sirvival87/cannabis-diagnose-dataset — explained in plain English
Analysis updated 2026-05-18
Build a plant health diagnosis tool or app using structured data on cannabis growing problems.
Look up symptoms, causes, and affected plant parts for common cultivation issues.
Train or test a classification model on labeled categories of plant deficiencies and diseases.
| sirvival87/cannabis-diagnose-dataset | 0labs-in/vision-link | 1038lab/agnes-ai | |
|---|---|---|---|
| Stars | 4 | 4 | 4 |
| Language | — | TypeScript | Python |
| Setup difficulty | easy | moderate | easy |
| Complexity | 1/5 | 3/5 | 2/5 |
| Audience | general | developer | vibe coder |
Figures from each repo's GitHub metadata at analysis time.
This project is an open dataset that catalogs common problems cannabis growers run into, such as nutrient deficiencies, pests, diseases, and environmental stress. It is maintained by MeinePlantage.de, a German language cannabis growing information site. The dataset covers 79 distinct diagnoses spread across 12 categories, including nutrient issues, pests, fungal and bacterial diseases, pH and EC problems, watering issues, root problems, light stress, temperature and humidity problems, training issues, and flowering or harvest problems. Each entry includes a German and English name, its category, a short description, which parts of the plant are affected, the typical growth phase it occurs in, the first symptoms a grower would notice, and common causes. The data is provided in two formats: a full JSON file and a full CSV file, along with a separate file that maps category IDs to their German and English names. It is worth noting what this dataset does not include. It does not contain remedies, long-term solutions, or the logic needed to tell similar looking problems apart, and it does not include severity ratings. Those more detailed features are part of a separate, full diagnosis system and an interactive wizard hosted on the maintainer's website, which this public dataset only partially represents. The dataset is released under the CC BY 4.0 license, which means it can be used, shared, and adapted for any purpose, including commercial use, as long as credit is given and a link back to the source is included. The README notes that the data is updated periodically and may not always match the very latest version of the maintainer's live database.
An open dataset of 79 common cannabis growing problems such as deficiencies, pests, and diseases, provided as JSON and CSV files.
Free to use, share, and adapt for any purpose including commercial use, as long as credit is given and a link back is included.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly general.
This repo across BitVibe Labs
double-check against the repo, no cap.