v1.0

docs/en/reference/models/nas/val.md

+---
+description: Explore the Ultralytics NASValidator for efficient YOLO model validation. Learn about NMS and post-processing configurations.
+keywords: Ultralytics, YOLO, NASValidator, object detection, non-maximum suppression, NMS, YOLO models, machine learning
+---
+
+# Reference for `ultralytics/models/nas/val.py`
+
+!!! note
+
+    This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/nas/val.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/nas/val.py). If you spot a problem please help fix it by [contributing](https://docs.ultralytics.com/help/contributing/) a [Pull Request](https://github.com/ultralytics/ultralytics/edit/main/ultralytics/models/nas/val.py) 🛠️. Thank you 🙏!
+
+<br>
+
+## ::: ultralytics.models.nas.val.NASValidator
+
+<br><br>

docs/en/reference/models/rtdetr/model.md

+---
+description: Explore the interface for Baidu's RT-DETR, a Vision Transformer-based real-time object detector in the Ultralytics Docs. Learn more about its efficient hybrid encoding and IoU-aware query selection.
+keywords: RT-DETR, real-time object detection, Vision Transformer, Ultralytics, model interface, Baidu, hybrid encoding, IoU-aware query selection, machine learning, AI
+---
+
+# Reference for `ultralytics/models/rtdetr/model.py`
+
+!!! note
+
+    This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/rtdetr/model.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/rtdetr/model.py). If you spot a problem please help fix it by [contributing](https://docs.ultralytics.com/help/contributing/) a [Pull Request](https://github.com/ultralytics/ultralytics/edit/main/ultralytics/models/rtdetr/model.py) 🛠️. Thank you 🙏!
+
+<br>
+
+## ::: ultralytics.models.rtdetr.model.RTDETR
+
+<br><br>

docs/en/reference/models/rtdetr/predict.md

+---
+description: Access the complete reference for the RTDETRPredictor class in Ultralytics. Learn about its attributes, methods, and example usage for real-time object detection.
+keywords: RTDETRPredictor, Ultralytics, Real-Time Detection Transformer, object detection, Vision Transformers, documentation, RT-DETR, Python class
+---
+
+# Reference for `ultralytics/models/rtdetr/predict.py`
+
+!!! note
+
+    This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/rtdetr/predict.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/rtdetr/predict.py). If you spot a problem please help fix it by [contributing](https://docs.ultralytics.com/help/contributing/) a [Pull Request](https://github.com/ultralytics/ultralytics/edit/main/ultralytics/models/rtdetr/predict.py) 🛠️. Thank you 🙏!
+
+<br>
+
+## ::: ultralytics.models.rtdetr.predict.RTDETRPredictor
+
+<br><br>

docs/en/reference/models/rtdetr/train.md

+---
+description: Explore RTDETRTrainer for efficient real-time object detection leveraging Vision Transformers. Learn configuration, dataset handling, and advanced model training.
+keywords: RTDETRTrainer, real-time object detection, Vision Transformers, YOLO, RT-DETR model, model training, dataset handling
+---
+
+# Reference for `ultralytics/models/rtdetr/train.py`
+
+!!! note
+
+    This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/rtdetr/train.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/rtdetr/train.py). If you spot a problem please help fix it by [contributing](https://docs.ultralytics.com/help/contributing/) a [Pull Request](https://github.com/ultralytics/ultralytics/edit/main/ultralytics/models/rtdetr/train.py) 🛠️. Thank you 🙏!
+
+<br>
+
+## ::: ultralytics.models.rtdetr.train.RTDETRTrainer
+
+<br><br>

docs/en/reference/models/rtdetr/val.md

+---
+description: Explore the RTDETRValidator and RTDETRDataset classes for real-time detection and tracking. Understand initialization, transformations, and post-processing.
+keywords: RTDETR, Ultralytics, object detection, tracking, YOLO, RTDETRDataset, RTDETRValidator, real-time detection
+---
+
+# Reference for `ultralytics/models/rtdetr/val.py`
+
+!!! note
+
+    This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/rtdetr/val.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/rtdetr/val.py). If you spot a problem please help fix it by [contributing](https://docs.ultralytics.com/help/contributing/) a [Pull Request](https://github.com/ultralytics/ultralytics/edit/main/ultralytics/models/rtdetr/val.py) 🛠️. Thank you 🙏!
+
+<br>
+
+## ::: ultralytics.models.rtdetr.val.RTDETRDataset
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.rtdetr.val.RTDETRValidator
+
+<br><br>

docs/en/reference/models/sam/amg.md

+---
+description: Explore the detailed API reference for Ultralytics SAM/AMG models, including functions for mask stability scores, crop box generation, and more.
+keywords: Ultralytics, SAM, AMG, API Reference, models, mask stability, crop boxes, data processing, YOLO
+---
+
+# Reference for `ultralytics/models/sam/amg.py`
+
+!!! note
+
+    This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/sam/amg.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/sam/amg.py). If you spot a problem please help fix it by [contributing](https://docs.ultralytics.com/help/contributing/) a [Pull Request](https://github.com/ultralytics/ultralytics/edit/main/ultralytics/models/sam/amg.py) 🛠️. Thank you 🙏!
+
+<br>
+
+## ::: ultralytics.models.sam.amg.is_box_near_crop_edge
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.amg.batch_iterator
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.amg.calculate_stability_score
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.amg.build_point_grid
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.amg.build_all_layer_point_grids
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.amg.generate_crop_boxes
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.amg.uncrop_boxes_xyxy
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.amg.uncrop_points
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.amg.uncrop_masks
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.amg.remove_small_regions
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.amg.batched_mask_to_box
+
+<br><br>

docs/en/reference/models/sam/build.md

+---
+description: Discover detailed instructions for building various Segment Anything Model (SAM) and Segment Anything Model 2 (SAM 2) architectures with Ultralytics, including SAM ViT and Mobile-SAM.
+keywords: Ultralytics, SAM model, Segment Anything Model, SAM 2 model, Segment Anything Model 2,  SAM ViT, Mobile-SAM, model building, deep learning, AI
+---
+
+# Reference for `ultralytics/models/sam/build.py`
+
+!!! note
+
+    This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/sam/build.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/sam/build.py). If you spot a problem please help fix it by [contributing](https://docs.ultralytics.com/help/contributing/) a [Pull Request](https://github.com/ultralytics/ultralytics/edit/main/ultralytics/models/sam/build.py) 🛠️. Thank you 🙏!
+
+<br>
+
+## ::: ultralytics.models.sam.build.build_sam_vit_h
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.build.build_sam_vit_l
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.build.build_sam_vit_b
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.build.build_mobile_sam
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.build.build_sam2_t
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.build.build_sam2_s
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.build.build_sam2_b
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.build.build_sam2_l
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.build._build_sam
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.build._build_sam2
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.build.build_sam
+
+<br><br>

docs/en/reference/models/sam/model.md

+---
+description: Explore the SAM (Segment Anything Model) and SAM 2 (Segment Anything Model 2) interface for real-time image segmentation. Learn about promptable segmentation and zero-shot capabilities.
+keywords: Ultralytics, SAM, Segment Anything Model, SAM 2, Segment Anything Model 2, image segmentation, real-time segmentation, zero-shot performance, promptable segmentation, SA-1B dataset
+---
+
+# Reference for `ultralytics/models/sam/model.py`
+
+!!! note
+
+    This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/sam/model.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/sam/model.py). If you spot a problem please help fix it by [contributing](https://docs.ultralytics.com/help/contributing/) a [Pull Request](https://github.com/ultralytics/ultralytics/edit/main/ultralytics/models/sam/model.py) 🛠️. Thank you 🙏!
+
+<br>
+
+## ::: ultralytics.models.sam.model.SAM
+
+<br><br>

docs/en/reference/models/sam/modules/blocks.md

+---
+description: Explore detailed documentation of various SAM and SAM 2 modules such as MaskDownSampler, CXBlock, and more, available in Ultralytics' repository.
+keywords: Ultralytics, SAM encoder, SAM 2 encoder, DropPath, MaskDownSampler, CXBlock, Fuser, TwoWayTransformer, TwoWayAttentionBlock, RoPEAttention, MultiScaleAttention, MultiScaleBlock. PositionEmbeddingSine, do_pool
+---
+
+# Reference for `ultralytics/models/sam/modules/blocks.py`
+
+!!! note
+
+    This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/sam/modules/blocks.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/sam/modules/blocks.py). If you spot a problem please help fix it by [contributing](https://docs.ultralytics.com/help/contributing/) a [Pull Request](https://github.com/ultralytics/ultralytics/edit/main/ultralytics/models/sam/modules/blocks.py) 🛠️. Thank you 🙏!
+
+<br>
+
+## ::: ultralytics.models.sam.modules.blocks.DropPath
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.blocks.MaskDownSampler
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.blocks.CXBlock
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.blocks.Fuser
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.blocks.SAM2TwoWayAttentionBlock
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.blocks.SAM2TwoWayTransformer
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.blocks.RoPEAttention
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.blocks.MultiScaleAttention
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.blocks.MultiScaleBlock
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.blocks.PositionEmbeddingSine
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.blocks.PositionEmbeddingRandom
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.blocks.Block
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.blocks.REAttention
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.blocks.PatchEmbed
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.blocks.do_pool
+
+<br><br>

docs/en/reference/models/sam/modules/decoders.md

+---
+description: Explore the MaskDecoder and MLP modules in Ultralytics for efficient mask prediction using transformer architecture. Detailed attributes, functionalities, and implementation.
+keywords: Ultralytics, MaskDecoder, MLP, machine learning, transformer architecture, mask prediction, neural networks, PyTorch modules
+---
+
+# Reference for `ultralytics/models/sam/modules/decoders.py`
+
+!!! note
+
+    This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/sam/modules/decoders.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/sam/modules/decoders.py). If you spot a problem please help fix it by [contributing](https://docs.ultralytics.com/help/contributing/) a [Pull Request](https://github.com/ultralytics/ultralytics/edit/main/ultralytics/models/sam/modules/decoders.py) 🛠️. Thank you 🙏!
+
+<br>
+
+## ::: ultralytics.models.sam.modules.decoders.MaskDecoder
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.decoders.SAM2MaskDecoder
+
+<br><br>

docs/en/reference/models/sam/modules/encoders.md

+---
+description: Explore detailed documentation of various SAM encoder modules such as ImageEncoderViT, PromptEncoder, and more, available in Ultralytics' repository.
+keywords: Ultralytics, SAM encoder, ImageEncoderViT, PromptEncoder, PositionEmbeddingRandom, Block, Attention, PatchEmbed
+---
+
+# Reference for `ultralytics/models/sam/modules/encoders.py`
+
+!!! note
+
+    This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/sam/modules/encoders.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/sam/modules/encoders.py). If you spot a problem please help fix it by [contributing](https://docs.ultralytics.com/help/contributing/) a [Pull Request](https://github.com/ultralytics/ultralytics/edit/main/ultralytics/models/sam/modules/encoders.py) 🛠️. Thank you 🙏!
+
+<br>
+
+## ::: ultralytics.models.sam.modules.encoders.ImageEncoderViT
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.encoders.PromptEncoder
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.encoders.MemoryEncoder
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.encoders.ImageEncoder
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.encoders.FpnNeck
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.encoders.Hiera
+
+<br><br>

docs/en/reference/models/sam/modules/memory_attention.md

+---
+description: Explore detailed documentation of various SAM 2 encoder modules such as MemoryAttentionLayer, MemoryAttention, available in Ultralytics' repository.
+keywords: Ultralytics, SAM 2 encoder, MemoryAttentionLayer, MemoryAttention
+---
+
+# Reference for `ultralytics/models/sam/modules/memory_attention.py`
+
+!!! note
+
+    This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/sam/modules/memory_attention.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/sam/modules/memory_attention.py). If you spot a problem please help fix it by [contributing](https://docs.ultralytics.com/help/contributing/) a [Pull Request](https://github.com/ultralytics/ultralytics/edit/main/ultralytics/models/sam/modules/memory_attention.py) 🛠️. Thank you 🙏!
+
+<br>
+
+## ::: ultralytics.models.sam.modules.memory_attention.MemoryAttentionLayer
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.memory_attention.MemoryAttention
+
+<br><br>

docs/en/reference/models/sam/modules/sam.md

+---
+description: Discover the Ultralytics SAM and SAM 2 module for object segmentation. Learn about its components, such as image encoders and mask decoders, in this comprehensive guide.
+keywords: Ultralytics, SAM Module, SAM 2 Module, object segmentation, image encoder, mask decoder, prompt encoder, AI, machine learning
+---
+
+# Reference for `ultralytics/models/sam/modules/sam.py`
+
+!!! note
+
+    This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/sam/modules/sam.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/sam/modules/sam.py). If you spot a problem please help fix it by [contributing](https://docs.ultralytics.com/help/contributing/) a [Pull Request](https://github.com/ultralytics/ultralytics/edit/main/ultralytics/models/sam/modules/sam.py) 🛠️. Thank you 🙏!
+
+<br>
+
+## ::: ultralytics.models.sam.modules.sam.SAMModel
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.sam.SAM2Model
+
+<br><br>

docs/en/reference/models/sam/modules/tiny_encoder.md

+---
+description: Explore the detailed implementation of TinyViT architecture including Conv2d_BN, PatchEmbed, MBConv, and more in Ultralytics.
+keywords: Ultralytics, TinyViT, Conv2d_BN, PatchEmbed, MBConv, Attention, PyTorch, YOLO, Deep Learning
+---
+
+# Reference for `ultralytics/models/sam/modules/tiny_encoder.py`
+
+!!! note
+
+    This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/sam/modules/tiny_encoder.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/sam/modules/tiny_encoder.py). If you spot a problem please help fix it by [contributing](https://docs.ultralytics.com/help/contributing/) a [Pull Request](https://github.com/ultralytics/ultralytics/edit/main/ultralytics/models/sam/modules/tiny_encoder.py) 🛠️. Thank you 🙏!
+
+<br>
+
+## ::: ultralytics.models.sam.modules.tiny_encoder.Conv2d_BN
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.tiny_encoder.PatchEmbed
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.tiny_encoder.MBConv
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.tiny_encoder.PatchMerging
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.tiny_encoder.ConvLayer
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.tiny_encoder.Mlp
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.tiny_encoder.Attention
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.tiny_encoder.TinyViTBlock
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.tiny_encoder.BasicLayer
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.tiny_encoder.TinyViT
+
+<br><br>

docs/en/reference/models/sam/modules/transformer.md

+---
+description: Explore the TwoWayTransformer module in Ultralytics, designed for simultaneous attention to image and query points. Ideal for object detection and segmentation tasks.
+keywords: Ultralytics, TwoWayTransformer, module, deep learning, transformer, object detection, image segmentation, attention mechanism, neural networks
+---
+
+# Reference for `ultralytics/models/sam/modules/transformer.py`
+
+!!! note
+
+    This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/sam/modules/transformer.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/sam/modules/transformer.py). If you spot a problem please help fix it by [contributing](https://docs.ultralytics.com/help/contributing/) a [Pull Request](https://github.com/ultralytics/ultralytics/edit/main/ultralytics/models/sam/modules/transformer.py) 🛠️. Thank you 🙏!
+
+<br>
+
+## ::: ultralytics.models.sam.modules.transformer.TwoWayTransformer
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.transformer.TwoWayAttentionBlock
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.transformer.Attention
+
+<br><br>

docs/en/reference/models/sam/modules/utils.md

+---
+description: Explore the detailed API reference for Ultralytics SAM and SAM 2 models.
+keywords: Ultralytics, SAM, SAM 2, API Reference, models, window partition, data processing, YOLO
+---
+
+# Reference for `ultralytics/models/sam/modules/utils.py`
+
+!!! note
+
+    This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/sam/modules/utils.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/sam/modules/utils.py). If you spot a problem please help fix it by [contributing](https://docs.ultralytics.com/help/contributing/) a [Pull Request](https://github.com/ultralytics/ultralytics/edit/main/ultralytics/models/sam/modules/utils.py) 🛠️. Thank you 🙏!
+
+<br>
+
+## ::: ultralytics.models.sam.modules.utils.select_closest_cond_frames
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.utils.get_1d_sine_pe
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.utils.init_t_xy
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.utils.compute_axial_cis
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.utils.reshape_for_broadcast
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.utils.apply_rotary_enc
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.utils.window_partition
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.utils.window_unpartition
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.utils.get_rel_pos
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.modules.utils.add_decomposed_rel_pos
+
+<br><br>

docs/en/reference/models/sam/predict.md

+---
+description: Explore Ultralytics SAM and SAM 2 Predictor for advanced, real-time image segmentation using the Segment Anything Model (SAM and SAM 2). Complete implementation details and auxiliary utilities.
+keywords: Ultralytics, SAM, Segment Anything Model, SAM 2, Segment Anything Model 2, image segmentation, real-time, prediction, AI, machine learning, Python, torch, inference
+---
+
+# Reference for `ultralytics/models/sam/predict.py`
+
+!!! note
+
+    This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/sam/predict.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/sam/predict.py). If you spot a problem please help fix it by [contributing](https://docs.ultralytics.com/help/contributing/) a [Pull Request](https://github.com/ultralytics/ultralytics/edit/main/ultralytics/models/sam/predict.py) 🛠️. Thank you 🙏!
+
+<br>
+
+## ::: ultralytics.models.sam.predict.Predictor
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.sam.predict.SAM2Predictor
+
+<br><br>

docs/en/reference/models/utils/loss.md

+---
+description: Explore detailed implementations of loss functions for DETR and RT-DETR models in Ultralytics.
+keywords: ultralytics, YOLO, DETR, RT-DETR, loss functions, object detection, deep learning, focal loss, varifocal loss, Hungarian matcher
+---
+
+# Reference for `ultralytics/models/utils/loss.py`
+
+!!! note
+
+    This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/utils/loss.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/utils/loss.py). If you spot a problem please help fix it by [contributing](https://docs.ultralytics.com/help/contributing/) a [Pull Request](https://github.com/ultralytics/ultralytics/edit/main/ultralytics/models/utils/loss.py) 🛠️. Thank you 🙏!
+
+<br>
+
+## ::: ultralytics.models.utils.loss.DETRLoss
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.utils.loss.RTDETRDetectionLoss
+
+<br><br>

docs/en/reference/models/utils/ops.md

+---
+description: Explore the utilities and operations in Ultralytics models like HungarianMatcher and get_cdn_group. Learn how to optimize and manage model operations efficiently.
+keywords: Ultralytics, models, utils, operations, HungarianMatcher, get_cdn_group, model optimization, pytorch, machine learning
+---
+
+# Reference for `ultralytics/models/utils/ops.py`
+
+!!! note
+
+    This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/utils/ops.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/utils/ops.py). If you spot a problem please help fix it by [contributing](https://docs.ultralytics.com/help/contributing/) a [Pull Request](https://github.com/ultralytics/ultralytics/edit/main/ultralytics/models/utils/ops.py) 🛠️. Thank you 🙏!
+
+<br>
+
+## ::: ultralytics.models.utils.ops.HungarianMatcher
+
+<br><br><hr><br>
+
+## ::: ultralytics.models.utils.ops.get_cdn_group
+
+<br><br>

docs/en/reference/models/yolo/classify/predict.md

+---
+description: Learn about the ClassificationPredictor class for YOLO models at Ultralytics. Get details on initialization, preprocessing, and postprocessing for classification tasks.
+keywords: YOLO, ClassificationPredictor, Ultralytics, model prediction, preprocess, postprocess, deep learning, machine learning
+---
+
+# Reference for `ultralytics/models/yolo/classify/predict.py`
+
+!!! note
+
+    This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/classify/predict.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/classify/predict.py). If you spot a problem please help fix it by [contributing](https://docs.ultralytics.com/help/contributing/) a [Pull Request](https://github.com/ultralytics/ultralytics/edit/main/ultralytics/models/yolo/classify/predict.py) 🛠️. Thank you 🙏!
+
+<br>
+
+## ::: ultralytics.models.yolo.classify.predict.ClassificationPredictor
+
+<br><br>