Instructions to use depth-anything/Depth-Anything-V2-Small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- DepthAnythingV2
How to use depth-anything/Depth-Anything-V2-Small 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 depth_anything_v2.dpt import DepthAnythingV2 # instantiate the model model = DepthAnythingV2(encoder="vits", features=64, out_channels=[48, 96, 192, 384]) # load the weights filepath = hf_hub_download(repo_id="depth-anything/Depth-Anything-V2-Small", filename="depth_anything_v2_vits.pth", repo_type="model") state_dict = torch.load(filepath, map_location="cpu") model.load_state_dict(state_dict).eval() raw_img = cv2.imread("your/image/path") depth = model.infer_image(raw_img) # HxW raw depth map in numpy - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -35,7 +35,6 @@ import torch
|
|
| 35 |
|
| 36 |
from depth_anything_v2.dpt import DepthAnythingV2
|
| 37 |
|
| 38 |
-
# take depth-anything-v2-large as an example
|
| 39 |
model = DepthAnythingV2(encoder='vits', features=64, out_channels=[48, 96, 192, 384])
|
| 40 |
model.load_state_dict(torch.load('checkpoints/depth_anything_v2_vits.pth', map_location='cpu'))
|
| 41 |
model.eval()
|
|
|
|
| 35 |
|
| 36 |
from depth_anything_v2.dpt import DepthAnythingV2
|
| 37 |
|
|
|
|
| 38 |
model = DepthAnythingV2(encoder='vits', features=64, out_channels=[48, 96, 192, 384])
|
| 39 |
model.load_state_dict(torch.load('checkpoints/depth_anything_v2_vits.pth', map_location='cpu'))
|
| 40 |
model.eval()
|