Text to image tools

There are several text-to-image tools available that can generate images based on textual descriptions. These tools use various techniques such as deep learning and generative adversarial networks (GANs) to convert text into visual representations. Here are a few popular text-to-image tools:

DALL-E: Developed by OpenAI, DALL-E is a text-to-image model that generates images from textual descriptions. It uses a combination of unsupervised learning and reinforcement learning to create unique and imaginative images.

AttnGAN: AttnGAN is a generative adversarial network-based model that can generate images from textual descriptions. It incorporates attention mechanisms to align the generated images with the given text.

StackGAN: StackGAN is another GAN-based model that can generate high-resolution images from textual descriptions. It employs a two-stage process where the first stage generates a low-resolution image, and the second stage refines it to produce a high-resolution image.

CLIP + VQ-VAE: This method combines the Contrastive Language-Image Pretraining (CLIP) model with the Vector Quantized Variational Autoencoder (VQ-VAE) architecture. It can generate images conditioned on textual prompts by optimizing the latent space of the VQ-VAE to match the text.

GPT-3 + Image Prompting: While primarily a language model, GPT-3 can also generate images when given textual prompts. By providing a detailed description or asking GPT-3 to "imagine an image," it can generate visual content based on the text provided. 

Artbreeder: Artbreeder is a platform that enables users to create new artworks by blending existing images together. While it primarily focuses on image manipulation and generation, it also has text-to-image functionality. You can input text prompts to guide the image generation process. Artbreeder offers both free and paid plans, with the free version providing access to a limited set of features.

DeepArt.io: DeepArt.io is an online platform that utilizes deep neural networks to transform images using artistic styles. While it is primarily geared towards style transfer and image manipulation, it doesn't have direct text-to-image synthesis capabilities. However, you can still use it in combination with other tools or approaches, such as providing textual descriptions to generate images separately and then applying style transfer using DeepArt.io.

there are some free alternatives and resources you can explore:

RunwayML is a creative tool that allows you to experiment with various machine learning models, including those for text-to-image synthesis. It provides a user-friendly interface and offers a range of pre-trained models that you can use for generating images from text prompts. While RunwayML offers a subscription-based plan, it also provides a limited free version that allows you to explore the tool's capabilities.

Google Colab: Google Colab is a free cloud-based platform that provides access to GPUs and TPUs. You can utilize it to run pre-trained text-to-image models such as DALL-E or AttnGAN, as long as you have the necessary code and model checkpoints.

OpenAI API Playground: OpenAI provides an API for their models, including the text-to-image model DALL-E. While the API itself is not free, OpenAI offers a limited access version called the "OpenAI API Playground" where you can experiment with the model and generate images for free within certain usage limits.

GitHub repositories: There are several open-source text-to-image models available on platforms like GitHub. You can search for repositories that contain code implementations of these models and run them locally. Keep in mind that setting up and running these models might require some technical expertise.