13 skills · sorted by relevance
Use this skill to bring a supported object-detection vision model from HuggingFace or NVIDIA NGC into an NVIDIA DeepStream pipeline with end-to-end automation: ONNX download, SafeTensors export, TRT engine build, custom nvinfer bbox parser, multi-stream benchmark, and PDF report. Object detection models only.
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Run TAO Data Services KPI analysis for object detection, comparing inference annotations against ground truth to compute per-class TP/FP/FN/TN, precision, recall, accuracy, and AP at a fixed IoU. Use when an object detection workflow needs per-class mAP reported after inference, or when the user asks to "run KPI analyze", "compute detection mAP", or "score my OD predictions against ground truth".
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Computer vision engineering for object detection, segmentation, and visual AI, covering CNN and Vision Transformer architectures and ONNX/TensorRT deployment. Use when building detection pipelines, training models, or optimizing inference.
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Train object-detection, image-classification, or SAM segmentation models on Hugging Face Jobs. Use for vision fine-tuning and evaluation; use huggingface-llm-trainer for language models.
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Routes FCOS object-detection repo tasks for inference demos, config/data setup, training/evaluation, ONNX export, and legacy PyTorch internals.
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Routes DINO DETR object-detection setup, COCO data validation, CUDA deformable-attention preparation, training, evaluation, inference, visualization, and bounded benchmarking tasks.
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Guide Det3D PyTorch 3D object-detection workflows across configuration, KITTI/nuScenes/Lyft data preparation, GPU training and evaluation, custom CUDA operations, and visualization.
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Routes Darkflow object-detection, training, and export workflows for the legacy YOLO package.
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Route D-FINE object-detection setup, training, architecture inspection, inference, export, and troubleshooting workflows.
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Routes CenterNet object-detection training, evaluation, configuration, and setup workflows.
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Operational guide for the NV oOS Dictation desktop companion app (Tauri v2 + Rust, examples/nvoos-dictate) — build/run on Windows/MSVC, the local-first engine track (parakeet/whisper/fastconformer/moonshine/silero-vad), the embedded remote-STT fallback, the Stage-2 polish provider track (disabled/openai_compat/nvoos plus local LM Studio and Ollama), the file/media decode seam (Symphonia 0.5), the live camera + local object-detection/tracking track (Proposals 073 + 075) with an opt-in VLM label-polish layer (Proposal 076), the CDP browser-control agent (feature agent) + FastConformer engine + NV oOS multi-SPA hub, model registry + verification harnesses, the plugins.updater boot-crash config rule, and the full test/clippy gate matrix. Use when building, extending, or debugging the dictation app, adding an engine/model, a polish provider, the browser agent, file/video transcription, camera/vision detection, or VLM relabeling.
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Computer Vision Specialist IA — Expert en vision par ordinateur (YOLO, OpenCV, object detection, OCR, segmentation)
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Computer Vision v2 IA — Expert en vision par ordinateur (détection d'objets, segmentation, OCR, vidéo, déploiement edge)
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