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Because other approaches like ODISE and Mask2Former evaluate on ADE20k, I was wondering if there was a script or summary of instructions on how to evaluate on cross-dataset on ADE20k-150?
Thanks so much!
The text was updated successfully, but these errors were encountered:
Thanks to the MMSeg toolkit, our model can be easily tested on ADE20K-150 by following these step:
Write 'configs/base/datasets/dataloader/ade.py' based on the '/Path/to/site-packages/mmseg/datasets/ade.py'. The evaluation function needed to be modified for better display.
Write 'configs/open_vocabulary/coco-to-ade.py'. Please refer to the script 'configs/cross_dataset/coco-to-context.py'.
If desired, prepare the text embeddings of ADE20K for faster inference using 'configs/base/datasets/text_embedding/get_embedding.ipynb'.
Ensure that the ADE20K dataset is prepared in MMSeg format.
Run this command for evaluation on ADE20K: python test.py ./configs/cross_dataset/coco-to-ade.py Path/to/coco/vpt_seg_zero_80k_12_100_multi/iter_80000.pth --eval=mIoU
We hope that these steps will be helpful for testing our model on ADE20K-150 using the MMSeg toolkit.
Because other approaches like ODISE and Mask2Former evaluate on ADE20k, I was wondering if there was a script or summary of instructions on how to evaluate on cross-dataset on ADE20k-150?
Thanks so much!
The text was updated successfully, but these errors were encountered: