feat(evaluation): add task-aware metrics, reporting, and workflow automation#7
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feat(evaluation): add task-aware metrics, reporting, and workflow automation#7cto-new[bot] wants to merge 1 commit intomasterTingelam/DeepLearningExamples:masterfrom feature-eval-reporting-workflowTingelam/DeepLearningExamples:feature-eval-reporting-workflowCopy head branch name to clipboard
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…ow automation This adds a full evaluation and reporting framework for Street Scene. Introduces task-aware metrics, a reporting system, and end-to-end workflow automation. - Implemented src/evaluation/metrics.py with detection, tracking, and classification metrics - Implemented src/evaluation/reporting.py to generate JSON/Markdown/HTML reports and comparisons - Wired the pipeline to emit metric plots and reproduction checklists after training and evaluation - Added CLI scripts: run_workflow.py, compare_runs.py, verify_repro.py, and deploy.py (stub) - Updated documentation (docs/evaluation_and_reporting.md, README) and dependencies (scikit-learn, motmetrics, seaborn) Impact: ensures reproducibility and easier cross-run analysis; reports saved per run.
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