Understanding Hand-Drawn Images with Image-to-Text Processing
Explore how Google Gemini uses image-to-text processing to analyze hand-drawn images. Understand CNN encoders and decoders in generating textual descriptions and how to apply these concepts to build AI tools like a Pictionary game.
Behind the scenes
Multimodal models such as Gemini can work with images as input. This enables them to analyze an image and generate a textual description of its content. Here’s a brief overview of how most image captioning models work:
The image is first processed into a format that is easily digestible for the model.
A
analyzes the image, extracting features like edges, objects, and their spatial relationships. This creates a compressed representation of the image’s visual content.CNN encoder A Convolutional Neural Network (CNN) encoder specializes in processing images/videos. It acts like a data summarizer, transforming raw visuals into a compact representation that captures the essence of the content. The
receives the encoded image representation from the CNN. It starts ...decoder Decoders are like translators. They take a condensed version of information, created by an encoder, and turn it back into something we can understand.