Computer vision researchers requires natural language image segmentation for large-scale computer vision model training
A research team required semantic segmentation of approximately 7 million images to train a computer vision model, but manual pixel-level annotation would have been prohibitively expensive and time-consuming. Easie deployed a fine-tuned LLM with conversational segmentation capabilities through EasieOps infrastructure to automate the process, generating pixel-accurate masks, bounding boxes and labeled annotations at scale for use with a ResNet-50 backbone.
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