ultralytics VS steampipe

Yep, I noticed this a while ago. It posts easily identifiable ChatGPT responses. It also posts garbage wrong answers which makes it worse than useless. Totally disrespectful to the userbase.

https://github.com/ultralytics/ultralytics/issues/5748#issue...

There are obvious places it is being used that I have noticed organically. For instance, check out the answers in this repo:

https://github.com/ultralytics/ultralytics/issues/5748#issue...

If you read the answers there, the style of answering is always to repeat the question in a very specific way. Once you see it you can’t in-see it.

When browsing the state-of-the-art in object detection on Papers with Code, I found the YOLO model to be one of the most popular, accurate, and fastest. That being said, I would recommend having a look at Ultralytics, which provides the tools to evaluate, predict, and export the latest versions of YOLO models with only a few lines of code.

YOLOv8 (You Only Look Once) is an open-source Computer Vision AI model released on January 10th, 2023. It’s called YOLO because it detects everything inside an image in a single pass. The new version can perform image detection, classification, instance segmentation, tracking, and pose estimation tasks.

Next, I needed to figure out, how can I access the stream, recognize an animal, then let Max know? There are tons of examples of recognizing an object via camera frames, but I ultimately found this python library called ultralytics that supports RTSP streams and classifying objects in the video frames using pre-built models. The docs looked like it would be pretty low effort, so after some experimentation, I was successful in having the ultralytics library recognize objects from my cheap camera!

I have created an issue in their Github as well but so far not much help has been recieved. You can check that here

And the target models include: * YOLOv8 (You Only Look Once) * YOLO-NAS * YOLOv5 * and DETR

Steampipe is a tool for querying cloud APIs and other data sources using SQL in a zero-ETL manner.

Readers may also enjoy Steampipe [1], an open source CLI to live query Google Sheets [2] and 140+ other services with SQL (e.g. AWS, GitHub, etc). It uses Postgres Foreign Data Wrappers under the hood and supports joins etc across the services. (Disclaimer - I'm a lead on the project.)

1 - https://github.com/turbot/steampipe

be mindful of its AGPLv3 https://github.com/turbot/steampipe/blob/v0.21.8/LICENSE (AFAIK v0.4.3 is the last MIT release https://github.com/turbot/steampipe/blob/v0.4.3/LICENSE ) and the actual providers are Apache 2 <https://github.com/turbot/steampipe-plugin-aws/blob/v0.131.0...> (but I don't know if provider drift makes them compatible with 0.4 or not)

iasql seems to be AWS only, but good for them for taking this on:

In a prior post I showed how to install Steampipe in AWS CloudShell to instantly query over 460+ resource types from your AWS APIs using SQL, and another post on how to use the Steampipe AWS Compliance mod to assess over 25+ security benchmarks across your AWS accounts.

Readers may find Steampipe's [1] AWS Thrifty Mod [2] useful. It will automatically scan multiple accounts and regions for 50 cost saving opportunities - many of which are looking for over-provisioned or unused resources. For example, it's crazy how much you can save by doing things like just converting your EBS volumes to the newer gp3 type. Combine with Flowpipe [3] to automate checks and actions. It's all open source and extensible.

1 - https://github.com/turbot/steampipe

Steampipe [1] is an open source project [2] that includes an embedded Postgres to instantly query cloud, code & more with SQL. This release expands our plugin ecosystem [3] to be a full Zero-ETL platform. Steampipe plugins can now run natively in your own Postgres as Foreign Data Wrappers [4], as SQLite extensions [5] or as simple data export tools [6]. Please give it a try, we'd love your feedback and contributions!

1 - https://steampipe.io