kener VS Deep_Object_Pose

1. Kener

I think the incident.svelte file could use some love, is it best practice to put part of the phrase somewhere else? Doesn't it increase the cognitive stress? Like there is somewhere a phrase, but part of the text is being calculated https://github.com/rajnandan1/kener/blob/74ea57d6bbf6ac4dd3e...

Isn't it easier to understand what is going on just by calculating the condition on the top and put the text on the markup based on that condition?

I feel like there are few places where in order to don't duplicate part of the text it's being made extremely difficult what the text is going to be by putting it far away

I've been doing some research in this area and there are a few deep learning solutions to this problem. For example, NVIDIA's Deep Object Pose Estimation will estimate the 6DOF pose of a known object. But you'll have to train the network if you want to detect a new object. PoseCNN, which someone else mentioned, does a similar thing. CenterPose is more interesting, as it can estimate then pose of an object from a known category; e.g. sneakers, or laptops, rather that one specific object (as DOPE and PoseCNN do).

For our last event of ArchE Week, the Ohio State Underwater Robotics Team (Website, Instagram) is hosting a workshop tonight on machine learning! The workshop is an interactive walkthrough of using machine learning solutions to make predictions. Some example problems we could be trying to solve are predicting a grade, predicting the weather, and the classic recognize a digit problem. Our team personally uses machine learning to do real-time object detection with YOLO and NVidia DOPE, so we may touch on that as well!