
# pretrained model

- https://huggingface.co/nvidia/mit-b0
- SegFormer (b0-sized) encoder pre-trained-only
- SegFormer encoder fine-tuned on Imagenet-1k. It was introduced in the paper SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers by Xie et al. and first released in this repository.


# training-set
- you can find the training-set here : https://codalab.lisn.upsaclay.fr/competitions/8769

# training-arguments
- channels : rgb
- batch : 8
- epochs : 8
- learning-rate : 5e-6
- GPU : T4

# results on test-set
- Mean IoU : 59.9 
- more information here : https://codalab.lisn.upsaclay.fr/competitions/8769
{"license": "apache-2.0", "library_name": "transformers", "tags": ["flair-one", "aerial image"], "pipeline_tag": "image-segmentation"}
transformers pytorch segformer flair-one aerial image image-segmentation license:apache-2.0 endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #segformer #flair-one #aerial image #image-segmentation #license-apache-2.0 #endpoints_compatible #has_space #region-us 


# pretrained model

- URL
- SegFormer (b0-sized) encoder pre-trained-only
- SegFormer encoder fine-tuned on Imagenet-1k. It was introduced in the paper SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers by Xie et al. and first released in this repository.


# training-set
- you can find the training-set here : URL

# training-arguments
- channels : rgb
- batch : 8
- epochs : 8
- learning-rate : 5e-6
- GPU : T4

# results on test-set
- Mean IoU : 59.9 
- more information here : URL
# pretrained model

- URL
- SegFormer (b0-sized) encoder pre-trained-only
- SegFormer encoder fine-tuned on Imagenet-1k. It was introduced in the paper SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers by Xie et al. and first released in this repository. # training-set
- you can find the training-set here : URL # training-arguments
- channels : rgb
- batch : 8
- epochs : 8
- learning-rate : 5e-6
- GPU : T4 # results on test-set
- Mean IoU : 59.9 
- more information here : URL
TAGS
#transformers #pytorch #segformer #flair-one #aerial image #image-segmentation #license-apache-2.0 #endpoints_compatible #has_space #region-us 
 # pretrained model

- URL
- SegFormer (b0-sized) encoder pre-trained-only
- SegFormer encoder fine-tuned on Imagenet-1k. It was introduced in the paper SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers by Xie et al. and first released in this repository. # training-set
- you can find the training-set here : URL # training-arguments
- channels : rgb
- batch : 8
- epochs : 8
- learning-rate : 5e-6
- GPU : T4 # results on test-set
- Mean IoU : 59.9 
- more information here : URL
TAGS
#transformers #pytorch #segformer #flair-one #aerial image #image-segmentation #license-apache-2.0 #endpoints_compatible #has_space #region-us 
# pretrained model

- URL
- SegFormer (b0-sized) encoder pre-trained-only
- SegFormer encoder fine-tuned on Imagenet-1k. It was introduced in the paper SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers by Xie et al. and first released in this repository.# training-set
- you can find the training-set here : URL# training-arguments
- channels : rgb
- batch : 8
- epochs : 8
- learning-rate : 5e-6
- GPU : T4# results on test-set
- Mean IoU : 59.9 
- more information here : URL