tao-analyze-gaps-vlm-bcq

VLM Binary Classification Gap Analysis Reads a VLM predictions JSON, compares each model response against ground truth, and writes FP/FN failure cases to a JSONL file with a summary report. Purpose After running a VLM on a binary yes/no evaluation task, the predictions need to be compared against ground truth to identify failure cases. This skill produces a structured list of FP (false positive) and FN (false negative) samples that downstream RCCA stages (e.g., cosmos generation, root cause analysis) consume to drive a DEFT iteration. Usage Invoke the vlm_bcq action inside the TAO Toolkit data services container with Hydra-style key=value overrides: gap_analysis vlm_bcq \ predictions_json = /path/to/results.json \ results_dir = /path/to/output/gaps Include videos_dir when video_id values in the predictions are relative paths: Show more Installs 584 Repository nvidia/skills GitHub Stars 1.9K First Seen Jun 8, 2026 Security Audits Gen Agent Trust Hub Pass Socket Pass Snyk Pass