deep-chat VS yolov7

Deep Chat has just received a huge update! You can now host entire LLMs on the browser. No servers, no connections, run it all in the comfort of your browser. Supported models include popular LLaMA and Mistral LLMs.

Check out the Open Source project to add it to your website: https://github.com/OvidijusParsiunas/deep-chat

Try it out live in the Deep Chat playground:

You provide examples of a backend endpoint for the major frameworks / languages. Such as PHP/Ruby/Go/.Net/Java/NextJS/Express etc.

Example: https://github.com/OvidijusParsiunas/deep-chat/tree/main/exa...

Check it out here: https://github.com/OvidijusParsiunas/deep-chat

If you want something off-the-shelf, try YoloV7.

The current dictionary is still in a beta state and has only been trained on 80 words (e.g. 'man', 'dog', 'car', 'keyboard', 'book', etc.; see list of words, see dataset). I used the object detection model Yolov7 (paper, all credits to them).

(Please note, this is a re-post of my original question here, I think this subreddit might be more appropriate for asking this question)At work, we use Unity, we have a project that needs object detection and classification. We decided to use this YOLO7 model (for non-technical reasons, It had to be the exact same model as the company does have pre-trained weights for this exact model). However, Unity only supports ONNX so I exported the model as an ONNX model, using the code provided in the repo:

Github Projects offering pretrained weights and train / run scripts. Example

The only project I found is this one that implements Yolov7

I'm wondering if there's an efficient way to visualize the image augmentations from the Yolov7 hyperparameters list here

yolov7: https://github.com/WongKinYiu/yolov7#performance