joshvm commited on
Commit
47c4af8
·
verified ·
1 Parent(s): 568ebfd

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +5 -5
README.md CHANGED
@@ -12,20 +12,20 @@ widget:
12
  example_title: Urban scene
13
  ---
14
 
15
- # Model Card for restor-tcd-segformer-mit-bx
16
 
17
  This is a semantic segmentation model that can delineate tree cover in aerial images.
18
 
 
 
19
  ## Model Details
20
 
21
  ### Model Description
22
 
23
  This semantic segmentation model was trained on global aerial imagery and is able to accurately delineate tree cover in similar images. The model does not detect individual trees, but provides a per-pixel classification of tree/no-tree.
24
 
25
- This model card refers to several models uploaded to Hugging Face. The model name refers to the specific architecture variant (e.g. nvidia-mit-b0 to nvidia-mit-b5) but the broad details for training and evaluation are identical.
26
-
27
- - **Developed by:** Restor / ETH Zurich
28
- - **Funded by:** This project was made possible via a Google.org impact grant
29
  - **Model type:** Semantic segmentation (binary class)
30
  - **License:** Model training code is provided under an Apache-2 license. NVIDIA has released SegFormer under their own research license. Users should check the terms of this license before deploying.
31
  - **Finetuned from model:** SegFormer family
 
12
  example_title: Urban scene
13
  ---
14
 
15
+ # Model Card for Restor's SegFormer-based TCD models
16
 
17
  This is a semantic segmentation model that can delineate tree cover in aerial images.
18
 
19
+ This model card refers to several models uploaded to Hugging Face. The model name refers to the specific architecture variant (e.g. nvidia-mit-b0 to nvidia-mit-b5) but the broad details for training and evaluation are identical.
20
+
21
  ## Model Details
22
 
23
  ### Model Description
24
 
25
  This semantic segmentation model was trained on global aerial imagery and is able to accurately delineate tree cover in similar images. The model does not detect individual trees, but provides a per-pixel classification of tree/no-tree.
26
 
27
+ - **Developed by:** [Restor](https://restor.eco) / [ETH Zurich](https://ethz.ch)
28
+ - **Funded by:** This project was made possible via a (Google.org impact grant)[https://blog.google/outreach-initiatives/sustainability/restor-helps-anyone-be-part-ecological-restoration/]
 
 
29
  - **Model type:** Semantic segmentation (binary class)
30
  - **License:** Model training code is provided under an Apache-2 license. NVIDIA has released SegFormer under their own research license. Users should check the terms of this license before deploying.
31
  - **Finetuned from model:** SegFormer family