{
 "schema_version": 1,
 "generated": "2026-10-31",
 "id": "victorbutoi-flexray--get-higher-quality-masks-with-ensemble-and-tta",
 "repo": "VictorButoi/FleXray",
 "repo_url": "https://github.com/VictorButoi/FleXray",
 "repo_slug": "victorbutoi-flexray",
 "title": "Raise mask quality with the five-model ensemble",
 "page_title": "How to raise mask quality with the five-model ensemble with Fle Xray",
 "summary": "Use --ensemble and --tta-samples to trade run time for more accurate anatomy masks.",
 "who": "A researcher comparing segmentation results who needs the best available output for a small batch of X-rays and can wait longer per image.",
 "problem": "A single forward pass of the flagship model may not give the most reliable masks for difficult images.",
 "outcome": "Masks from the X-High setting, five-model ensemble with 8-pass test-time augmentation, saved to a predictions folder, optionally limited to one label.",
 "steps": [
  "Install the package with `python -m pip install flexray`.",
  "Run the X-High mode with `flexify --ensemble --tta-samples 8 --input ./image.png --output-dir ./predictions`.",
  "To keep one anatomical label only, add `--binary femurs` to the same command.",
  "Compare the output against the Low mode with `flexify --input ./image.png --output-dir ./predictions_low` and review the masks side by side. (inferred, check the README)"
 ],
 "agent_prompt": "In the FleXray repo, run `flexify --ensemble --tta-samples 8 --input <image-path> --output-dir <output-dir>` on the target X-ray. Expect the same three .npy arrays plus label_names.json. Verify that the mask arrays are uint8 and that the channel count matches label_names.json.",
 "agents": [
  "any"
 ],
 "difficulty": "Intermediate",
 "time": "30 minutes",
 "basis": "readme",
 "caveat": "The README does not give run-time or accuracy numbers for the modes, so the time cost and quality gain must be measured on your own images.",
 "category": "Research",
 "tags": [
  "Research"
 ],
 "lang": "python",
 "requirements": [
  "Python 3.10 or newer and pip",
  "One or more X-ray images in PNG, JPEG, TIFF, BMP, or DICOM (DICOM needs the dicom extra)",
  "Internet access to download pretrained weights from Hugging Face on first run",
  "For training only: a labeled dataset, and a GPU or CPU for the dry run; the README says training is single-process with at most one GPU",
  "For the MCP use case: an MCP-capable client such as Claude Code or Claude Desktop"
 ],
 "risk": "sensitive",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": false,
 "score": 0.9,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/victorbutoi-flexray/get-higher-quality-masks-with-ensemble-and-tta/",
 "md": "https://dedupedai.com/use-cases/victorbutoi-flexray/get-higher-quality-masks-with-ensemble-and-tta/index.md",
 "disclaimer": "Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked \"Seen in the wild\", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email hello@dedupedai.com and we will look at it promptly.",
 "api": "https://dedupedai.com/api/v1/usecases/victorbutoi-flexray--get-higher-quality-masks-with-ensemble-and-tta.json",
 "api_version": "v1"
}