Instructions to use Intel/dpt-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Intel/dpt-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("depth-estimation", model="Intel/dpt-large")# Load model directly from transformers import AutoImageProcessor, AutoModelForDepthEstimation processor = AutoImageProcessor.from_pretrained("Intel/dpt-large") model = AutoModelForDepthEstimation.from_pretrained("Intel/dpt-large") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -31,7 +31,7 @@ fine-tuned versions on a task that interests you.
|
|
| 31 |
|
| 32 |
### How to use
|
| 33 |
|
| 34 |
-
Here is how to use this model
|
| 35 |
|
| 36 |
```python
|
| 37 |
from transformers import DPTFeatureExtractor, DPTForDepthEstimation
|
|
|
|
| 31 |
|
| 32 |
### How to use
|
| 33 |
|
| 34 |
+
Here is how to use this model for zero-shot depth estimation on an image:
|
| 35 |
|
| 36 |
```python
|
| 37 |
from transformers import DPTFeatureExtractor, DPTForDepthEstimation
|