CropGAN
UC Davis Plant AI & Biophysics Lab
Every new field, season or camera seems to need fresh labelled images, and labelling is the bottleneck. This is code for a model that generates labelled crop imagery from existing pictures so you can train detectors without annotating again.
QUICK INFO
SOLUTION TYPE
Models, data & tools
TECHNOLOGY CATEGORY
Models & fine-tunes
AREA OF WORK
Seed genetics & breeding
ACCESS
Free
DEPLOYMENT
Self-hosted / on-premise · Downloadable
SOURCE REVIEWED
August 23, 2026
What it helps with
- Generate labelled crop images
- Train a crop detector without labelling again
- Reuse labels across fields and seasons
- New camera means new labels problem
- Code for generating crop imagery
Scope & audience
WHO IT'S FOR
Scientist / researcher · Input manufacturer (seed / chem / fert)
AREA OF WORK
Seed genetics & breeding
COMMODITY / SCOPE
Cross-commodity
Access & technical details
ACCESS
Anyone can get it
INTERFACE
Code repository
DEPLOYMENT
You run it yourself
LANGUAGES
Not stated by provider
Featured media
Source information
This listing was compiled from publicly available source material. Verify current details with the provider.
PROVIDER DOCUMENTATION
Reviewed August 2026
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