I’m training a pre-trained maisi-rflow model to generate new images conditioned on segmentation masks generated with vista3D.
In MAISI-data is written that the pseudo-labels can be produced using VISTA3D. I’m using MONAI bundle. Both MAISI and VISTA3D have labels IDs from 1 to 132 as can be compared in this two links:
1.https://github.com/Project-MONAI/tutorials/blob/main/generation/maisi/configs/label_dict.json
2. https://github.com/Project-MONAI/VISTA/blob/main/vista3d/data/jsons/label_dict.json
However, when I follow the MAISI inference tutorial and download the provided pseudo-labels, I see the label 200=body which does not exist in VISTA3D. As a result, when I condition maisi-rflow on my masks that only include IDs up to 132, generation quality degrades due to the missing label.
Which model or pipeline should I use to produce complete pseudo-labels compatible with maisi-rflow conditioning? Below are examples of generated images.
I’m training a pre-trained maisi-rflow model to generate new images conditioned on segmentation masks generated with vista3D.
In MAISI-data is written that the pseudo-labels can be produced using VISTA3D. I’m using MONAI bundle. Both MAISI and VISTA3D have labels IDs from 1 to 132 as can be compared in this two links:
1.https://github.com/Project-MONAI/tutorials/blob/main/generation/maisi/configs/label_dict.json
2. https://github.com/Project-MONAI/VISTA/blob/main/vista3d/data/jsons/label_dict.json
However, when I follow the MAISI inference tutorial and download the provided pseudo-labels, I see the label 200=body which does not exist in VISTA3D. As a result, when I condition maisi-rflow on my masks that only include IDs up to 132, generation quality degrades due to the missing label.
Which model or pipeline should I use to produce complete pseudo-labels compatible with maisi-rflow conditioning? Below are examples of generated images.