然后,我安装并测试了Grounded SAM 2【https://github.com/IDEA-Research/Grounded-SAM-2】,这是一个基于Meta流行的Segment Anything Model 2(SAM 2)【https://ai.meta.com/sam2/】的更复杂和更大的VLM。与YOLO-World不同,在YOLO-World中你指定类别名称,而在Grounded SAM 2中你可以用更复杂的文本进行提示。...
SAM2更新了SAM2.1的checkpoint,我们也是第一时间适配上了SAM2.1的checkpoint,在long video的tracking上应该会有更稳定的效果 SAM2支持了Box Prompt,所以可以直接根据Grounding的Box Prompt结果出Mask即可,不需要再通过SAM2的Mask或者是基于Mask的Point Sample作为Prompt Introduction Meta推出的Segment Anything Model 2 (SAM...
Grounded SAM 2: Ground and Track Anything in Videos with Grounding DINO, Florence-2 and SAM 2 - IDEA-Research/Grounded-SAM-2
Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything - ShuoShenDe/Grounded-Sam2-Tracking
Step 2: Prompt Grounding DINO and SAM image predictor to get the box and mask for specific frame """ # prompt grounding dino to get the box coordinates on specific frame img_path = os.path.join(video_dir, frame_names[ann_frame_idx]) image = Image.open(img_path) # run Ground...
Grounded-SAM-2 / grounded_sam2_tracking_demo.py grounded_sam2_tracking_demo.py6.93 KB 一键复制编辑原始数据按行查看历史 bd8090提交于7个月前.feat: add grounded_sam2_tracking_demo_with_continuous_id.py and test data importos importcv2
While SAM 2 has no understanding of what the objects are, you can combine the model with Florence-2, a multimodal model, to generate segmentation masks for regions in an image with text prompts. For example, you could have a dataset of screws and provide the label “screw”. Florence-2 ...
【Grounded SAM 2:结合Grounding DINO和SAM 2的多任务视觉模型,用于图像和视频的开放世界目标检测与跟踪,简化代码实现,增强用户便利性】'Grounded SAM 2: Ground and Track Anything with Grounding DINO and SAM 2' GitHub: github.com/IDEA-Research/Grounded-SAM-2 #图像分割# #视频跟踪# #开放世界模型# ...
在本文中,我们提出了一种多视图草图引导的文本到 3D 生成框架(即 Sketch2NeRF),以将草图控制添加到 3D 生成中。 具体来说,我们的方法利用预训练的 2D 扩散模型(例如,Stable Diffusion 和 ControlNet)来监督由神经辐射场 (NeRF) 表示的 3D 场景的优化。 我们提出了一种新颖的同步生成和重建方法来有效优化 NeRF...
This work presents Sa2VA, the first unified model for dense grounded understanding of both images and videos. Unlike existing multi-modal large language models, which are often limited to specific modalities and tasks, Sa2VA supports a wide range of image and video tasks, including referring seg...