| | --- |
| | license: apache-2.0 |
| | --- |
| | |
| | # Depth Any Canopy Small |
| |
|
| | <!-- Provide a quick summary of what the model is/does. --> |
| |
|
| | This is the small version of Depth Any Canopy presented in Depth Any Canopy Paper. A [Base version](https://huggingface.co/DarthReca/depth-any-canopy-base) is also available. |
| | a |
| | ## Model Details |
| |
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| | <!-- Provide a longer summary of what this model is. --> |
| |
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| | The model is Depth-Anything-Small finetuned for canopy height estimation on a filtered set of [EarthView](https://huggingface.co/datasets/satellogic/EarthView). |
| |
|
| | - **License:** Apache 2.0 |
| | - **Finetuned from model:** [Depth-Anything-Small](https://huggingface.co/depth-anything/Depth-Anything-V2-Small-hf) |
| |
|
| | ## Uses and Limitations |
| |
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| | <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> |
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| | The model is capable of working with aerial imagery of NEON. The coverage is limited to the US. We cannot guarantee its generalizability over other areas of the globe. |
| | The images cover only RGB channels; no study of hyperspectral imagery was done. |
| |
|
| | ## How to Get Started with the Model |
| |
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| | Use the code below to get started with the model. |
| |
|
| | ```python |
| | # Use a pipeline as a high-level helper |
| | from transformers import pipeline |
| | |
| | pipe = pipeline("depth-estimation", model="DarthReca/depth-any-canopy-base") |
| | |
| | # Load model directly |
| | from transformers import AutoModelForDepthEstimation |
| | |
| | model = AutoModelForDepthEstimation.from_pretrained("DarthReca/depth-any-canopy-base") |
| | ``` |
| |
|
| | ## Environmental Impact |
| |
|
| | <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> |
| |
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| | - **Carbon Emitted:** 0.14 kgCO2 |
| |
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| | Carbon emissions are estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute). |
| |
|
| | ## Citation |
| |
|
| | <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> |
| |
|
| | **BibTeX:** |
| |
|
| | ``` |
| | @inbook{RegeCambrin2025, |
| | title = {Depth Any Canopy: Leveraging Depth Foundation Models for Canopy Height Estimation}, |
| | ISBN = {9783031923876}, |
| | ISSN = {1611-3349}, |
| | url = {http://dx.doi.org/10.1007/978-3-031-92387-6_5}, |
| | DOI = {10.1007/978-3-031-92387-6_5}, |
| | booktitle = {Computer Vision – ECCV 2024 Workshops}, |
| | publisher = {Springer Nature Switzerland}, |
| | author = {Rege Cambrin, Daniele and Corley, Isaac and Garza, Paolo}, |
| | year = {2025}, |
| | pages = {71–86} |
| | } |
| | ``` |
