添加状态分类和液面分割
This commit is contained in:
琉璃月光
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---
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description: Discover how to use the FastSAM model with Ultralytics. Learn about its interface and implementation details with practical examples.
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keywords: FastSAM, Ultralytics, model interface, YOLO, deep learning, machine learning, segmentation, predictor, validator, Python
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---
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# Reference for `ultralytics/models/fastsam/model.py`
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!!! Note
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This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/fastsam/model.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/fastsam/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/fastsam/model.py) 🛠️. Thank you 🙏!
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<br>
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## ::: ultralytics.models.fastsam.model.FastSAM
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<br><br>
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---
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description: Explore the Fast SAM Predictor in the Ultralytics YOLO framework. Learn about its segmentation prediction tasks, configuration, and post-processing steps.
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keywords: Ultralytics, Fast SAM Predictor, YOLO, segmentation, prediction, AI model, non-max suppression, mask prediction, tutorial
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---
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# Reference for `ultralytics/models/fastsam/predict.py`
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!!! Note
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This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/fastsam/predict.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/fastsam/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/fastsam/predict.py) 🛠️. Thank you 🙏!
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<br>
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## ::: ultralytics.models.fastsam.predict.FastSAMPredictor
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<br><br>
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---
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description: Explore the utility functions in FastSAM for adjusting bounding boxes and calculating IoU, benefiting computer vision projects.
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keywords: FastSAM, bounding boxes, IoU, Ultralytics, image processing, computer vision
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---
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# Reference for `ultralytics/models/fastsam/utils.py`
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!!! Note
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This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/fastsam/utils.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/fastsam/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/fastsam/utils.py) 🛠️. Thank you 🙏!
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<br>
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## ::: ultralytics.models.fastsam.utils.adjust_bboxes_to_image_border
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<br><br>
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---
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description: Discover FastSAM Validator for segmentation in Ultralytics YOLO. Learn how to validate with custom metrics and avoid common errors. Contribute on GitHub!.
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keywords: FastSAM Validator, Ultralytics, YOLO, segmentation, validation, metrics, GitHub, contribute, documentation
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---
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# Reference for `ultralytics/models/fastsam/val.py`
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!!! Note
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This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/fastsam/val.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/fastsam/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/fastsam/val.py) 🛠️. Thank you 🙏!
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<br>
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## ::: ultralytics.models.fastsam.val.FastSAMValidator
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<br><br>
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---
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description: Explore the YOLO-NAS model interface and learn how to utilize pre-trained YOLO-NAS models for object detection with Ultralytics.
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keywords: Ultralytics, YOLO, YOLO-NAS, object detection, pre-trained models, machine learning, deep learning, NAS model
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---
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# Reference for `ultralytics/models/nas/model.py`
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!!! Note
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This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/nas/model.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/nas/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/nas/model.py) 🛠️. Thank you 🙏!
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<br>
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## ::: ultralytics.models.nas.model.NAS
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<br><br>
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---
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description: Learn about NASPredictor in Ultralytics YOLO for efficient object detection. Explore its attributes, methods, and usage with examples.
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keywords: Ultralytics, YOLO, NASPredictor, object detection, machine learning, AI, non-maximum suppression, bounding boxes, image processing
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---
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# Reference for `ultralytics/models/nas/predict.py`
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!!! Note
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This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/nas/predict.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/nas/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/nas/predict.py) 🛠️. Thank you 🙏!
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<br>
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## ::: ultralytics.models.nas.predict.NASPredictor
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<br><br>
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16
ultralytics_yolov8-main/docs/en/reference/models/nas/val.md
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16
ultralytics_yolov8-main/docs/en/reference/models/nas/val.md
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---
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description: Explore the Ultralytics NASValidator for efficient YOLO model validation. Learn about NMS and post-processing configurations.
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keywords: Ultralytics, YOLO, NASValidator, object detection, non-maximum suppression, NMS, YOLO models, machine learning
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---
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# Reference for `ultralytics/models/nas/val.py`
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!!! Note
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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 🙏!
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<br>
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## ::: ultralytics.models.nas.val.NASValidator
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<br><br>
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---
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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.
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keywords: RT-DETR, real-time object detection, Vision Transformer, Ultralytics, model interface, Baidu, hybrid encoding, IoU-aware query selection, machine learning, AI
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---
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# Reference for `ultralytics/models/rtdetr/model.py`
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!!! Note
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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 🙏!
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<br>
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## ::: ultralytics.models.rtdetr.model.RTDETR
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<br><br>
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---
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description: Access the complete reference for the RTDETRPredictor class in Ultralytics. Learn about its attributes, methods, and example usage for real-time object detection.
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keywords: RTDETRPredictor, Ultralytics, Real-Time Detection Transformer, object detection, Vision Transformers, documentation, RT-DETR, Python class
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---
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# Reference for `ultralytics/models/rtdetr/predict.py`
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!!! Note
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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 🙏!
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<br>
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## ::: ultralytics.models.rtdetr.predict.RTDETRPredictor
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<br><br>
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---
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description: Explore RTDETRTrainer for efficient real-time object detection leveraging Vision Transformers. Learn configuration, dataset handling, and advanced model training.
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keywords: RTDETRTrainer, real-time object detection, Vision Transformers, YOLO, RT-DETR model, model training, dataset handling
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---
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# Reference for `ultralytics/models/rtdetr/train.py`
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!!! Note
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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 🙏!
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<br>
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## ::: ultralytics.models.rtdetr.train.RTDETRTrainer
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<br><br>
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---
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description: Explore the RTDETRValidator and RTDETRDataset classes for real-time detection and tracking. Understand initialization, transformations, and post-processing.
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keywords: RTDETR, Ultralytics, object detection, tracking, YOLO, RTDETRDataset, RTDETRValidator, real-time detection
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---
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# Reference for `ultralytics/models/rtdetr/val.py`
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!!! Note
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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 🙏!
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<br>
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## ::: ultralytics.models.rtdetr.val.RTDETRDataset
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<br><br><hr><br>
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## ::: ultralytics.models.rtdetr.val.RTDETRValidator
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<br><br>
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56
ultralytics_yolov8-main/docs/en/reference/models/sam/amg.md
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56
ultralytics_yolov8-main/docs/en/reference/models/sam/amg.md
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---
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description: Explore the detailed API reference for Ultralytics SAM/AMG models, including functions for mask stability scores, crop box generation, and more.
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keywords: Ultralytics, SAM, AMG, API Reference, models, mask stability, crop boxes, data processing, YOLO
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---
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# Reference for `ultralytics/models/sam/amg.py`
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!!! Note
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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 🙏!
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<br>
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## ::: ultralytics.models.sam.amg.is_box_near_crop_edge
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<br><br><hr><br>
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## ::: ultralytics.models.sam.amg.batch_iterator
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<br><br><hr><br>
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## ::: ultralytics.models.sam.amg.calculate_stability_score
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<br><br><hr><br>
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## ::: ultralytics.models.sam.amg.build_point_grid
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<br><br><hr><br>
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## ::: ultralytics.models.sam.amg.build_all_layer_point_grids
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<br><br><hr><br>
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## ::: ultralytics.models.sam.amg.generate_crop_boxes
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<br><br><hr><br>
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## ::: ultralytics.models.sam.amg.uncrop_boxes_xyxy
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<br><br><hr><br>
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## ::: ultralytics.models.sam.amg.uncrop_points
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<br><br><hr><br>
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## ::: ultralytics.models.sam.amg.uncrop_masks
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<br><br><hr><br>
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## ::: ultralytics.models.sam.amg.remove_small_regions
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<br><br><hr><br>
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## ::: ultralytics.models.sam.amg.batched_mask_to_box
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<br><br>
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---
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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.
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keywords: Ultralytics, SAM model, Segment Anything Model, SAM 2 model, Segment Anything Model 2, SAM ViT, Mobile-SAM, model building, deep learning, AI
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---
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# Reference for `ultralytics/models/sam/build.py`
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!!! Note
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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 🙏!
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<br>
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## ::: ultralytics.models.sam.build.build_sam_vit_h
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<br><br><hr><br>
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## ::: ultralytics.models.sam.build.build_sam_vit_l
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<br><br><hr><br>
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## ::: ultralytics.models.sam.build.build_sam_vit_b
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<br><br><hr><br>
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## ::: ultralytics.models.sam.build.build_mobile_sam
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<br><br><hr><br>
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## ::: ultralytics.models.sam.build.build_sam2_t
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<br><br><hr><br>
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## ::: ultralytics.models.sam.build.build_sam2_s
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<br><br><hr><br>
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## ::: ultralytics.models.sam.build.build_sam2_b
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<br><br><hr><br>
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## ::: ultralytics.models.sam.build.build_sam2_l
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<br><br><hr><br>
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## ::: ultralytics.models.sam.build._build_sam
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<br><br><hr><br>
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## ::: ultralytics.models.sam.build._build_sam2
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<br><br><hr><br>
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## ::: ultralytics.models.sam.build.build_sam
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<br><br>
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---
|
||||
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
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---
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# Reference for `ultralytics/models/sam/model.py`
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|
||||
!!! 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>
|
||||
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||||
## ::: ultralytics.models.sam.model.SAM
|
||||
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<br><br>
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---
|
||||
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
|
||||
---
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||||
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# Reference for `ultralytics/models/sam/modules/blocks.py`
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||||
!!! 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 🙏!
|
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<br>
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## ::: ultralytics.models.sam.modules.blocks.DropPath
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<br><br><hr><br>
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## ::: ultralytics.models.sam.modules.blocks.MaskDownSampler
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<br><br><hr><br>
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## ::: ultralytics.models.sam.modules.blocks.CXBlock
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<br><br><hr><br>
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## ::: ultralytics.models.sam.modules.blocks.Fuser
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<br><br><hr><br>
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## ::: ultralytics.models.sam.modules.blocks.SAM2TwoWayAttentionBlock
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<br><br><hr><br>
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## ::: ultralytics.models.sam.modules.blocks.SAM2TwoWayTransformer
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<br><br><hr><br>
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## ::: ultralytics.models.sam.modules.blocks.RoPEAttention
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<br><br><hr><br>
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## ::: ultralytics.models.sam.modules.blocks.MultiScaleAttention
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<br><br><hr><br>
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## ::: ultralytics.models.sam.modules.blocks.MultiScaleBlock
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<br><br><hr><br>
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## ::: ultralytics.models.sam.modules.blocks.PositionEmbeddingSine
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|
||||
<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>
|
||||
@ -0,0 +1,20 @@
|
||||
---
|
||||
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>
|
||||
@ -0,0 +1,36 @@
|
||||
---
|
||||
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>
|
||||
@ -0,0 +1,20 @@
|
||||
---
|
||||
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>
|
||||
@ -0,0 +1,20 @@
|
||||
---
|
||||
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>
|
||||
@ -0,0 +1,52 @@
|
||||
---
|
||||
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>
|
||||
@ -0,0 +1,24 @@
|
||||
---
|
||||
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>
|
||||
@ -0,0 +1,52 @@
|
||||
---
|
||||
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>
|
||||
@ -0,0 +1,20 @@
|
||||
---
|
||||
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>
|
||||
@ -0,0 +1,20 @@
|
||||
---
|
||||
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>
|
||||
@ -0,0 +1,20 @@
|
||||
---
|
||||
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>
|
||||
@ -0,0 +1,16 @@
|
||||
---
|
||||
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>
|
||||
@ -0,0 +1,16 @@
|
||||
---
|
||||
description: Explore the train.py module in Ultralytics YOLO for efficient classification model training. Learn more with examples and detailed code documentation.
|
||||
keywords: YOLO, Ultralytics, classification, training, machine learning, deep learning, PyTorch, train.py
|
||||
---
|
||||
|
||||
# Reference for `ultralytics/models/yolo/classify/train.py`
|
||||
|
||||
!!! Note
|
||||
|
||||
This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/classify/train.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/classify/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/yolo/classify/train.py) 🛠️. Thank you 🙏!
|
||||
|
||||
<br>
|
||||
|
||||
## ::: ultralytics.models.yolo.classify.train.ClassificationTrainer
|
||||
|
||||
<br><br>
|
||||
@ -0,0 +1,16 @@
|
||||
---
|
||||
description: Explore the source code and functionalities of the YOLO Classification Validator in Ultralytics for evaluating classification models effectively.
|
||||
keywords: Ultralytics, YOLO, classification, validation, ClassifyMetrics, ConfusionMatrix, PyTorch, deep learning, model evaluation, AI, machine learning
|
||||
---
|
||||
|
||||
# Reference for `ultralytics/models/yolo/classify/val.py`
|
||||
|
||||
!!! Note
|
||||
|
||||
This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/classify/val.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/classify/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/yolo/classify/val.py) 🛠️. Thank you 🙏!
|
||||
|
||||
<br>
|
||||
|
||||
## ::: ultralytics.models.yolo.classify.val.ClassificationValidator
|
||||
|
||||
<br><br>
|
||||
@ -0,0 +1,16 @@
|
||||
---
|
||||
description: Explore the Ultralytics YOLO Detection Predictor. Learn how to implement and use the DetectionPredictor class for object detection in Python.
|
||||
keywords: YOLO, Ultralytics, DetectionPredictor, object detection, Python, machine learning, AI, non_max_suppression
|
||||
---
|
||||
|
||||
# Reference for `ultralytics/models/yolo/detect/predict.py`
|
||||
|
||||
!!! Note
|
||||
|
||||
This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/detect/predict.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/detect/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/detect/predict.py) 🛠️. Thank you 🙏!
|
||||
|
||||
<br>
|
||||
|
||||
## ::: ultralytics.models.yolo.detect.predict.DetectionPredictor
|
||||
|
||||
<br><br>
|
||||
@ -0,0 +1,16 @@
|
||||
---
|
||||
description: Learn about the DetectionTrainer class for training YOLO models on custom datasets. Discover methods, examples, and more.
|
||||
keywords: Ultralytics, YOLO, DetectionTrainer, training, object detection, machine learning, build dataset, dataloader, detection model
|
||||
---
|
||||
|
||||
# Reference for `ultralytics/models/yolo/detect/train.py`
|
||||
|
||||
!!! Note
|
||||
|
||||
This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/detect/train.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/detect/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/yolo/detect/train.py) 🛠️. Thank you 🙏!
|
||||
|
||||
<br>
|
||||
|
||||
## ::: ultralytics.models.yolo.detect.train.DetectionTrainer
|
||||
|
||||
<br><br>
|
||||
@ -0,0 +1,16 @@
|
||||
---
|
||||
description: Explore the DetectionValidator class for YOLO models in Ultralytics. Learn validation techniques, metrics, and dataset handling for object detection.
|
||||
keywords: YOLO validation, detection validation, YOLO metrics, Ultralytics, object detection, machine learning, AI
|
||||
---
|
||||
|
||||
# Reference for `ultralytics/models/yolo/detect/val.py`
|
||||
|
||||
!!! Note
|
||||
|
||||
This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/detect/val.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/detect/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/yolo/detect/val.py) 🛠️. Thank you 🙏!
|
||||
|
||||
<br>
|
||||
|
||||
## ::: ultralytics.models.yolo.detect.val.DetectionValidator
|
||||
|
||||
<br><br>
|
||||
@ -0,0 +1,20 @@
|
||||
---
|
||||
description: Explore the ultralytics.models.yolo.model module for YOLO object detection. Learn initialization, model mapping, and more.
|
||||
keywords: YOLO, object detection, Ultralytics, YOLO model, machine learning, Python, model initialization
|
||||
---
|
||||
|
||||
# Reference for `ultralytics/models/yolo/model.py`
|
||||
|
||||
!!! Note
|
||||
|
||||
This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/model.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/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/yolo/model.py) 🛠️. Thank you 🙏!
|
||||
|
||||
<br>
|
||||
|
||||
## ::: ultralytics.models.yolo.model.YOLO
|
||||
|
||||
<br><br><hr><br>
|
||||
|
||||
## ::: ultralytics.models.yolo.model.YOLOWorld
|
||||
|
||||
<br><br>
|
||||
@ -0,0 +1,16 @@
|
||||
---
|
||||
description: Learn how to use the Ultralytics YOLO OBBPredictor for oriented bounding box predictions. Enhance your object detection models with ease.
|
||||
keywords: Ultralytics, YOLO, OBBPredictor, oriented bounding box, object detection, AI, machine learning, PyTorch
|
||||
---
|
||||
|
||||
# Reference for `ultralytics/models/yolo/obb/predict.py`
|
||||
|
||||
!!! Note
|
||||
|
||||
This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/obb/predict.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/obb/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/obb/predict.py) 🛠️. Thank you 🙏!
|
||||
|
||||
<br>
|
||||
|
||||
## ::: ultralytics.models.yolo.obb.predict.OBBPredictor
|
||||
|
||||
<br><br>
|
||||
@ -0,0 +1,16 @@
|
||||
---
|
||||
description: Explore the Ultralytics YOLO OBB Trainer class for efficient training with Oriented Bounding Box models. Learn with examples and method details.
|
||||
keywords: Ultralytics, YOLO, OBB Trainer, Oriented Bounding Box, Machine Learning, Training, AI
|
||||
---
|
||||
|
||||
# Reference for `ultralytics/models/yolo/obb/train.py`
|
||||
|
||||
!!! Note
|
||||
|
||||
This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/obb/train.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/obb/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/yolo/obb/train.py) 🛠️. Thank you 🙏!
|
||||
|
||||
<br>
|
||||
|
||||
## ::: ultralytics.models.yolo.obb.train.OBBTrainer
|
||||
|
||||
<br><br>
|
||||
@ -0,0 +1,16 @@
|
||||
---
|
||||
description: Explore the OBBValidator for YOLO, an advanced class for oriented bounding boxes (OBB). Learn initialization, processes, and evaluation methods.
|
||||
keywords: Ultralytics, YOLO, OBBValidator, Oriented Bounding Boxes, DetectionValidator, validation, Python, deep learning
|
||||
---
|
||||
|
||||
# Reference for `ultralytics/models/yolo/obb/val.py`
|
||||
|
||||
!!! Note
|
||||
|
||||
This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/obb/val.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/obb/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/yolo/obb/val.py) 🛠️. Thank you 🙏!
|
||||
|
||||
<br>
|
||||
|
||||
## ::: ultralytics.models.yolo.obb.val.OBBValidator
|
||||
|
||||
<br><br>
|
||||
@ -0,0 +1,16 @@
|
||||
---
|
||||
description: Learn about the PosePredictor class for YOLO model predictions on pose data. Get setup instructions, example usage, and implementation details.
|
||||
keywords: YOLO, Pose Prediction, Ultralytics, PosePredictor, YOLOv8, Machine Learning, Deep Learning, Python, AI Models
|
||||
---
|
||||
|
||||
# Reference for `ultralytics/models/yolo/pose/predict.py`
|
||||
|
||||
!!! Note
|
||||
|
||||
This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/pose/predict.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/pose/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/pose/predict.py) 🛠️. Thank you 🙏!
|
||||
|
||||
<br>
|
||||
|
||||
## ::: ultralytics.models.yolo.pose.predict.PosePredictor
|
||||
|
||||
<br><br>
|
||||
@ -0,0 +1,16 @@
|
||||
---
|
||||
description: Explore the PoseTrainer class for training pose models using YOLO from Ultralytics. Includes initialization, model configuration, and plotting methods.
|
||||
keywords: PoseTrainer, YOLO, Ultralytics, pose models, training, model configuration, deep learning, machine learning, pose estimation
|
||||
---
|
||||
|
||||
# Reference for `ultralytics/models/yolo/pose/train.py`
|
||||
|
||||
!!! Note
|
||||
|
||||
This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/pose/train.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/pose/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/yolo/pose/train.py) 🛠️. Thank you 🙏!
|
||||
|
||||
<br>
|
||||
|
||||
## ::: ultralytics.models.yolo.pose.train.PoseTrainer
|
||||
|
||||
<br><br>
|
||||
@ -0,0 +1,16 @@
|
||||
---
|
||||
description: Explore the PoseValidator class for YOLO models. Learn how to extend DetectionValidator for pose validation with example code and detailed methods.
|
||||
keywords: Ultralytics, YOLO, PoseValidator, pose validation, machine learning, object detection, keypoints, python code, AI, deep learning
|
||||
---
|
||||
|
||||
# Reference for `ultralytics/models/yolo/pose/val.py`
|
||||
|
||||
!!! Note
|
||||
|
||||
This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/pose/val.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/pose/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/yolo/pose/val.py) 🛠️. Thank you 🙏!
|
||||
|
||||
<br>
|
||||
|
||||
## ::: ultralytics.models.yolo.pose.val.PoseValidator
|
||||
|
||||
<br><br>
|
||||
@ -0,0 +1,16 @@
|
||||
---
|
||||
description: Understand the SegmentationPredictor class for segmentation-based predictions using YOLO. Learn more about its implementation and example usage.
|
||||
keywords: YOLO, SegmentationPredictor, machine learning, computer vision, object detection, Ultralytics, prediction, model, non-max suppression
|
||||
---
|
||||
|
||||
# Reference for `ultralytics/models/yolo/segment/predict.py`
|
||||
|
||||
!!! Note
|
||||
|
||||
This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/segment/predict.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/segment/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/segment/predict.py) 🛠️. Thank you 🙏!
|
||||
|
||||
<br>
|
||||
|
||||
## ::: ultralytics.models.yolo.segment.predict.SegmentationPredictor
|
||||
|
||||
<br><br>
|
||||
@ -0,0 +1,16 @@
|
||||
---
|
||||
description: Learn how to train YOLO models for segmentation tasks with Ultralytics. Explore the SegmentationTrainer class and its functionalities.
|
||||
keywords: YOLO, segmentation, train, Ultralytics, SegmentationTrainer, Python, machine learning, deep learning, tutorials
|
||||
---
|
||||
|
||||
# Reference for `ultralytics/models/yolo/segment/train.py`
|
||||
|
||||
!!! Note
|
||||
|
||||
This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/segment/train.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/segment/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/yolo/segment/train.py) 🛠️. Thank you 🙏!
|
||||
|
||||
<br>
|
||||
|
||||
## ::: ultralytics.models.yolo.segment.train.SegmentationTrainer
|
||||
|
||||
<br><br>
|
||||
@ -0,0 +1,16 @@
|
||||
---
|
||||
description: Explore the YOLO Segmentation Validator module for validating segment models. Understand its usage, metrics, and implementation within the Ultralytics framework.
|
||||
keywords: YOLO, segmentation, validator, Ultralytics, model validation, machine learning, deep learning, AI, computer vision
|
||||
---
|
||||
|
||||
# Reference for `ultralytics/models/yolo/segment/val.py`
|
||||
|
||||
!!! Note
|
||||
|
||||
This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/segment/val.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/segment/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/yolo/segment/val.py) 🛠️. Thank you 🙏!
|
||||
|
||||
<br>
|
||||
|
||||
## ::: ultralytics.models.yolo.segment.val.SegmentationValidator
|
||||
|
||||
<br><br>
|
||||
@ -0,0 +1,20 @@
|
||||
---
|
||||
description: Learn how to train a World Model with Ultralytics YOLO using advanced techniques and customizable options for optimal performance.
|
||||
keywords: Ultralytics, YOLO, World Model, training, deep learning, computer vision, AI, machine learning, tutorial
|
||||
---
|
||||
|
||||
# Reference for `ultralytics/models/yolo/world/train.py`
|
||||
|
||||
!!! Note
|
||||
|
||||
This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/world/train.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/world/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/yolo/world/train.py) 🛠️. Thank you 🙏!
|
||||
|
||||
<br>
|
||||
|
||||
## ::: ultralytics.models.yolo.world.train.WorldTrainer
|
||||
|
||||
<br><br><hr><br>
|
||||
|
||||
## ::: ultralytics.models.yolo.world.train.on_pretrain_routine_end
|
||||
|
||||
<br><br>
|
||||
@ -0,0 +1,16 @@
|
||||
---
|
||||
description: Explore the WorldTrainerFromScratch in YOLO for open-set datasets. Learn how to build, train, and evaluate models efficiently.
|
||||
keywords: YOLO, WorldTrainer, open-set datasets, training, evaluation, build dataset, YOLO World, machine learning
|
||||
---
|
||||
|
||||
# Reference for `ultralytics/models/yolo/world/train_world.py`
|
||||
|
||||
!!! Note
|
||||
|
||||
This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/world/train_world.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/world/train_world.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/world/train_world.py) 🛠️. Thank you 🙏!
|
||||
|
||||
<br>
|
||||
|
||||
## ::: ultralytics.models.yolo.world.train_world.WorldTrainerFromScratch
|
||||
|
||||
<br><br>
|
||||
Reference in New Issue
Block a user