How to Use Roboflow Models in Make Sense

Roboflow has introduced a new integration with the Make Sense annotation tool to streamline the process of annotating images for computer vision models, thereby reducing the time between conceptualizing and deploying a model. This integration allows users to utilize Roboflow models within the Make Sense environment to suggest annotations, which can be accepted, rejected, or modified, thus minimizing manual annotation efforts. The guide outlines the steps to use this model-assisted labeling feature, which involves uploading images, configuring the Make Sense tool with a Roboflow model, and using the model to automatically generate and refine annotations. The predictions made by the model are drawn as bounding boxes in Make Sense, allowing users to adjust them as needed before exporting the annotations for further use in training models. This enhancement makes annotating images significantly faster, leveraging Roboflow’s capabilities to optimize the workflow in Make Sense.