Issues related to FID calculation and BEVfusion about magicdrive HOT 7 CLOSED

You can add +runner.validation_index=all to generate the full validation set.

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Hello, I have improved the test config according to your method, but I found that although I can infer the entire test set, the generated images still do not meet the standards of Nuscenes. In Nuscenes' samples, the images exist as a single view, but the generated images are concatenated with 6 views. At the same time, the file names used for indexing the generated images are different from those in the Nuscenes dataset samples. How can I replace the images in the old dataset with images from the new dataset?

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For FID, please track progress at #32

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Dear author, thank you very much for your reply. However, if we only calculate FID, I think we can use the test generated ori_img and gen_img to calculate it. But compared to this, I am more concerned about how to apply it to object detection networks such as BEVFusion in the future. The current generation method seems to only be able to concatenate 6 views together. May I ask if I need to use the generated images to create a new dataset, do I need to split all the images in the test generated validation set myself and convert them into the format of nuscenes validation set?

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if we only calculate FID, I think we can use the test generated ori_img and gen_img to calculate it.

You can calculate like this if you want, but this is not the standard process and we never adopt this in any case.

The current generation method seems to only be able to concatenate 6 views together.

If you look into the code, you will find out that each image is generated separately and then stitch together. You can change the code for your purpose.

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Okay, thank you for your reply. I will try it out.

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Close for now. If you have other follow-ups, feel free to re-open.

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