add well-formatted docstrings | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from copy import copy
from pathlib import Path
from ultralytics.models import yolo
from ultralytics.nn.tasks import SegmentationModel
from ultralytics.utils import DEFAULT_CFG, RANK
class SegmentationTrainer(yolo... | --- +++ @@ -11,14 +11,50 @@
class SegmentationTrainer(yolo.detect.DetectionTrainer):
+ """A class extending the DetectionTrainer class for training based on a segmentation model.
+
+ This trainer specializes in handling segmentation tasks, extending the detection trainer with segmentation-specific
+ functi... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/yolo/segment/train.py |
Document helper functions with docstrings | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from ultralytics.data.utils import HUBDatasetStats
from ultralytics.hub.auth import Auth
from ultralytics.hub.session import HUBTrainingSession
from ultralytics.hub.utils import HUB_API_ROOT, HUB_WEB_ROOT, PREFIX
fr... | --- +++ @@ -23,6 +23,19 @@
def login(api_key: str | None = None, save: bool = True) -> bool:
+ """Log in to the Ultralytics HUB API using the provided API key.
+
+ The session is not stored; a new session is created when needed using the saved SETTINGS or the HUB_API_KEY
+ environment variable if successfu... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/hub/__init__.py |
Add inline docstrings for readability | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
import torch
import torch.nn as nn
import torchvision
from ultralytics.nn.modules.utils import _get_clones
from ultralytics.utils.ops import xywh2xyxy
def is_right_padded(mas... | --- +++ @@ -11,10 +11,29 @@
def is_right_padded(mask: torch.Tensor):
+ """Given a padding mask (following pytorch convention, 1s for padded values), returns whether the padding is on the
+ right or not.
+ """
return (mask.long() == torch.sort(mask.long(), dim=-1)[0]).all()
def concat_padded_seque... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/sam/sam3/geometry_encoders.py |
Improve my code by adding docstrings | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from copy import copy
from pathlib import Path
from typing import Any
from ultralytics.models import yolo
from ultralytics.nn.tasks import PoseModel
from ultralytics.utils import DEFAULT_CFG
from ultralytics.utils.... | --- +++ @@ -13,8 +13,43 @@
class PoseTrainer(yolo.detect.DetectionTrainer):
+ """A class extending the DetectionTrainer class for training YOLO pose estimation models.
+
+ This trainer specializes in handling pose estimation tasks, managing model training, validation, and visualization
+ of pose keypoints ... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/yolo/pose/train.py |
Generate consistent docstrings | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from typing import Any
import torch
import torch.nn as nn
import torch.nn.functional as F
from scipy.optimize import linear_sum_assignment
from ultralytics.utils.metrics import bbox_iou
from ultralytics.utils.ops ... | --- +++ @@ -14,6 +14,37 @@
class HungarianMatcher(nn.Module):
+ """A module implementing the HungarianMatcher for optimal assignment between predictions and ground truth.
+
+ HungarianMatcher performs optimal bipartite assignment over predicted and ground truth bounding boxes using a cost
+ function that c... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/utils/ops.py |
Help me document legacy Python code | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from pathlib import Path
from typing import Any
import torch
from ultralytics.data.build import load_inference_source
from ultralytics.engine.model import Model
from ultralytics.models import yolo
from ultralytics... | --- +++ @@ -24,8 +24,44 @@
class YOLO(Model):
+ """YOLO (You Only Look Once) object detection model.
+
+ This class provides a unified interface for YOLO models, automatically switching to specialized model types
+ (YOLOWorld or YOLOE) based on the model filename. It supports various computer vision tasks ... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/yolo/model.py |
Document this module using docstrings | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import cv2
import torch
from PIL import Image
from ultralytics.data.augment import classify_transforms
from ultralytics.engine.predictor import BasePredictor
from ultralytics.engine.results import Results
from ultr... | --- +++ @@ -13,12 +13,45 @@
class ClassificationPredictor(BasePredictor):
+ """A class extending the BasePredictor class for prediction based on a classification model.
+
+ This predictor handles the specific requirements of classification models, including preprocessing images and
+ postprocessing predict... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/yolo/classify/predict.py |
Fill in missing docstrings in my code | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import itertools
from glob import glob
from math import ceil
from pathlib import Path
from typing import Any
import cv2
import numpy as np
from PIL import Image
from ultralytics.data.utils import exif_size, img2la... | --- +++ @@ -18,6 +18,20 @@
def bbox_iof(polygon1: np.ndarray, bbox2: np.ndarray, eps: float = 1e-6) -> np.ndarray:
+ """Calculate Intersection over Foreground (IoF) between polygons and bounding boxes.
+
+ Args:
+ polygon1 (np.ndarray): Polygon coordinates with shape (N, 8).
+ bbox2 (np.ndarray)... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/data/split_dota.py |
Generate helpful docstrings for debugging | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from ultralytics.models.yolo.detect.predict import DetectionPredictor
from ultralytics.utils import DEFAULT_CFG, ops
class PosePredictor(DetectionPredictor):
def __init__(self, cfg=DEFAULT_CFG, overrides=None... | --- +++ @@ -7,16 +7,61 @@
class PosePredictor(DetectionPredictor):
+ """A class extending the DetectionPredictor class for prediction based on a pose model.
+
+ This class specializes in pose estimation, handling keypoints detection alongside standard object detection
+ capabilities inherited from Detectio... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/yolo/pose/predict.py |
Add docstrings to improve collaboration | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from pathlib import Path
from typing import Any
import torch
from ultralytics.data import YOLODataset
from ultralytics.data.augment import Compose, Format, v8_transforms
from ultralytics.models.yolo.detect import ... | --- +++ @@ -16,14 +16,69 @@
class RTDETRDataset(YOLODataset):
+ """Real-Time DEtection and TRacking (RT-DETR) dataset class extending the base YOLODataset class.
+
+ This specialized dataset class is designed for use with the RT-DETR object detection model and is optimized for
+ real-time detection and tra... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/rtdetr/val.py |
Add concise docstrings to each method | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import gc
import random
import shutil
import subprocess
import time
from datetime import datetime
import numpy as np
import torch
from ultralytics.cfg import CFG_INT_KEYS, get_cfg, get_save_dir
from ultralytics.ut... | --- +++ @@ -1,4 +1,18 @@ # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+"""
+Module provides functionalities for hyperparameter tuning of the Ultralytics YOLO models for object detection, instance
+segmentation, image classification, pose estimation, and multi-object tracking.
+
+Hyperparameter tu... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/engine/tuner.py |
Write clean docstrings for readability | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
from __future__ import annotations
from collections import OrderedDict
from typing import Callable
import torch
import torch.nn as nn
from torch.utils.checkpoint import checkp... | --- +++ @@ -15,6 +15,7 @@
class ResidualAttentionBlock(nn.Module):
+ """Transformer block with multi-head attention, layer normalization, and MLP feed-forward network."""
def __init__(
self,
@@ -25,6 +26,7 @@ act_layer: Callable[[], nn.Module] = nn.GELU,
norm_layer: Callable[[int... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/sam/sam3/text_encoder_ve.py |
Generate docstrings for exported functions | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from typing import Any
import torch
import torch.nn as nn
import torch.nn.functional as F
from ultralytics.utils.loss import FocalLoss, VarifocalLoss
from ultralytics.utils.metrics import bbox_iou
from .ops impor... | --- +++ @@ -15,6 +15,24 @@
class DETRLoss(nn.Module):
+ """DETR (DEtection TRansformer) Loss class for calculating various loss components.
+
+ This class computes classification loss, bounding box loss, GIoU loss, and optionally auxiliary losses for the DETR
+ object detection model.
+
+ Attributes:
+ ... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/utils/loss.py |
Add minimal docstrings for each function | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from pathlib import Path
from typing import Any
import torch
import torch.distributed as dist
from ultralytics.data import ClassificationDataset, build_dataloader
from ultralytics.engine.validator import BaseValid... | --- +++ @@ -16,8 +16,52 @@
class ClassificationValidator(BaseValidator):
+ """A class extending the BaseValidator class for validation based on a classification model.
+
+ This validator handles the validation process for classification models, including metrics calculation, confusion
+ matrix generation, ... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/yolo/classify/val.py |
Add docstrings for production code | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from pathlib import Path
from typing import Any
import torch
from ultralytics.engine.model import Model
from ultralytics.utils import DEFAULT_CFG_DICT
from ultralytics.utils.downloads import attempt_download_asset... | --- +++ @@ -18,12 +18,41 @@
class NAS(Model):
+ """YOLO-NAS model for object detection.
+
+ This class provides an interface for the YOLO-NAS models and extends the `Model` class from Ultralytics engine. It
+ is designed to facilitate the task of object detection using pre-trained or custom-trained YOLO-NA... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/nas/model.py |
Turn comments into proper docstrings | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import numpy as np
import torch
from ultralytics.data.augment import LoadVisualPrompt
from ultralytics.models.yolo.detect import DetectionPredictor
from ultralytics.models.yolo.segment import SegmentationPredictor
class YOLOEVPDetectPredictor(Detec... | --- +++ @@ -9,15 +9,58 @@
class YOLOEVPDetectPredictor(DetectionPredictor):
+ """A class extending DetectionPredictor for YOLO-EVP (Enhanced Visual Prompting) predictions.
+
+ This class provides common functionality for YOLO models that use visual prompting, including model setup, prompt
+ handling, and p... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/yolo/yoloe/predict.py |
Add detailed docstrings explaining each function | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import torch
import torch.nn as nn
class AGLU(nn.Module):
def __init__(self, device=None, dtype=None) -> None:
super().__init__()
self.act = nn.Softplus(beta=-1.0)
self.lambd = nn.Parameter(nn.init.uniform_(torch.empty(1... | --- +++ @@ -1,17 +1,54 @@ # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+"""Activation modules."""
import torch
import torch.nn as nn
class AGLU(nn.Module):
+ """Unified activation function module from AGLU.
+
+ This class implements a parameterized activation function with learnabl... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/nn/modules/activation.py |
Create documentation for each function signature | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from copy import copy, deepcopy
from pathlib import Path
import torch
from ultralytics.data import YOLOConcatDataset, build_yolo_dataset
from ultralytics.data.augment import LoadVisualPrompt
from ultralytics.model... | --- +++ @@ -19,8 +19,28 @@
class YOLOETrainer(DetectionTrainer):
+ """A trainer class for YOLOE object detection models.
+
+ This class extends DetectionTrainer to provide specialized training functionality for YOLOE models, including custom
+ model initialization, validation, and dataset building with mul... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/yolo/yoloe/train.py |
Add docstrings for utility scripts | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from copy import copy, deepcopy
from ultralytics.models.yolo.segment import SegmentationTrainer
from ultralytics.nn.tasks import YOLOESegModel
from ultralytics.utils import RANK
from .train import YOLOETrainer, YOLOETrainerFromScratch, YOLOEVPTraine... | --- +++ @@ -11,8 +11,28 @@
class YOLOESegTrainer(YOLOETrainer, SegmentationTrainer):
+ """Trainer class for YOLOE segmentation models.
+
+ This class combines YOLOETrainer and SegmentationTrainer to provide training functionality specifically for YOLOE
+ segmentation models, enabling both object detection ... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/yolo/yoloe/train_seg.py |
Improve my code by adding docstrings | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from copy import deepcopy
from pathlib import Path
from typing import Any
import torch
from torch.nn import functional as F
from ultralytics.data import YOLOConcatDataset, build_dataloader, build_yolo_dataset
from... | --- +++ @@ -21,9 +21,47 @@
class YOLOEDetectValidator(DetectionValidator):
+ """A validator class for YOLOE detection models that handles both text and visual prompt embeddings.
+
+ This class extends DetectionValidator to provide specialized validation functionality for YOLOE models. It supports
+ validat... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/models/yolo/yoloe/val.py |
Generate docstrings for this script | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import copy
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.init import constant_, xavier_uniform_
from ultralytics.utils import NOT_MACOS14
from ultralytics.utils.tal ... | --- +++ @@ -1,4 +1,5 @@ # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+"""Model head modules."""
from __future__ import annotations
@@ -23,6 +24,45 @@
class Detect(nn.Module):
+ """YOLO Detect head for object detection models.
+
+ This class implements the detection head used in YOL... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/nn/modules/head.py |
Add docstrings for internal functions | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.init import constant_, xavier_uniform_
from ultralytics.utils.torch_utils import TORCH_1_11
from .conv import Conv
from... | --- +++ @@ -1,4 +1,5 @@ # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+"""Transformer modules."""
from __future__ import annotations
@@ -29,6 +30,23 @@
class TransformerEncoderLayer(nn.Module):
+ """A single layer of the transformer encoder.
+
+ This class implements a standard tran... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/nn/modules/transformer.py |
Auto-generate documentation strings for this file | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from pathlib import Path
from typing import Any
import numpy as np
import torch
import torch.nn as nn
from ultralytics.utils.checks import check_suffix
from ultralytics.utils.downloads import is_url
from .backend... | --- +++ @@ -32,6 +32,17 @@
def check_class_names(names: list | dict) -> dict[int, str]:
+ """Check class names and convert to dict format if needed.
+
+ Args:
+ names (list | dict): Class names as list or dict format.
+
+ Returns:
+ (dict): Class names in dict format with integer keys and str... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/nn/autobackend.py |
Write docstrings for utility functions | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from itertools import cycle
from typing import Any
import cv2
import numpy as np
from ultralytics.solutions.solutions import BaseSolution, SolutionResults # Import a parent class
from ultralytics.utils import plt... | --- +++ @@ -13,9 +13,43 @@
class Analytics(BaseSolution):
+ """A class for creating and updating various types of charts for visual analytics.
+
+ This class extends BaseSolution to provide functionality for generating line, bar, pie, and area charts based on
+ object detection and tracking data.
+
+ At... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/solutions/analytics.py |
Create docstrings for each class method | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import math
from typing import Any
import cv2
from ultralytics.solutions.solutions import BaseSolution, SolutionAnnotator, SolutionResults
from ultralytics.utils.plotting import colors
class DistanceCalculation(BaseSolution):
def __init__(sel... | --- +++ @@ -10,8 +10,30 @@
class DistanceCalculation(BaseSolution):
+ """A class to calculate distance between two objects in a real-time video stream based on their tracks.
+
+ This class extends BaseSolution to provide functionality for selecting objects and calculating the distance between
+ them in a v... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/solutions/distance_calculation.py |
Create docstrings for all classes and functions | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from typing import Any
import cv2
import numpy as np
from ultralytics.solutions.object_counter import ObjectCounter
from ultralytics.solutions.solutions import SolutionAnnotator, SolutionResults
class Heatmap(Ob... | --- +++ @@ -12,8 +12,34 @@
class Heatmap(ObjectCounter):
+ """A class to draw heatmaps in real-time video streams based on object tracks.
+
+ This class extends the ObjectCounter class to generate and visualize heatmaps of object movements in video
+ streams. It uses tracked object positions to create a cu... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/solutions/heatmap.py |
Provide clean and structured docstrings | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import contextlib
import pickle
import re
import types
from copy import deepcopy
from pathlib import Path
import torch
import torch.nn as nn
from ultralytics.nn.autobackend import check_class_names
from ultralytics.nn.modules import (
AIFI,
... | --- +++ @@ -100,18 +100,76 @@
class BaseModel(torch.nn.Module):
+ """Base class for all YOLO models in the Ultralytics family.
+
+ This class provides common functionality for YOLO models including forward pass handling, model fusion, information
+ display, and weight loading capabilities.
+
+ Attribute... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/nn/tasks.py |
Improve documentation using docstrings | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from abc import abstractmethod
from pathlib import Path
import torch
import torch.nn as nn
from PIL import Image
from ultralytics.utils import checks
from ultralytics.utils.torch_utils import smart_inference_mode
... | --- +++ @@ -20,22 +20,65 @@
class TextModel(nn.Module):
+ """Abstract base class for text encoding models.
+
+ This class defines the interface for text encoding models used in vision-language tasks. Subclasses must implement
+ the tokenize and encode_text methods to provide text tokenization and encoding ... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/nn/text_model.py |
Generate docstrings for exported functions | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import torch
from torch import optim
def zeropower_via_newtonschulz5(G: torch.Tensor, eps: float = 1e-7) -> torch.Tensor:
assert len(G.shape) == 2
X = G.bfloat16()
X /= X.norm() + eps # ensure top sin... | --- +++ @@ -7,6 +7,33 @@
def zeropower_via_newtonschulz5(G: torch.Tensor, eps: float = 1e-7) -> torch.Tensor:
+ """Compute the zeroth power / orthogonalization of matrix G using Newton-Schulz iteration.
+
+ This function implements a quintic Newton-Schulz iteration to compute an approximate orthogonalization ... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/optim/muon.py |
Generate docstrings for this script | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from pathlib import Path
import numpy as np
import torch
from PIL import Image
from ultralytics.utils import LOGGER
from ultralytics.utils.checks import check_requirements
from .base import BaseBackend
class Co... | --- +++ @@ -15,8 +15,18 @@
class CoreMLBackend(BaseBackend):
+ """CoreML inference backend for Apple hardware.
+
+ Loads and runs inference with CoreML models (.mlpackage files) using the coremltools library. Supports both static
+ and dynamic input shapes and handles NMS-included model outputs.
+ """
... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/nn/backends/coreml.py |
Write documentation strings for class attributes | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from typing import Any
from ultralytics.engine.results import Results
from ultralytics.solutions.solutions import BaseSolution, SolutionResults
class InstanceSegmentation(BaseSolution):
def __init__(self, **kwargs: Any) -> None:
kwargs... | --- +++ @@ -7,8 +7,40 @@
class InstanceSegmentation(BaseSolution):
+ """A class to manage instance segmentation in images or video streams.
+
+ This class extends the BaseSolution class and provides functionality for performing instance segmentation, including
+ drawing segmented masks with bounding boxes ... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/solutions/instance_segmentation.py |
Document this code for team use | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import copy
import math
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.init import uniform_
__all__ = "inverse_sigmoid", "multi_scale_deformable_attn_pytorch"
def _get_clones(module, n):
ret... | --- +++ @@ -13,14 +13,61 @@
def _get_clones(module, n):
+ """Create a list of cloned modules from the given module.
+
+ Args:
+ module (nn.Module): The module to be cloned.
+ n (int): Number of clones to create.
+
+ Returns:
+ (nn.ModuleList): A ModuleList containing n clones of the in... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/nn/modules/utils.py |
Write Python docstrings for this snippet | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from pathlib import Path
import numpy as np
import torch
from ultralytics.utils import LOGGER
from ultralytics.utils.checks import check_requirements
from .base import BaseBackend
class OpenVINOBackend(BaseBack... | --- +++ @@ -14,8 +14,18 @@
class OpenVINOBackend(BaseBackend):
+ """Intel OpenVINO inference backend for Intel hardware acceleration.
+
+ Loads and runs inference with Intel OpenVINO IR models (*_openvino_model/ directories). Supports automatic device
+ selection, Intel-specific device targeting, and async... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/nn/backends/openvino.py |
Help me document legacy Python code | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from pathlib import Path
import numpy as np
import torch
from ultralytics.utils import ARM64, LOGGER
from ultralytics.utils.checks import check_requirements
from .base import BaseBackend
class PaddleBackend(Bas... | --- +++ @@ -14,8 +14,18 @@
class PaddleBackend(BaseBackend):
+ """Baidu PaddlePaddle inference backend.
+
+ Loads and runs inference with Baidu PaddlePaddle models (*_paddle_model/ directories). Supports both CPU and GPU
+ execution with automatic device configuration and memory pool initialization.
+ "... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/nn/backends/paddle.py |
Generate docstrings for each module | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from collections import defaultdict
from typing import Any
from ultralytics.solutions.solutions import BaseSolution, SolutionAnnotator, SolutionResults
class AIGym(BaseSolution):
def __init__(self, **kwargs: Any) -> None:
kwargs["model... | --- +++ @@ -7,8 +7,36 @@
class AIGym(BaseSolution):
+ """A class to manage gym steps of people in a real-time video stream based on their poses.
+
+ This class extends BaseSolution to monitor workouts using YOLO pose estimation models. It tracks and counts
+ repetitions of exercises based on predefined ang... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/solutions/ai_gym.py |
Generate helpful docstrings for debugging | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from pathlib import Path
import numpy as np
import torch
from ultralytics.utils import LOGGER
from ultralytics.utils.checks import check_requirements
from .base import BaseBackend
class NCNNBackend(BaseBackend)... | --- +++ @@ -14,8 +14,18 @@
class NCNNBackend(BaseBackend):
+ """Tencent NCNN inference backend for mobile and embedded deployment.
+
+ Loads and runs inference with Tencent NCNN models (*_ncnn_model/ directories). Optimized for mobile platforms with
+ optional Vulkan GPU acceleration when available.
+ "... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/nn/backends/ncnn.py |
Write proper docstrings for these functions | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from pathlib import Path
import torch
from ultralytics.utils import LOGGER
from ultralytics.utils.checks import check_executorch_requirements
from .base import BaseBackend
class ExecuTorchBackend(BaseBackend):
... | --- +++ @@ -13,8 +13,18 @@
class ExecuTorchBackend(BaseBackend):
+ """Meta ExecuTorch inference backend for on-device deployment.
+
+ Loads and runs inference with Meta ExecuTorch models (.pte files) using the ExecuTorch runtime. Supports both
+ standalone .pte files and directory-based model packages with... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/nn/backends/executorch.py |
Write proper docstrings for these functions | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from dataclasses import dataclass, field
from typing import Any
import cv2
@dataclass
class SolutionConfig:
source: str | None = None
model: str | None = None
classes: list[int] | None = None
sho... | --- +++ @@ -10,6 +10,57 @@
@dataclass
class SolutionConfig:
+ """Manages configuration parameters for Ultralytics Vision AI solutions.
+
+ The SolutionConfig class serves as a centralized configuration container for all the Ultralytics solution modules:
+ https://docs.ultralytics.com/solutions/#solutions. I... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/solutions/config.py |
Add minimal docstrings for each function | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import os
from pathlib import Path
import torch
from ultralytics.utils import LOGGER
from ultralytics.utils.checks import check_requirements
from .base import BaseBackend
class AxeleraBackend(BaseBackend):
... | --- +++ @@ -14,8 +14,18 @@
class AxeleraBackend(BaseBackend):
+ """Axelera AI inference backend for Axelera Metis AI accelerators.
+
+ Loads compiled Axelera models (.axm files) and runs inference using the Axelera AI runtime SDK. Requires the Axelera
+ runtime environment to be activated before use.
+ ... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/nn/backends/axelera.py |
Create docstrings for each class method | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from pathlib import Path
import numpy as np
import torch
from ultralytics.utils import LOGGER
from ultralytics.utils.checks import check_requirements
from .base import BaseBackend
class ONNXBackend(BaseBackend)... | --- +++ @@ -14,13 +14,32 @@
class ONNXBackend(BaseBackend):
+ """Microsoft ONNX Runtime inference backend with optional OpenCV DNN support.
+
+ Loads and runs inference with ONNX models (.onnx files) using either Microsoft ONNX Runtime with CUDA/CoreML
+ execution providers, or OpenCV DNN for lightweight C... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/nn/backends/onnx.py |
Write docstrings that follow conventions | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import json
import os
from pathlib import Path
import torch
from ultralytics.utils import LOGGER
from ultralytics.utils.checks import check_requirements
from .base import BaseBackend
class MNNBackend(BaseBacken... | --- +++ @@ -15,8 +15,18 @@
class MNNBackend(BaseBackend):
+ """MNN (Mobile Neural Network) inference backend.
+
+ Loads and runs inference with MNN models (.mnn files) using the Alibaba MNN framework. Optimized for mobile and edge
+ deployment with configurable thread count and precision.
+ """
d... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/nn/backends/mnn.py |
Add docstrings for production code | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import ast
from abc import ABC, abstractmethod
import torch
class BaseBackend(ABC):
def __init__(self, weight: str | torch.nn.Module, device: torch.device | str, fp16: bool = False):
self.device = de... | --- +++ @@ -9,8 +9,35 @@
class BaseBackend(ABC):
+ """Base class for all inference backends.
+
+ This abstract class defines the interface that all inference backends must implement. It provides common
+ functionality for model loading, metadata processing, and device management.
+
+ Attributes:
+ ... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/nn/backends/base.py |
Create docstrings for all classes and functions | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import json
from collections import OrderedDict, namedtuple
from pathlib import Path
import numpy as np
import torch
from ultralytics.utils import IS_JETSON, LINUX, LOGGER, PYTHON_VERSION
from ultralytics.utils.ch... | --- +++ @@ -16,8 +16,18 @@
class TensorRTBackend(BaseBackend):
+ """NVIDIA TensorRT inference backend for GPU-accelerated deployment.
+
+ Loads and runs inference with NVIDIA TensorRT serialized engines (.engine files). Supports both TensorRT 7-9 and
+ TensorRT 10+ APIs, dynamic input shapes, FP16 precisio... | https://raw.githubusercontent.com/ultralytics/ultralytics/HEAD/ultralytics/nn/backends/tensorrt.py |
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