Depth Estimation
PyTorch
DepthAnythingV2
English
monocular-depth
metric-depth
close-range
fine-tuned
intel-realsense
d405
hand-tracking
virtual-keyboard
human-computer-interaction
cvpr2026
Eval Results (legacy)
Instructions to use muxiddin19/vrkeyb-cvpr2026 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- DepthAnythingV2
How to use muxiddin19/vrkeyb-cvpr2026 with DepthAnythingV2:
# Install from https://github.com/DepthAnything/Depth-Anything-V2 # Load the model and infer depth from an image import cv2 import torch from huggingface_hub import hf_hub_download from depth_anything_v2.dpt import DepthAnythingV2 # instantiate the model model = DepthAnythingV2(encoder="<ENCODER>", features=<NUMBER_OF_FEATURES>, out_channels=<OUT_CHANNELS>) # load the weights filepath = hf_hub_download(repo_id="muxiddin19/vrkeyb-cvpr2026", filename="depth_anything_v2_<ENCODER>.pth", repo_type="model") state_dict = torch.load(filepath, map_location="cpu") model.load_state_dict(state_dict) model.eval() raw_img = cv2.imread("your/image/path") depth = model.infer_image(raw_img) # HxW raw depth map in numpy - Notebooks
- Google Colab
- Kaggle
Download depth_anything_v2_vits_d405_finetuned.pth from muxiddin19/vrkeyb-cvpr2026: direct link, hf CLI and curl.
- Browser
- Download file 297 MB
-
https://huggingface.co/muxiddin19/vrkeyb-cvpr2026/resolve/main/depth_anything_v2_vits_d405_finetuned.pth
- Command line
-
hf download hf://muxiddin19/vrkeyb-cvpr2026/depth_anything_v2_vits_d405_finetuned.pth
-
curl -L -o depth_anything_v2_vits_d405_finetuned.pth https://huggingface.co/muxiddin19/vrkeyb-cvpr2026/resolve/main/depth_anything_v2_vits_d405_finetuned.pth
297 MB
- Xet hash:
- 2481912fd3aaa9caa83a13968b6937fd0467e7c4ee66a9af0bd64f6593fe7179
- Size of remote file:
- 297 MB
- SHA256:
- 5215f4cebf4857248d99d7a7bf54e370db8c64a8434db2e4500dba2c91ae6180
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