Detect Small Objects with Roboflow Workflows
Blog post from Roboflow
In the context of computer vision projects focused on detecting small objects, the SAHI technique, which involves slicing large images into smaller segments for individual inference and then stitching the results, can enhance detection accuracy. The guide explains how to implement this technique using Roboflow Workflows, a web-based application builder, by creating a small object detection pipeline with an Image Slicer block. The process involves slicing an input image, running an object detection model on each slice, and then using a Detections Stitch block to combine the results. Visualization is enhanced with bounding box and label visualizers. Testing and deploying the Workflow can be done through the Roboflow cloud, a dedicated server, or personal hardware, with deployment options suited to varying latency requirements. The guide serves as an introduction to utilizing Roboflow for building efficient small object detection systems, with additional resources available for exploring more templates and blocks.