Downloads · 30 days
0
GelGenie-LowRes-Extended-Dec-2023
mattaq/GelGenie-LowRes-Extended-Dec-2023
GelGenie-LowRes-Extended-Dec-2023 is a image segmentation model from mattaq. Use it for the image segmentation task on the model card, and read the license before you ship it in a product. It is set up for pytorch. The card lists the license as apache-2.0.
This model consists of an SMP-UNet trained on the LSDB dataset in December 2023 for GelGenie. It should only be used for low-resolution images.
Access
Public
Updated Oct 7, 2024
Repo size
344 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.pth172 MB · 50%
At a glance
- Task
- Image Segmentation
- Library
- pytorch
- License
- apache-2.0
- Access
- Public
- Created
- Dec 24, 2023
- Updated
- Oct 7, 2024
- SHA
- 3a837df9
Model card
From the Hugging Face model README
This model consists of an SMP-UNet trained on the LSDB dataset in December 2023 for GelGenie. It should only be used for low-resolution images.
The model was trained on both the training and validation set for 600 epochs and the final checkpoint extracted (total of 59 images).
Its performance is slightly worse than the other low resolution model available despite the extended dataset it was trained on.
For more details on the configuration used for training, please visit https://huggingface.co/mattaq/GelGenie-LowRes-Extended-Dec-2023 and check the config.toml file. Our codebase is fully open-sourced and is available here: https://github.com/mattaq31/GelGenie.
- Task
- Image Segmentation
- Library
- pytorch
- License
- apache-2.0
- Created
- Dec 24, 2023
- Updated
- Oct 7, 2024