#Ai

One of my favorite tools for people to dive into deep learning is Darknet. Not this one. This is a neural network framework in c. But despite that, this is nice in a way that it can function as an application. Before you use it, you need the weights file, it is linked in the repository. The command is, darknet detector test <labels> <config> <weights> <image path>. Example of usage is the following. [Read More]

So let say you want to training a neural networks to identify something in image. The first step is not actually code it. The first step is data gathering. The next step is labeling. You may also want to identify multiple objects in your image, if so you also need to label the items in the image. What we do in the case for object detection is, we essentially draw a square or a region and set a name. [Read More]

We have shown how one can create your own https://devkami.com/blogs/2021/01/11-ml-labeling/. Another way to get dataset is the Google Open Image Dataset. This is a dataset that have 1.5 million annotations for 600 categories. It covers some common thing that trained in YOLO. You can have a shot at trying to see if the category exist. To use this, I suggest that you use a tools, the one I use is the OID Toolkit, I use the fork by The AI Guy a youtuber talking about these. [Read More]