2 repository-uri
Automated plotting and analysis tools for machine learning experiments.
Distinguishing note: Focuses on visualization automation for tuning.
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Anomalib 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
Logs training parameters and outputs to loggers and generates visual plots for experiment analysis.
SwanLab is an open-source machine learning experiment tracking platform and observability tool. It provides a centralized dashboard for logging training metrics, hyperparameters, and hardware performance to monitor and analyze AI model training runs. The platform is distinguished by its focus on self-hosted infrastructure, allowing users to deploy private instances via Docker or Kubernetes for secure on-premises data control. It also includes specialized utilities for migrating historical experiment logs and synchronizing real-time metrics from external tools like MLflow. The system covers a
Renders training data using interactive line charts, ROC curves, and custom visualizations with filtering.