Full Disclosure: I'm a ML Team Lead at DagsHub.

TL;DR DagsHub lets you stream datasets from any repo you can access for free. We have open-source datasets for various tasks and domains (image, video, MRI, audio, etc.) that you can use, or upload yours and stream it. Learn more - https://dagshub.com/docs/feature_guide/direct_data_access/

How does it work? Every DagsHub repo comes with a configured remote storage, where users can host models, datasets, or any other large file.

We recently added a new capability to our open-source client and free-to-use API that enables the streaming of files stored on DagsHub Storage.

It enables access to any dataset stored on DagsHub, stream it to your machine, version it, and upload it to your DagsHub repo - all from your python code.

I think the coolest part of this feature is that it doesn't require any modifications to your code base or data format.

You can find more info about it here -> https://dagshub.com/docs/feature_guide/direct_data_access/

Feel free to reach out if you have any other questions (:

Comparing confidence metrics of the networks themselves is like comparing two athletes by asking them each how good they are and declaring athlete B the winner of the race because he thought he was better than athlete A thought about himself.

Yup. They don't plan to release a paper but a technical report https://github.com/meituan/YOLOv6/issues/95

I agree. The name YOLO is heavily amused (A good example: https://github.com/jinfagang/yolov7). However, you should note that the research team of YOLOv5 is also not the original one. As @garblegarble mentioned, the original research group stopped working on it (https://news.ycombinator.com/item?id=31918087).

> But note that YOLOv7 doesn't meant to be a successor of yolo family, 7 is just a magic and lucky number. Instead, YOLOv7 extend yolo into many other vision tasks, such as instance segmentation, one-stage keypoints detection etc..

Are you kidding me?

Deceptive habits like this give ML a really bad reputation and gives me so little confidence that this technology will be used responsibly as ML becomes increasingly powerful.