SmartFarmingLab/field_dataset_survey
A curated collection of 45 high-quality RGB image datasets for computer vision in agriculture. Features datasets for weed detection, disease identification, and crop monitoring, focusing on natural field scenes. Part of our GIL 2025 survey paper.
This collection helps agricultural researchers and technology developers find high-quality image data to train AI models for smart farming applications. It provides access information to 45 curated datasets, primarily RGB images of natural field scenes. Farmers, agronomists, and agricultural technology companies can use these datasets to build tools for tasks like identifying weeds, detecting crop diseases, or monitoring plant growth.
Use this if you need reliable, real-world image data of plants in fields to develop or test AI systems for agricultural tasks.
Not ideal if you're looking for satellite imagery, drone footage with non-RGB sensors, or datasets focused on laboratory or greenhouse plant images.
Stars
14
Forks
1
Language
TeX
License
—
Category
Last pushed
Jan 07, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/computer-vision/SmartFarmingLab/field_dataset_survey"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
cropandweed/cropandweed-dataset
[WACV 2023] Information and scripts for the CropAndWeed Dataset
josemenber/image-based-crop-anomaly-detection
A Convolutional Neural Network approach for image-based anomaly detection in smart agriculture
cepdnaclk/e16-4yp-Identification-of-Weeds-in-broadcasted-Paddy-fields-using-multispectral-UAV-images
Develop a model to Identify paddy crops and weeds by images taken from UAV (unmanned aerial...