Depth Estimation
Transformers
Safetensors
English
chmv2
dinov3
canopy-height
chm
Eval Results (legacy)
Instructions to use WEO-SAS/chm-meta-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WEO-SAS/chm-meta-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("depth-estimation", model="WEO-SAS/chm-meta-v2")# Load model directly from transformers import AutoModelForDepthEstimation model = AutoModelForDepthEstimation.from_pretrained("WEO-SAS/chm-meta-v2", dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 475 Bytes
62e8b24 | 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 27 28 | {
"data_format": "channels_first",
"do_normalize": true,
"do_pad": true,
"do_rescale": true,
"do_resize": false,
"ensure_multiple_of": 16,
"image_mean": [
0.42,
0.411,
0.296
],
"image_processor_type": "CHMv2ImageProcessorFast",
"image_std": [
0.213,
0.156,
0.143
],
"keep_aspect_ratio": true,
"resample": 3,
"rescale_factor": 0.00392156862745098,
"size": {
"height": 384,
"width": 384
},
"size_divisor": 16
}
|