{
 "schema_version": 1,
 "generated": "2026-10-20",
 "id": "psrben-visionhope--evaluate-visionhope-checkpoint-on-benchmark",
 "repo": "PSRben/VisionHOPE",
 "repo_url": "https://github.com/PSRben/VisionHOPE",
 "repo_slug": "psrben-visionhope",
 "title": "Check Vision HOPE accuracy on ImageNet, COCO, or ADE20K",
 "page_title": "How to check Vision HOPE accuracy on ImageNet, COCO, or ADE20K with Vision HOPE",
 "summary": "Run the matching test script on your downloaded dataset to measure a released checkpoint.",
 "who": "A researcher who wants to confirm reported results on a local copy of ImageNet-1K, COCO 2017, or ADE20K before building on the checkpoint.",
 "problem": "Published numbers are only useful if you can reproduce them on your own dataset copy and hardware.",
 "outcome": "You get the evaluation output from the matching test script for the checkpoint and dataset you chose.",
 "steps": [
  "Install the environment for your task: `python -m pip install -r requirements/classification.txt` for ImageNet, or the detection or segmentation requirements for COCO or ADE20K.",
  "Download the checkpoint with `hf download PSRben/VisionHOPE visionhope_small.pth --local-dir weights` or the matching COCO or ADE20K filename.",
  "Arrange your dataset as `data/imagenet/`, `data/coco/`, or `data/ade20k/`, or set `--data-root` to its location.",
  "Run `CUDA_VISIBLE_DEVICES=0 bash scripts/test/visionhope_small.sh --data-root data/imagenet --checkpoint weights/visionhope_small.pth` for ImageNet. (inferred, check the README)",
  "Compare the printed metrics with the Main results table in the README and note any gap caused by precision or preprocessing settings."
 ],
 "agent_prompt": "Using the VisionHOPE repo (PSRben/VisionHOPE), run scripts/test/visionhope_small.sh on the dataset at <dataset path> with checkpoint weights/visionhope_small.pth. Report the evaluation metrics and compare them with the Main results section of the README. Verify that the dataset folders match the layout in the Datasets section before the run starts.",
 "agents": [
  "any"
 ],
 "difficulty": "Intermediate",
 "time": "2 hours",
 "basis": "readme",
 "caveat": "You must download ImageNet-1K, COCO 2017, or ADE20K from their official websites yourself, and those downloads are large and not included in the repo.",
 "category": "Research",
 "tags": [
  "Research"
 ],
 "lang": "python",
 "requirements": [
  "Linux with an NVIDIA GPU, the CUDA toolkit (including nvcc), and a C++ compiler",
  "Python 3.10 (recommended) and CUDA 12.1",
  "Pretrained checkpoint from Hugging Face, GitHub Releases, or Baidu Netdisk",
  "For dataset tasks: ImageNet-1K, COCO 2017, or ADE20K downloaded from their official websites"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": false,
 "score": 0.7,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/psrben-visionhope/evaluate-visionhope-checkpoint-on-benchmark/",
 "md": "https://dedupedai.com/use-cases/psrben-visionhope/evaluate-visionhope-checkpoint-on-benchmark/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/psrben-visionhope--evaluate-visionhope-checkpoint-on-benchmark.json",
 "api_version": "v1"
}