Looksense Machine Learning
Machine LearningDecember 2024 - Present
Project Overview
Looksense is a sophisticated machine learning project that implements a 7-class classification model using PyTorch. The model processes input images of size 177x177 pixels and utilizes advanced data augmentation techniques to improve performance. A key technical achievement is the successful conversion of the PyTorch model to TensorFlow.js, enabling browser-based inference. The project is deployed and accessible through both a custom domain (looksense.site) and GitHub Pages.
Technical Implementation
Model Architecture: The PyTorch model is designed to process 177x177 pixel images across 7 distinct classes, providing robust classification capabilities.
Data Augmentation: Implemented advanced augmentation techniques to enhance model generalization and performance, ensuring robust predictions across varied input conditions.
Model Conversion: Successfully converted the PyTorch model to TensorFlow.js through an intermediate TensorFlow conversion, enabling direct browser-based inference without server dependencies.