Summary

In this chapter, we covered various image processing techniques, such as loading, resizing, normalizing, and standardizing images to prepare them for ML applications. We implemented augmentation to generate diverse variations for improved model generalization and applied noise removal to enhance image quality. We also examined the use of OCR for text extraction from images, particularly addressing the challenges presented by thumbnails. Additionally, we explored the BLIP model’s capability to generate captions based on visual content. Furthermore, we discussed video processing techniques involving frame extraction and key moment analysis.

Finally, we introduced the Whisper model, highlighting its effectiveness in converting audio to text and its automatic speech recognition capabilities across multiple languages.