models
dict |
|---|
{
"GelGenie-Universal-Dec-2023": {
"abbrvName": "Universal Model",
"modelName": "GelGenie-Universal-Dec-2023",
"description": "SMPUNet trained with global padding on entire GelGenie training dataset",
"hf_repo_id": "mattaq/GelGenie-Universal-Dec-2023",
"hf_revision": "main",
"torchscript_file": "unet_dec_21_epoch_579.pt",
"onnx_file": "unet_dec_21_epoch_579.onnx"
},
"GelGenie-Universal-FineTune-May-2024": {
"abbrvName": "Sharp Band Model",
"modelName": "GelGenie-Universal-FineTune-May-2024",
"description": "SMPUNet finetuned from universal model to improve performance on sharp bands",
"hf_repo_id": "mattaq/GelGenie-Universal-FineTune-May-2024",
"hf_revision": "main",
"torchscript_file": "unet_dec_21_finetune_epoch_590.pt",
"onnx_file": "unet_dec_21_finetune_epoch_590.onnx"
},
"GelGenie-Universal-Extended-Dec-2023": {
"abbrvName": "Universal Model (Extended)",
"modelName": "GelGenie-Universal-Extended-Dec-2023",
"description": "SMPUNet trained with global padding on entire GelGenie dataset",
"hf_repo_id": "mattaq/GelGenie-Universal-Extended-Dec-2023",
"hf_revision": "main",
"torchscript_file": "unet_dec_21_extended_set_epoch_600.pt",
"onnx_file": "unet_dec_21_extended_set_epoch_600.onnx"
},
"GelGenie-LowRes-Dec-2023": {
"abbrvName": "Low-Res Model",
"modelName": "GelGenie-LowRes-Dec-2023",
"description": "SMPUNet trained with global padding on LSDB training dataset",
"hf_repo_id": "mattaq/GelGenie-LowRes-Dec-2023",
"hf_revision": "main",
"torchscript_file": "unet_dec_21_lsdb_only_epoch_427.pt",
"onnx_file": "unet_dec_21_lsdb_only_epoch_427.onnx"
},
"GelGenie-LowRes-Extended-Dec-2023": {
"abbrvName": "Low-Res Model (Extended)",
"modelName": "GelGenie-LowRes-Extended-Dec-2023",
"description": "SMPUNet trained with global padding on entire LSDB dataset",
"hf_repo_id": "mattaq/GelGenie-LowRes-Extended-Dec-2023",
"hf_revision": "main",
"torchscript_file": "unet_dec_21_lsdb_only_extended_set_epoch_600.pt",
"onnx_file": "unet_dec_21_lsdb_only_extended_set_epoch_600.onnx"
},
"GelGenie-nnUNet-Dec-2023": {
"abbrvName": "nnUNet (slow without GPU)",
"modelName": "GelGenie-nnUNet-Dec-2023",
"description": "nnUNet trained on entire GelGenie training dataset",
"hf_repo_id": "mattaq/GelGenie-nnUNet-Dec-2023",
"hf_revision": "main",
"torchscript_file": "gaussian_tta_packaged_nnunet.pt",
"onnx_file": "None"
},
"GelGenie-nnUNet-Extended-Dec-2023": {
"abbrvName": "nnUNet (Extended - slow without GPU)",
"modelName": "GelGenie-nnUNet-Extended-Dec-2023",
"description": "nnUNet trained on entire GelGenie dataset",
"hf_repo_id": "mattaq/GelGenie-nnUNet-Extended-Dec-2023",
"hf_revision": "main",
"torchscript_file": "gaussian_tta_packaged_nnunet.pt",
"onnx_file": "None"
},
"GelGenie-SMPUNet-GP-4-Nov-2023": {
"abbrvName": "Prototype Model (Universal)",
"modelName": "GelGenie-SMPUNet-GP-4-Nov-2023",
"description": "Prototype SMPUNet trained with global padding",
"hf_repo_id": "mattaq/GelGenie-SMPUNet-GP-4-Nov-2023",
"hf_revision": "main",
"torchscript_file": "unet_global_padding_nov_4_epoch_198.pt",
"onnx_file": "unet_global_padding_nov_4_epoch_198.onnx"
},
"nnUNet-GelGenie-15-Dec-2023": {
"abbrvName": "Prototype nnUNet Model (slow without GPU)",
"modelName": "nnUNet-GelGenie-15-Dec-2023",
"description": "Prototype nnUNet",
"hf_repo_id": "mattaq/nnUNet-GelGenie-15-Dec-2023",
"hf_revision": "main",
"torchscript_file": "gaussian_tta_packaged_nnunet.pt",
"onnx_file": "None"
},
"GelGenie-AttUNet-CW-4-Nov-2023": {
"abbrvName": "Prototype Model (Lightweight)",
"modelName": "GelGenie-AttUNet-CW-4-Nov-2023",
"description": "Prototype Attention UNet (monai) trained with class weighting",
"hf_repo_id": "mattaq/GelGenie-AttUNet-CW-4-Nov-2023",
"hf_revision": "main",
"torchscript_file": "attunet_nov_4_class_weighting_epoch_338.pt",
"onnx_file": "attunet_nov_4_class_weighting_epoch_338.onnx"
},
"GelGenie-SMPUNet-GP-NOLSDB-5-Nov-2023": {
"abbrvName": "Prototype Model (High-Res)",
"modelName": "GelGenie-SMPUNet-GP-NOLSDB-5-Nov-2023",
"description": "Prototype SMPUNet trained with global padding on non-LSDB data",
"hf_repo_id": "mattaq/GelGenie-SMPUNet-GP-NOLSDB-5-Nov-2023",
"hf_revision": "main",
"torchscript_file": "unet_global_padding_nov_5_no_lsdb_epoch_585.pt",
"onnx_file": "unet_global_padding_nov_5_no_lsdb_epoch_585.onnx"
},
"GelGenie-SMPUNet-GP-LSDB-6-Nov-2023": {
"abbrvName": "Prototype Model (Low-Res)",
"modelName": "GelGenie-SMPUNet-GP-LSDB-6-Nov-2023",
"description": "Prototype SMPUNet trained with global padding on LSDB data only",
"hf_repo_id": "mattaq/GelGenie-SMPUNet-GP-LSDB-6-Nov-2023",
"hf_revision": "main",
"torchscript_file": "unet_global_padding_nov_6_lsdb_only_epoch_306.pt",
"onnx_file": "unet_global_padding_nov_6_lsdb_only_epoch_306.onnx"
}
} |
This is the registry of models which can be used both in PyTorch (standalone) or in the GelGenie QuPath Extension.
More details TBC
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