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It would be great if Model API models had a method similar to the `postprocess`, that would generate a saliency map for models in any domain. Currently, we need to keep that logic on the GETi side. It…
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Hi!
This is a very nice work. And I have a question. Could you please tell me how you drew the saliency maps in the paper? If possible, please provide some details. Thanks!
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I am a novice. Can I ask how to draw the PR curves and F-measure curves in the paper, and do I need to reproduce the method you compare one by one? Or if there's an easier way?
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Self explanatory
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Hi,
Why do we need saliency maps to train the model?
Where can we find the saliency maps for ImageNet dataset?
Thanks
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accelerate launch train_background.py \
--pretrained_model_name_or_path=$MODEL_NAME \
--train_text_encoder \
--instance_data_dir=$INSTANCE_DIR \
--output_dir=$OUTPUT_DIR \
--resolution=512 \
--…
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Dear DeepFRI developers,
There seems to be an error in the saliency maps when the latest release and the downloadable models are used. For example in the case of 2PE5 in the Nat. Comms paper for the…
ga01 updated
7 months ago
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Hi,
Is it possible to upload the predicted saliency maps into Google Drive?
I can't download them.
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May you please provide saliency maps for reference?
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[Saliency maps (or sensitivity masks)](https://pair-code.github.io/saliency/) visualize which inputs contribute towards a model decision. They are generated from gradient-based methods such as [integr…