# image classification output for Yolo in 2022

**URL:** <https://support.prodi.gy/t/image-classification-output-for-yolo-in-2022/5156>\
**Category:** Uncategorized\
**Tags:** usage, image, solved\
**Created:** [January 4, 2022, 10:28pm UTC](https://support.prodi.gy/t/image-classification-output-for-yolo-in-2022/5156 "2022-01-04T22:28:51Z")\
**Posts on this page:** 1\
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**Author:** ![ljvmiranda921](https://sea2.discourse-cdn.com/flex020/user_avatar/support.prodi.gy/ljvmiranda921/32/3197_2.png) [@ljvmiranda921](https://support.prodi.gy/u/ljvmiranda921)\
**Post date:** [January 5, 2022, 3:45am UTC](https://support.prodi.gy/t/image-classification-output-for-yolo-in-2022/5156/2 "2022-01-05T03:45:09Z")

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Hi @info2000, the output annotations are still in a JSONL file, and you still need to parse it to the YOLO format afterwards. You can refer to this [blogpost](https://mlops.systems/redactionmodel/computervision/datalabelling/2021/11/29/prodigy-object-detection-training.html) that did a similar approach (although here he's converting it into the COCO format but he also showed what a typical image annotation looks like)

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