Our professionally trained annotators will annotate images of shelves, products, brands and prices for you. Whether the images are normal or panoramic, you can count on us to deliver high-quality annotations. We’ll even make a dataset from our own images if you don’t have any to use. We support many diverse retail applications. We’ll help you create and optimize deep learning models for any retail application imaginable, such as shelf management, price checking, identifying misplaced items, and more.
Our first step in creating a dataset for logos is to collect data. We scour the planet for tens of thousands of original images, content created for us from micro workers around the world. They are paid in Ether for their hard work, which is diligently scrutinized by our experienced project managers. Once we have quality image data then we can analyze the images in our image annotation platform, by our annotater team, also distributed around the world.
Here we have a high quality dataset - a large group of diverse images in the wild. Unlike photos on the web, which are often marketing images with photosohopped backgrounds, our images are truly real-world images. They include the complexities of real world lighting and backgrounds and so on, which makes this data all the stronger.
At this point we have trained the model ourselves on various platforms, such as Google AutoML and Amazon, and have evaluated the results in our own platform. As you can see here we can demonstrate the precision, recall, confidence threshold, and more aspects of the model. Also below you can see a confusion matrix, which shows the accuracy in recognizing specific objects that we have trained the model to recognize. But don’t worry, we customize our efforts to tailor to your level of needs, so whether or not you have machine learning engineers, we can help you.