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Train the model where the workflow lives
deep-learning machine-learning computer-vision

Train the model where the workflow lives

New deep learning and machine learning nodes bring trainable vision, sensor forecasting, anomaly detection, and model deployment into Flow-Like workflows.

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From a Detection to a Track, Then an Entity
computer-vision tracking onnx

From a Detection to a Track, Then an Entity

Build a camera workflow that separates detected boxes, temporal tracks, appearance evidence, and entity associations, including uncertain results and state lifetime.

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Local Vision, Useful Results: Face Analysis Comes to Flow-Like
local-ai computer-vision face-analysis

Local Vision, Useful Results: Face Analysis Comes to Flow-Like

Flow-Like adds local SCRFD face detection, ArcFace embeddings, age and gender estimates, verified model caching, and one ONNX acceleration policy across platforms.

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