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Displaying 14 results

CDF Augmentation is an image & video augmentation pipeline that leverages NVIDIA Cosmos and other generative models to produce photorealistic synthetic image and video data. It supports multiple augmentation strategies including weather, lighting, and scene transformations for training and validating models in NVIDIA Metropolis applications.
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Enhances images and videos before downstream annotation stages.
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Generates visual QA evidence and converts it into structured annotation artifacts.
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Runs RF-DETR object detection and multi-object tracking.
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Adds reasoning traces to existing annotations using captioning, visual QA, and other available scene context.
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Generates image and video captions for the Auto Labeling pipeline.
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Exports completed scene annotations to supported training formats.
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Runs SAM3 text-prompted object detection and tracking.
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Assembles person attributes and generates search queries from visual QA results.
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Uses SAM3 to ground image expressions into bounding boxes and masks.
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Extracts groundable expressions from image captions.
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Compiles and launches Dockerized Auto Labeling service workflows.
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Generates discriminative referring expressions for known image objects.
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CDF Simulation generates annotated synthetic PCB imagery for training and validating automated optical inspection models. It uses NVIDIA Omniverse Replicator to produce photorealistic images for manufacturing quality assurance pipelines.
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