A text-to-image generation model takes text input and generates an output image based on the textual description. The model uses advanced deep learning algorithms to learn the relationships between the text and the corresponding images. These models are trained on large datasets of paired text and image samples to learn how to generate images that align with the given text description. The models employ a variety of techniques such as convolutional neural networks (CNNs) and generative adversarial networks (GANs) to generate high-quality images that accurately reflect the characteristics of the given textual input.
Current Prompt: Photo of a sunset behind the Eiffel Tower, shot with a 35 mm camera, featuring realism, octane render, 8k resolution, trending on artstation, hyper-detailed, photo-realistic with maximum detail, volumetric light, realistic matte painting, ultra-detailed, contrasting with an ‘ugly, low quality’ aesthetic.