Developer Builds AI Painting Attribution Tool Using PyTorch and ResNet-50

A developer has created an artist attribution system that uses deep learning to predict the likely creator of a painting from an input image. The project leverages transfer learning with a pretrained ResNet-50 model rather than building a convolutional neural network from scratch, making training faster and more practical. Given an image, the model returns the top predicted artist along with a confidence score and the top three candidate guesses. The system supports multiple hardware environments, including NVIDIA CUDA, Apple Silicon, and standard CPUs, and can also run on cloud platforms like Google Colab. The project is intended as a practical introduction to computer vision, image classification, and fine-tuning techniques using PyTorch and torchvision.