yolov7 VS kafdrop

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

Are there any comparison to CMAK or Kafdrop ?

For Kafka I really liked using tools like conduktor or Kafdrop where you can basically create a subscription ad look at topics, events and payloads.

Kafdrop - https://github.com/obsidiandynamics/kafdrop

No mentions, and 1 open issue with a question 2) Kafka Drop https://github.com/obsidiandynamics/kafdrop

Kafdrop (https://github.com/obsidiandynamics/kafdrop) is very popular and pretty solid. I'd start there. Kafka itself also comes with some cli tools and you can also extract metrics out of it via JMX/jolokia.

Kafdrop