Art Recognition with a Computer Vision Model
Blog post from Roboflow
A Roboflow Universe project introduces an art classification model capable of predicting the artistic movement and style of an image, covering a range from Early Renaissance to Pop Art. Trained on the Wiki Art dataset using Roboflow's one-click training solution, the model utilizes a collection of 6,417 images across 25 different classes. Users can test the model's predictions for free by dragging and dropping an image on the project page, and it supports various deployment options, including API, curl command, Webcam, and an Example Web App. The original dataset, credited to Wei Ren Tan, Chee Seng Chan, Hernan E. Aguirre, and Kiyoshi Tanaka, is available on GitHub along with their related research paper. Roboflow Universe encourages users to explore new datasets and models released weekly, offering continual access to advancements in computer vision.
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