{ "checker": { "claims": [ { "claim": "Each photo is cut out into a new output folder (tested with -o, since the default -no-bg location is not an argv destination)", "command": " -o -y", "evidence": "\u20261 done \u00b7 0 failed \u00b7 0 already done \u00b7 13s\n ! showcase.png: edge MP to fit free RAM\n output \u2192 \n\n", "expected": "one image processed into the new folder ", "input": "", "kind": "claim", "outcome": "Real input produced the expected result: 1 done", "returncode": 0, "source": "Output goes to a new `-no-bg/` folder next to the input.", "source_checked": true, "source_file": "README.md", "verdict": "yes" }, { "claim": "--dry-run --json plans the run as JSON with the model chosen", "command": " --dry-run --json", "evidence": "\u2026\"model\": \"silueta\", \"model_choice\": {\"profile\": \"uniform\", \"model\": \"silueta\", \"score\": 8.1, \"best_model\": \"birefnet-general-lite\", \"best_score\": 8.6, \"best_needs_gb\": 11.7, \"needs_gb\": 3.0, \"fits\": true, \"gap\": 0.5}, \"edges\": \"matte\", \"output_format\": \"png\", \"finish\": null, \"already_done\": 0}\n", "expected": "JSON plan event naming the auto-chosen model silueta", "input": "", "kind": "claim", "outcome": "Real input produced the expected result: \"model\": \"silueta\"", "returncode": 0, "source": "scan and plan only; one JSON event per line for agents", "source_checked": true, "source_file": "README.md", "verdict": "yes" }, { "claim": "--shop plans a white square 2000 px JPEG output", "command": " --shop --dry-run --json", "evidence": "\u2026\"output_format\": \"jpg\", \"finish\": {\"background\": \"#FFFFFF\", \"square\": true, \"pad\": 7.5, \"size\": 2000}, \"already_done\": 0}\n", "expected": "plan with output_format jpg", "input": "", "kind": "claim", "outcome": "Real input produced the expected result: \"output_format\": \"jpg\"", "returncode": 0, "source": "`--shop` puts every product on white, square, 2000 px and ready to", "source_checked": true, "source_file": "README.md", "verdict": "yes" } ], "cycle_checks": [ { "claim": "Scheduled or looping main behavior", "command": "", "evidence": "Entry points inspected (README, src/bulk_bg_remove cli.py and the ui server). The product is a one-shot CLI run per folder; no cron, scheduler, --once/--now, or webhook loop was found. The only while-True loop is the local UI server's event stream (src/bulk_bg_remove/ui/server.py:343), which is not a product cycle.", "expected": "identify the product trigger", "input": "source inspection", "kind": "cycle", "outcome": "Entry points inspected (README, src/bulk_bg_remove cli.py and the ui server). The product is a one-shot CLI run per folder; no cron, scheduler, --once/--now, or webhook loop was found. The only while-True loop is the local UI server's event stream (src/bulk_bg_remove/ui/server.py:343), which is not a product cycle.", "source": "repository entry points", "verdict": "yes" } ], "details": { "argv": [ "", "", "-o", "", "-y" ], "kind": "cli", "needs_browser": false, "needs_credentials": false, "returncode": 0, "scope": "product operation", "stderr": "", "stdout": " \u2584\u2584\u2584 BULK-BG-REMOVE \u2584\u2584\u2584\n v0.1.0 \u00b7 100% local \u00b7 subject pixels untouched\n\n [1/4 SCAN] x86_64 \u00b7 1 perf cores \u00b7 3.5 GB free RAM \u00b7 cpu\n 1 images (WebP 1) \u00b7 0 MB \u00b7 0 skipped\n [2/4 PLAN] 1 to process \u00b7 1 worker, one image at a time (limited by RAM) \u00b7 \nETA ~2s\n model silueta \u00b7 edges matte \u00b7 needs 3.0 GB free RAM\n auto: silueta fits your free RAM (8.1/10 on uniform images; best \nbirefnet-general-lite 8.6)\n output \u2192 \n\n[excerpt truncated]", "working": true }, "evidence_strength": "readme_checked", "example_checks": [ { "claim": "Documented folder run with --format webp for smaller lossless files", "command": " -o --format webp -y", "deferred": false, "evidence": " by RAM) \u00b7 \nETA ~2s\n model silueta \u00b7 edges matte \u00b7 needs 3.0 GB free RAM\n auto: silueta fits your free RAM (8.1/10 on uniform images; best \nbirefnet-general-lite 8.6)\n output \u2192 \n\n [3/4 RUN] loading model in each worker\u2026\n worker 0 ready\n \u2713 demo.webp 1280\u00d7720 1.6s\n\n [4/4 VERIFY] checking 1 outputs\u2026\n GAME CLEAR \u00b7 1 done \u00b7 0 failed \u00b7 0 already done \u00b7 5s\n output \u2192 \n", "expected": "one image processed into as webp", "input": " --format webp", "kind": "example", "outcome": "command completed successfully", "returncode": 0, "source": "README.md Options table: --format webp|jpg", "verdict": "yes" } ], "status": "PASS" }, "deviations": [ "Installed the PyPI release (uv tool install bulk-bg-remove, version 0.1.0) as the README documents, instead of building from the pinned checkout; the workspace pyproject also says 0.1.0 but I did not diff the sources.", "Input photo was assets/showcase.webp from the repo (a composite of four real photos), copied into fresh input folders.", "Claim and example runs use an explicit -o output folder, because the checker requires output_directory to match an argv destination; the README default location (-no-bg next to the input) was observed manually in the first run but not replayed.", "The --ui browser drag-and-drop page was not exercised; the CLI path was used instead.", "No Git metadata setup was needed; the workspace was used directly, not as a git checkout.", "Removed my manual photos-no-bg output before replay; checker-generated output folders were left in " ], "fault_owner": null, "main_blocker": null, "operation": "Remove backgrounds from every photo in a folder with the bulk-bg-remove CLI, writing a new output folder with cut-out PNGs", "operation_scope": "Linux x86_64 guest (Ubuntu, Python 3.12.3, uv 0.13.5), CPU only, 3.5 GB free RAM; downloads the silueta model (44 MB) on first run; no browser or credentials needed for the CLI path", "outcome": "working", "plain_failure": null, "steps": [ "curl -s $CDP_URL/json/version (HTTP 200, Chrome/155 shared endpoint reachable; not needed for CLI)", "uv tool install bulk-bg-remove (installed 0.1.0 into )", "bulk-bg-remove doctor (READY)", "bulk-bg-remove --dry-run --json (plan: model silueta)", "bulk-bg-remove -y (1 done, 0 failed; output showcase.png)", "bulk-bg-remove -o -y (probe, replayed PASS)", "bulk-bg-remove --shop --dry-run --json (output_format jpg)" ], "stuck_step": null, "suggested_fix": null }