yolo-world资料(源码+文档)

上传者: m0_37302966 | 上传时间: 2025-10-02 20:24:15 | 文件大小: 2.35MB | 文件类型: ZIP
yolo-world ********************* Highlights & Introduction This repo contains the PyTorch implementation, pre-trained weights, and pre-training/fine-tuning code for YOLO-World. YOLO-World is pre-trained on large-scale datasets, including detection, grounding, and image-text datasets. YOLO-World is the next-generation YOLO detector, with a strong open-vocabulary detection capability and grounding ability. YOLO-World presents a prompt-then-detect paradigm for efficient user-vocabulary inference

文件下载

资源详情

[{"title":"( 161 个子文件 2.35MB ) yolo-world资料(源码+文档)","children":[{"title":"nvdsparsebbox_mmyolo.cpp <span style='color:#111;'> 3.63KB </span>","children":null,"spread":false},{"title":"Dockerfile <span style='color:#111;'> 1.18KB </span>","children":null,"spread":false},{"title":".dockerignore <span style='color:#111;'> 15B </span>","children":null,"spread":false},{"title":".gitattributes <span style='color:#111;'> 696B </span>","children":null,"spread":false},{"title":".gitignore <span style='color:#111;'> 1.37KB </span>","children":null,"spread":false},{"title":".gitmodules <span style='color:#111;'> 108B </span>","children":null,"spread":false},{"title":"inference.ipynb <span style='color:#111;'> 1008.85KB </span>","children":null,"spread":false},{"title":"bus.jpg <span style='color:#111;'> 476.01KB </span>","children":null,"spread":false},{"title":"zidane.jpg <span style='color:#111;'> 164.99KB </span>","children":null,"spread":false},{"title":"lvis_v1_class_texts.json <span style='color:#111;'> 27.51KB </span>","children":null,"spread":false},{"title":"lvis_v1_base_class_captions.json <span style='color:#111;'> 20.13KB </span>","children":null,"spread":false},{"title":"obj365v1_class_texts.json <span style='color:#111;'> 4.92KB </span>","children":null,"spread":false},{"title":"coco_class_texts.json <span style='color:#111;'> 1022B </span>","children":null,"spread":false},{"title":"LICENSE <span style='color:#111;'> 68.65KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 19.41KB </span>","children":null,"spread":false},{"title":"model_convert.md <span style='color:#111;'> 6.28KB </span>","children":null,"spread":false},{"title":"data.md <span style='color:#111;'> 5.16KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 3.70KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 3.63KB </span>","children":null,"spread":false},{"title":"finetuning.md <span style='color:#111;'> 3.51KB </span>","children":null,"spread":false},{"title":"prompt_yolo_world.md <span style='color:#111;'> 3.29KB </span>","children":null,"spread":false},{"title":"reparameterize.md <span style='color:#111;'> 3.01KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 2.97KB </span>","children":null,"spread":false},{"title":"tflite_deploy.md <span style='color:#111;'> 2.42KB </span>","children":null,"spread":false},{"title":"deploy.md <span style='color:#111;'> 2.20KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 2.11KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 1.88KB </span>","children":null,"spread":false},{"title":"README_zh-CN.md <span style='color:#111;'> 1.59KB </span>","children":null,"spread":false},{"title":"installation.md <span style='color:#111;'> 1.39KB </span>","children":null,"spread":false},{"title":"updates.md <span style='color:#111;'> 731B </span>","children":null,"spread":false},{"title":"READEME.md <span style='color:#111;'> 534B </span>","children":null,"spread":false},{"title":"faq.md <span style='color:#111;'> 512B </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 464B </span>","children":null,"spread":false},{"title":"README_zh-CN.md <span style='color:#111;'> 406B </span>","children":null,"spread":false},{"title":"finetune_yoloworld.png <span style='color:#111;'> 466.43KB </span>","children":null,"spread":false},{"title":"yolo_arch.png <span style='color:#111;'> 297.76KB </span>","children":null,"spread":false},{"title":"yolo_logo.png <span style='color:#111;'> 99.93KB </span>","children":null,"spread":false},{"title":"reparameterize.png <span style='color:#111;'> 62.77KB </span>","children":null,"spread":false},{"title":"mm_mix_img_transforms.py <span style='color:#111;'> 46.38KB </span>","children":null,"spread":false},{"title":"yolo_world_head.py <span style='color:#111;'> 29.37KB </span>","children":null,"spread":false},{"title":"yolo_bricks.py <span style='color:#111;'> 24.13KB </span>","children":null,"spread":false},{"title":"yolo_world_seg_head.py <span style='color:#111;'> 24.07KB </span>","children":null,"spread":false},{"title":"numpy_coder.py <span style='color:#111;'> 10.80KB </span>","children":null,"spread":false},{"title":"yolo_world_pafpn.py <span style='color:#111;'> 9.61KB </span>","children":null,"spread":false},{"title":"gradio_demo.py <span style='color:#111;'> 9.20KB </span>","children":null,"spread":false},{"title":"yolo_world_v2_seg_l_vlpan_bn_2e-4_80e_8gpus_seghead_finetune_lvis.py <span style='color:#111;'> 9.08KB </span>","children":null,"spread":false},{"title":"yolo_world_v2_seg_m_vlpan_bn_2e-4_80e_8gpus_seghead_finetune_lvis.py <span style='color:#111;'> 9.08KB </span>","children":null,"spread":false},{"title":"yolo_world_seg_l_dual_vlpan_2e-4_80e_8gpus_seghead_finetune_lvis.py <span style='color:#111;'> 9.06KB </span>","children":null,"spread":false},{"title":"yolo_world_seg_m_dual_vlpan_2e-4_80e_8gpus_seghead_finetune_lvis.py <span style='color:#111;'> 9.06KB </span>","children":null,"spread":false},{"title":"yolo_world.py <span style='color:#111;'> 9.04KB </span>","children":null,"spread":false},{"title":"model.py <span style='color:#111;'> 8.72KB </span>","children":null,"spread":false},{"title":"ort_nms.py <span style='color:#111;'> 8.54KB </span>","children":null,"spread":false},{"title":"yolo_world_seg_l_dual_vlpan_2e-4_80e_8gpus_allmodules_finetune_lvis.py <span style='color:#111;'> 8.51KB </span>","children":null,"spread":false},{"title":"yolow_v5_optim_constructor.py <span style='color:#111;'> 8.45KB </span>","children":null,"spread":false},{"title":"yolo_world_seg_m_dual_vlpan_2e-4_80e_8gpus_allmodules_finetune_lvis.py <span style='color:#111;'> 8.41KB </span>","children":null,"spread":false},{"title":"mm_backbone.py <span style='color:#111;'> 8.24KB </span>","children":null,"spread":false},{"title":"tflite_demo.py <span style='color:#111;'> 8.15KB </span>","children":null,"spread":false},{"title":"trt_nms.py <span style='color:#111;'> 7.86KB </span>","children":null,"spread":false},{"title":"image_demo.py <span style='color:#111;'> 7.64KB </span>","children":null,"spread":false},{"title":"yolo_world_v2_l_vlpan_bn_2e-3_100e_4x8gpus_obj365v1_goldg_train_1280ft_lvis_minival.py <span style='color:#111;'> 7.58KB </span>","children":null,"spread":false},{"title":"onnx_demo.py <span style='color:#111;'> 7.56KB </span>","children":null,"spread":false},{"title":"yolo_world_v2_x_vlpan_bn_2e-3_100e_4x8gpus_obj365v1_goldg_train_1280ft_lvis_minival.py <span style='color:#111;'> 7.50KB </span>","children":null,"spread":false},{"title":"yolo_world_v2_m_vlpan_bn_2e-3_100e_4x8gpus_obj365v1_goldg_train_1280ft_lvis_minival.py <span style='color:#111;'> 7.49KB </span>","children":null,"spread":false},{"title":"yolo_world_v2_l_clip_large_vlpan_bn_2e-3_100e_4x8gpus_obj365v1_goldg_train_800ft_lvis_minival.py <span style='color:#111;'> 7.49KB </span>","children":null,"spread":false},{"title":"yolo_world_v2_s_vlpan_bn_2e-3_100e_4x8gpus_obj365v1_goldg_train_1280ft_lvis_minival.py <span style='color:#111;'> 7.38KB </span>","children":null,"spread":false},{"title":"yolov5_mixed_grounding.py <span style='color:#111;'> 7.26KB </span>","children":null,"spread":false},{"title":"yolo_world_v2_x_vlpan_bn_2e-3_100e_4x8gpus_obj365v1_goldg_cc3mlite_train_lvis_minival.py <span style='color:#111;'> 7.24KB </span>","children":null,"spread":false},{"title":"yolo_world_v2_xl_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco.py <span style='color:#111;'> 7.18KB </span>","children":null,"spread":false},{"title":"export_onnx.py <span style='color:#111;'> 7.13KB </span>","children":null,"spread":false},{"title":"yolo_world_v2_xl_vlpan_bn_2e-3_100e_4x8gpus_obj365v1_goldg_train_lvis_minival.py <span style='color:#111;'> 7.07KB </span>","children":null,"spread":false},{"title":"yolov5_cc3m_grounding.py <span style='color:#111;'> 7.05KB </span>","children":null,"spread":false},{"title":"yolo_world_v2_m_vlpan_bn_noeinsum_2e-3_100e_4x8gpus_obj365v1_goldg_train_lvis_minival.py <span style='color:#111;'> 6.86KB </span>","children":null,"spread":false},{"title":"yolo_world_v2_l_vlpan_bn_2e-4_80e_8gpus_mask-refine_prompt_tuning_coco.py <span style='color:#111;'> 6.82KB </span>","children":null,"spread":false},{"title":"yolo_world_v2_l_vlpan_bn_sgd_1e-3_80e_8gpus_mask-refine_finetune_coco.py <span style='color:#111;'> 6.80KB </span>","children":null,"spread":false},{"title":"yolo_world_l_dual_vlpan_l2norm_2e-3_100e_4x8gpus_obj365v1_goldg_train_lvis_minival.py <span style='color:#111;'> 6.78KB </span>","children":null,"spread":false},{"title":"yolo_world_s_dual_vlpan_l2norm_2e-3_100e_4x8gpus_obj365v1_goldg_train_lvis_minival.py <span style='color:#111;'> 6.78KB </span>","children":null,"spread":false},{"title":"yolo_world_m_dual_vlpan_l2norm_2e-3_100e_4x8gpus_obj365v1_goldg_train_lvis_minival.py <span style='color:#111;'> 6.78KB </span>","children":null,"spread":false},{"title":"yolo_world_x_dual_vlpan_l2norm_2e-3_100e_4x8gpus_obj365v1_goldg_train_lvis_minival.py <span style='color:#111;'> 6.78KB </span>","children":null,"spread":false},{"title":"yolo_world_v2_x_vlpan_bn_2e-3_100e_4x8gpus_obj365v1_goldg_train_lvis_minival.py <span style='color:#111;'> 6.76KB </span>","children":null,"spread":false},{"title":"yolo_world_v2_l_vlpan_bn_2e-3_100e_4x8gpus_obj365v1_goldg_train_lvis_minival.py <span style='color:#111;'> 6.76KB </span>","children":null,"spread":false},{"title":"yolo_world_v2_l_clip_large_vlpan_bn_2e-3_100e_4x8gpus_obj365v1_goldg_train_lvis_minival.py <span style='color:#111;'> 6.76KB </span>","children":null,"spread":false},{"title":"yolo_world_v2_m_vlpan_bn_2e-3_100e_4x8gpus_obj365v1_goldg_train_lvis_minival.py <span style='color:#111;'> 6.74KB </span>","children":null,"spread":false},{"title":"yolo_world_l_dual_vlpan_l2norm_2e-3_100e_4x8gpus_obj365v1_goldg_train_lvis_val.py <span style='color:#111;'> 6.73KB </span>","children":null,"spread":false},{"title":"backendwrapper.py <span style='color:#111;'> 6.72KB </span>","children":null,"spread":false},{"title":"yolo_world_v2_l_vlpan_bn_2e-3_100e_4x8gpus_obj365v1_goldg_train_lvis_val.py <span style='color:#111;'> 6.72KB </span>","children":null,"spread":false},{"title":"yolo_world_v2_s_vlpan_bn_2e-3_100e_4x8gpus_obj365v1_goldg_train_lvis_minival.py <span style='color:#111;'> 6.66KB </span>","children":null,"spread":false},{"title":"yolo_world_v2_l_vlpan_bn_sgd_1e-3_40e_8gpus_finetune_coco.py <span style='color:#111;'> 6.64KB </span>","children":null,"spread":false},{"title":"yolo_world_l_efficient_neck_2e-4_80e_8gpus_mask-refine_finetune_coco.py <span style='color:#111;'> 6.36KB </span>","children":null,"spread":false},{"title":"yolo_world_l_dual_vlpan_2e-4_80e_8gpus_mask-refine_finetune_coco.py <span style='color:#111;'> 6.05KB </span>","children":null,"spread":false},{"title":"yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco.py <span style='color:#111;'> 6.05KB </span>","children":null,"spread":false},{"title":"yolo_world_v2_x_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco.py <span style='color:#111;'> 6.04KB </span>","children":null,"spread":false},{"title":"yolo_world_v2_l_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco.py <span style='color:#111;'> 6.03KB </span>","children":null,"spread":false},{"title":"yolo_world_v2_l_efficient_neck_2e-4_80e_8gpus_mask-refine_finetune_coco.py <span style='color:#111;'> 6.03KB </span>","children":null,"spread":false},{"title":"yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco.py <span style='color:#111;'> 6.02KB </span>","children":null,"spread":false},{"title":"yolo_world_v2_s_rep_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco.py <span style='color:#111;'> 6.00KB </span>","children":null,"spread":false},{"title":"yolo_world_v2_s_bn_2e-4_80e_8gpus_mask-refine_finetune_coco.py <span style='color:#111;'> 5.99KB </span>","children":null,"spread":false},{"title":"yolo_world_l_dual_vlpan_2e-4_80e_8gpus_finetune_coco.py <span style='color:#111;'> 5.89KB </span>","children":null,"spread":false},{"title":"test.py <span style='color:#111;'> 5.32KB </span>","children":null,"spread":false},{"title":"export_onnx.py <span style='color:#111;'> 5.27KB </span>","children":null,"spread":false},{"title":"yolo_world_v2_l_vlpan_bn_2e-4_80e_8gpus_prompt_tuning_coco.py <span style='color:#111;'> 5.11KB </span>","children":null,"spread":false},{"title":"......","children":null,"spread":false},{"title":"<span style='color:steelblue;'>文件过多,未全部展示</span>","children":null,"spread":false}],"spread":true}]

评论信息

免责申明

【只为小站】的资源来自网友分享,仅供学习研究,请务必在下载后24小时内给予删除,不得用于其他任何用途,否则后果自负。基于互联网的特殊性,【只为小站】 无法对用户传输的作品、信息、内容的权属或合法性、合规性、真实性、科学性、完整权、有效性等进行实质审查;无论 【只为小站】 经营者是否已进行审查,用户均应自行承担因其传输的作品、信息、内容而可能或已经产生的侵权或权属纠纷等法律责任。
本站所有资源不代表本站的观点或立场,基于网友分享,根据中国法律《信息网络传播权保护条例》第二十二条之规定,若资源存在侵权或相关问题请联系本站客服人员,zhiweidada#qq.com,请把#换成@,本站将给予最大的支持与配合,做到及时反馈和处理。关于更多版权及免责申明参见 版权及免责申明