Generating Renaissance Art with Computer Vision
Blog post from Roboflow
Two high school sophomores, Samay Lakhani and Sujay Sundar, developed a Deep Convolutional Generative Adversarial Network (DCGAN) during a 24-hour hackathon to create abstract images in the style of Renaissance paintings. Utilizing Roboflow to preprocess and augment their dataset, they increased the number of images from 300 to over 900, allowing the model to better capture and reproduce key features of Renaissance art. Their project, inspired by ThisPersonDoesNotExist.com, aimed to demonstrate the accessibility of building computer vision models. Despite initial challenges, including the model producing noise, data augmentation through Roboflow significantly enhanced performance, ultimately leading them to win the hackathon's social impact category. The students have prior experience with Roboflow's tools, achieving high precision in object detection tasks, highlighting Roboflow's efficiency in reducing the time and effort needed for computer vision projects.
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