
Stable Diffusion XL - Text 2 Image (Advanced)
In our last post, we explored basic themes to generate images from text. In this post, we investigate more advanced techniques to improve image quality.
In our last post, we explored basic themes to generate images from text. In this post, we investigate more advanced techniques to improve image quality.
Text-to-image generation has made significant strides, particularly with models like Stable Diffusion XL (SDXL). This article explores various aspects of image generation using SDXL and offers practical insights based on observed characteristics.
Google Gemma is a powerful neural network. While Gemma is primarily focused on research and advanced users, its neural network capabilities could be interesting to a wide range of users.
Image segmentation is crucial for object recognition and advanced image processing, perceiving object descriptions, and associating them with their respective image regions. Today we will explore use cases of such a model.
Image captioning is important because it provides a textual representation of the content and context of an image, improving accessibility and understanding for all users, especially those with visual impairments. In this post, we introduce BLIP for this use case.
Sentiment analysis is an increasingly important part of the evaluation of news from social networks. In the following article, we would like to present a pretrained transformer that is tailored for this task: the Emotion Text Classifier.
T5 is a powerful language model capable of performing a wide range of text-to-text tasks, including text classification, language translation or text summarization. The aim of this post is to introduce this pretrained transformer to the reader.