1、Grounding DINO: Marrying DINO withGrounded Pre-TrainingforOpen-Set Object Detection 论文:https://arxiv.org/pdf/2303.05499.pdf 代码:https://github.com/IDEA-Research/GroundingDINO 2、Grounding DINO代码复现 2.1 代码下载
dinov2_vits14 = torch.hub.load('','dinov2_vits14',source='local').cuda() features = torch.zeros(4, patch_h * patch_w, feat_dim) imgs_tensor = torch.zeros(4,3, patch_h *14, patch_w *14).cuda() img_path =f'/kaggle/input/demo-image/1 (4).png'img = Image.open(img_pa...
dinov2代码与预训练模型 (0)踩踩(0) 所需:5积分 lstm模型训练和应用注意事项 2025-03-19 13:30:44 积分:1 CsvOrXlsxToBase64.dll 2025-03-19 12:02:34 积分:1 Speex源码和交叉编译库文件 2025-03-18 21:41:57 积分:1 C++并发编程:`std::async`与`std::thread`的对比与应用 ...
- PyTorch一键加载:直接用hub命令调用预训练模型,3行代码就能跑起来,连分类头都帮你配好了。 **上手三步走**: 1. 先装好PyTorch(记得带CUDA加速); 2. 复制官方加载代码,比如`dinov2_vitb14 = torch.hub.load('facebookresearch/dinov2', 'dinov2_vitb14')`; 3. 需要分类任务?再加一句带`_lc`后缀...