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romaine

Dataset Metadata

Metadata Value
Classes romaine
Machine Learning Task object_detection
Agricultural Task crops_detection
Location USA
Sensor Modality RGB
Platform ground
Input Data Format JPG
Annotation Format coco_json
Number of Images 500

Dataset

romaine_annotated

Quick start

You can easily open the dataset in any application compatible with the COCO format. Here is an example of how to do that using FiftyOne.

  • Download the dataset, and extract the archive.
wget "https://ghaipublic.s3.us-west-2.amazonaws.com/datasets/romaine_annotated.zip"
unzip romaine_annotated.zip
  • You should end up with a folder structure similar to this one:
Project/
|--romaine/
|  |--coco.json
|  |--image1.jpg
|  |--...
  • Create a virtual environment, and install the Python FiftyOne package.
python -m venv .venv
source .venv/bin/activate
python -m pip install fiftyone
  • Create and run the following script.
import fiftyone as fo
import fiftyone.zoo as foz


dataset = fo.Dataset.from_dir(
    dataset_type=fo.types.COCODetectionDataset,
    data_path="./romaine/",
    labels_path="./romaine/coco.json",
    include_id=True,
)

# Verify that the class list for our dataset was imported
print(dataset.default_classes)
print(dataset)

session = fo.launch_app(dataset)
session.wait()