# unable to use binary classification for images using jsonl loader **URL:** \ **Category:** Uncategorized\ **Tags:** usage, image, solved\ **Created:** [July 8, 2021, 1:50pm UTC](https://support.prodi.gy/t/unable-to-use-binary-classification-for-images-using-jsonl-loader/4419 "2021-07-08T13:50:19Z")\ **Posts on this page:** 1\ **Showing post:** 2
**Author:** ![ines](https://sea2.discourse-cdn.com/flex020/user_avatar/support.prodi.gy/ines/32/3_2.png) [@ines](https://support.prodi.gy/u/ines)\ **Post date:** [July 10, 2021, 7:01am UTC](https://support.prodi.gy/t/unable-to-use-binary-classification-for-images-using-jsonl-loader/4419/2 "2021-07-10T07:01:02Z")
Hi! The problem here is that when you load in your data via JSON(L), Prodigy will just take exactly what's in the data and render it in the UI – in this case, images from local file paths. However, images and other files from local paths are typically [blocked by modern browsers](https://stackoverflow.com/questions/39007243/cannot-open-local-file-chrome-not-allowed-to-load-local-resource) for security reasons – you can disable this, but it's not usually recommended. The `image` recipes use the [`fetch_media`](https://prodi.gy/docs/api-components#fetch_media) pre-processor to convert images from local paths to base64-encoded strings, so you can send them directly over the API. This works fine for smaller files and means you can store the data with the annotations. If your files are larger, it's usually better to serve them from a local web server or URLs instead. See [my comment here](https://support.prodi.gy/t/choice-of-audios/4408/2) for more details. So if you want to load your images from a JSONL file instead of a directory, the easiest solution would be to either start a local web server in the top-level directory and use `localhost` paths, or to put them in an S3 bucket or similar. --- _[View the full topic](https://support.prodi.gy/t/unable-to-use-binary-classification-for-images-using-jsonl-loader/4419)._