Update README.md

README.md

@@ -3,7 +3,7 @@ license: cc-by-4.0
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 # MapPool - Bubbling up an extremely large corpus of maps for AI
 
-This repository contains URLs, textual descriptions, embeddings of 50 million potential maps. It has been derived from the [CommonPool  dataset](https://huggingface.co/datasets/mlfoundations/datacomp_xlarge) from [DataComp](https://www.datacomp.ai/). The MapPool dataset may help to train resource-intensive architectures like Transformers or Diffusion Models in order to establish foundation models specialized on maps.
+This repository contains URLs, textual descriptions, embeddings of 75 million potential maps. It has been derived from the [CommonPool  dataset](https://huggingface.co/datasets/mlfoundations/datacomp_xlarge) from [DataComp](https://www.datacomp.ai/). The MapPool dataset may help to train resource-intensive architectures like Transformers or Diffusion Models in order to establish foundation models specialized on maps.
 
 ## How is the data structured?
 
@@ -96,6 +96,7 @@ if __name__ == "__main__":
     multiprocessing.freeze_support()
     main()
 ```
+Note that image links may be broken since the release of the original CommonPool dataset. It is estimated that 2/3 of the images are still available, that is, 50 million potential map images. 5TB of storage are needed when assuming an average image size of 100kB. With a large bandwidth, it may be possible to download the images within 24h.
 
 ## How was this dataset created?