Datasets:
metadata
license: cc-by-4.0
pretty_name: synthetic image-classification dataset
task_categories:
- image-classification
tags:
- image
- image-classification
- synthetic-data
- text-to-image
- image-to-image
- edge-impulse
size_categories:
- n<1K
Synthetic Image-Classification Dataset
Synthetic image-classification dataset generated with stable diffusion (zerogpu_sdxl_turbo) using text-to-image from class names + short descriptions.
Classes
| Label | Images |
|---|---|
background |
20 |
coffee-mug |
20 |
lamp |
20 |
Layout
train/<label>/<label>.<id>.jpg
test/<label>/<label>.<id>.jpg
metadata.csv
Loading
from datasets import load_dataset
ds = load_dataset("imagefolder", data_dir="coffee-lamp")
# or, once pushed to the Hub:
ds = load_dataset("eoinedge/coffee-lamp")
print(ds)
Edge Impulse
Filenames use the label.<id>.jpg convention, so they upload directly:
edge-impulse-uploader --category training train/**/*.jpg
Notes
Synthetic images are a bootstrap for image-classification models. Validate with real captures from the target device's camera before deployment.