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Awesome GitHub RepositoriesArray-Based Data Containers
Provides efficient NumPy-based data structures for handling image and metadata arrays in anomaly detection workflows.
Distinct from NumPy Array Integration: Distinct from NumPy Array Integration: focuses on providing data structures that store image and metadata as NumPy arrays, not on memory mapping or integration layers.
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Awesome Array-Based Data Containers GitHub Repositories
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- open-edge-platform/anomalib
open-edge-platform/anomalib
5,871GitHub पर देखेंAnomalib is a PyTorch-based library for visual anomaly detection, offering a modular framework, a comprehensive model zoo, and a benchmarking suite designed for industrial defect detection. It provides a wide range of algorithms—including generative, discriminative, teacher-student, and vision-language approaches—that support unsupervised, few-shot, and zero-shot settings. The library enables deployment through model export to ONNX and OpenVINO for edge devices, and includes a no-code web application for training and inference. It also features a command-line interface for orchestrating multi
Anomalib provides efficient numpy-based data structures for handling image and metadata arrays in anomaly detection workflows.
Pythonanomaly-detectionanomaly-localizationanomaly-segmentation
