Instructions to use thealper2/depth-anything-v2-base-minecraft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thealper2/depth-anything-v2-base-minecraft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("depth-estimation", model="thealper2/depth-anything-v2-base-minecraft")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForDepthEstimation processor = AutoImageProcessor.from_pretrained("thealper2/depth-anything-v2-base-minecraft") model = AutoModelForDepthEstimation.from_pretrained("thealper2/depth-anything-v2-base-minecraft", device_map="auto") - DepthAnythingV2
How to use thealper2/depth-anything-v2-base-minecraft 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="thealper2/depth-anything-v2-base-minecraft", 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
File size: 413 Bytes
4f06474 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | {
"do_normalize": true,
"do_pad": false,
"do_rescale": true,
"do_resize": true,
"ensure_multiple_of": 14,
"image_mean": [
0.485,
0.456,
0.406
],
"image_processor_type": "DPTImageProcessor",
"image_std": [
0.229,
0.224,
0.225
],
"keep_aspect_ratio": true,
"resample": 3,
"rescale_factor": 0.00392156862745098,
"size": {
"height": 476,
"width": 854
}
}
|