foodvision-bench
importedsoftware/foodvision-bench
Open reproducible benchmarks for food-image recognition models and APIs.
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- active
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- unknown
- Documentation
- unknown
- Tags
- benchmark · calorie-estimation · clip · computer-vision · food-recognition · mape · nutrition · reproducibility
- Regulatory
- unknown
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- NutriGofood-recognition · nutrition
🥗 AI Nutrition Assistant / AI 智能营养师 — Photo food recognition, AI nutrition analysis & personalized dietary advice. 拍照识别食物、AI 营养分析、个性化膳食建议的全栈应用。
- MKTY-Systemclip
[AI LLM + Medicine and Healthcare] Minh Khoe Tue Y Smart Healthcare System【人工智能大模型与医疗保健毕业设计项目】明康慧医(MKTY)智慧医疗系统)
- ClawBioreproducibility
🦖 ClawBio - The first bioinformatics-native AI agent skill library. Local-first. Reproducible. Open. Free.
- figtracerreproducibility
Plain-text, git-tracked lab notebook for reproducible bioinformatics — keeps figures in your Markdown notes in sync with the R & Python code that made them, when the notes live outside the analysis.…
- hu-neuro-pipelinereproducibility
Single trial EEG pipeline at the Abdel Rahman Lab for Neurocognitive Psychology, Humboldt-Universität zu Berlin
- labwrightreproducibility
Labwright — the AI bench copilot that gets your numbers right. Verifiable LLM-driven wet-lab experimental design: the model proposes, deterministic calculators compute and verify every number.…
- api.github.com/repos/foodvision-bench/foodvision-benchretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2026-08-05, 10 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/22.json→ .entries["foodvision-bench"]
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