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fundus-lesions-segmentation-unet_seresnext50_32x4d
ClementP/fundus-lesions-segmentation-unet_seresnext50_32x4d
fundus-lesions-segmentation-unet_seresnext50_32x4d is a machine learning model from ClementP. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
We focus on the semantic segmentations of:
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At a glance
- Library
- transformers
- License
- mit
- Access
- Public
- Created
- Jun 3, 2024
- Updated
- Jun 4, 2024
- SHA
- a2cfcb59
Model card
From the Hugging Face model README
Lesions Segmentation in Fundus
Introduction
We focus on the semantic segmentations of:
- Cotton Wool Spot
- Exudates
- Hemmorrhages
- Microaneurysms
For an easier use of the models, we refer to cleaned-up version of the code provided in the fundus lesions toolkit.
Architecture
The model uses unet_seresnext50_32x4d as architecture. The implementation is taken from torchSeg
Training datasets
The model was trained on the following datasets: DDR, FGADR, IDRID, MESSIDOR, RETLES
Resolution
The image resolution for training was set to 1024 x 1024.
- Library
- transformers
- License
- mit
- Languages
- en
- Created
- Jun 3, 2024
- Updated
- Jun 4, 2024