Image-to-3D
SAM 3D Body
3d-human-mesh-recovery
human-mesh-recovery
uncertainty-estimation
3d-morphable-models
mhr
Instructions to use meghshukla/clue with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- SAM 3D Body
How to use meghshukla/clue with SAM 3D Body:
import cv2 import numpy as np from notebook.utils import setup_sam_3d_body from tools.vis_utils import visualize_sample_together estimator = setup_sam_3d_body("meghshukla/clue") img_bgr = cv2.imread("path/to/image.jpg") outputs = estimator.process_one_image(cv2.cvtColor(img_bgr, cv2.COLOR_BGR2RGB)) rend_img = visualize_sample_together(img_bgr, outputs, estimator.faces) cv2.imwrite("output.jpg", rend_img.astype(np.uint8)) - Notebooks
- Google Colab
- Kaggle
Access CLUE
This repository is publicly accessible, but you have to accept the conditions to access its files and content.
CLUE's weights build on Meta's SAM 3D Body and are distributed under the SAM License. They work together with Meta's SAM 3D Body release, which you need to request separately on facebook/sam-3d-body-dinov3.
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