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    Models/Object Detection/SalahALHaismawi/yolov26-fire-detection
    Object Detectionultralyticsmit

    yolov26-fire-detection

    by SalahALHaismawi

    Identifier
    Model ID
    SalahALHaismawi/yolov26-fire-detection

    Tags

    ultralyticsyoloyolov26fire-detectionsmoke-detectioncomputer-visionpytorchreal-timesafetyobject-detectiondataset:customlicense:mitmodel-indexregion:us

    Use yolov26-fire-detection on Mixpeek

    Build multimodal processing pipelines with this model and others. Extract features, run inference, and set up retrieval in Mixpeek Studio.

    Open Studio

    How It Runs on Mixpeek

    On Mixpeek, yolov26-fire-detection runs as a managed extractor inside a processing pipeline. Point a bucket of object detection data at it, and Mixpeek handles GPU provisioning, batching, retries, and writing the outputs into a vector store you can query.

    Extractor outputs land in the Mixpeek Vector Store (MVS), where you can combine them with retrieval, reranking, and filter stages to build end-to-end search and agent-perception pipelines, no model-serving infrastructure to maintain.