From Pixels to Diagnosis: Building a Real-Time Skin Lesion Classifier with Flutter & ViT

In the world of digital health, the distance between a patient and a preliminary diagnosis is shrinking rapidly. Today, we're diving into the intersection of Mobile Vision, TensorFlow Lite, and Vision Transformer (ViT) to build an offline, privacy-first skin lesion classification app. Whether you are interested in on-device machine learning, Flutter AI integration, or optimizing Vision Transformers for mobile, this guide covers the end-to-end journey of bringing high-accuracy medical imaging to the palm of your hand. Why Offline Mobile Vision? Healthcare apps often struggle with two major hurdles: Privacy and Connectivity. By leveraging TensorFlow Lite Quantization, we can deploy a complex Vision Transformer model directly on a smartphone. This allows for: Zero Latency: Instant inference without waiting for a server response. Privacy: Sensitive medical images never leave the user's device. Accessibility: Works in remote areas with no internet. The Architecture To achieve high-speed inf