Image GPT, or iGPT, is a machine learning model developed by OpenAI that combines the power of natural language processing with computer vision to generate realistic images.
At its core, iGPT is an autoregressive language model that uses a transformer architecture to learn the relationships between the pixels in an image. It is trained on massive amounts of data to predict the next pixel in an image based on the previous pixels.
This table shows the model specifications:
Model Name | Input Resolution | Parameters | Features |
|---|---|---|---|
iGPT-Large | 32*32*3 & 48*48*3 | 1362 | 1536 |
iGPT-XL | 64*64*3 | 6801 | 3072 & 15360 |
Unlike traditional computer vision models, iGPT can generate images from scratch without the need for pre-existing images or templates. It can also perform a wide range of image-related tasks, such as image completion, style transfer, and image captioning.
There are some tuning techniques of Pre Training & Fine Tuning:
One of the key advantages of iGPT is its ability to generate highly realistic images. It can produce images with intricate details, such as realistic textures, shadows, and lighting.
Moreover, it can generate images that are novel and creative, opening up exciting new possibilities for artists, designers, and other creatives.
However, there are also some limitations to iGPT. For example, it can struggle with generating images that require a deep understanding of context or with generating images that deviate significantly from the training data. Nonetheless, iGPT is a promising new tool in the field of computer vision, and its potential applications are vast and varied.