Synthetic Fruit Dataset raw
3 years ago
Available Download Formats
COCO JSON annotations are used with EfficientDet Pytorch and Detectron 2.
CreateML JSON format is used with Apple's CreateML and Turi Create tools.
Pascal VOC XML
Common XML annotation format for local data munging (pioneered by ImageNet).
YOLO Darknet TXT
Darknet TXT annotations used with YOLO Darknet (both v3 and v4) and YOLOv3 PyTorch.
YOLO v3 Keras TXT
TXT annotations used with YOLOv3 Keras.
YOLO v4 PyTorch
Darknet TXT annotations used with YOLOv4 PyTorch (deprecated).
MT-YOLOv6 TXT annotations used with meituan/YOLOv6.
YOLO v5 PyTorch
TXT annotations and YAML config used with YOLOv5.
YOLO v7 PyTorch
TXT annotations and YAML config used with YOLOv7.
TXT annotations and YAML config used with YOLOv8.
Tensorflow Object Detection CSV
CSV format used with Tensorflow (usually converted before training so you probably want to export as a TFRecord instead unless you need to inspect the human-readable CSV).
RetinaNet Keras CSV
A custom CSV format used by Keras implementation of RetinaNet.
Converts your object detection dataset into a classification dataset CSV.
OpenAI CLIP Classification
Converts your object detection dataset a classification dataset for use with OpenAI CLIP.
TFRecord binary format used for both Tensorflow 1.5 and Tensorflow 2.0 Object Detection models.
Your images are split at upload time. Learn more.
Applied to all images in dataset
No preprocessing steps were applied.
Preprocessing can decrease training time and increase inference speed. Learn more on our blog.
Randomly applied to images in your training set
No augmentation steps were applied.
Augmentations create new training examples for your model to learn from. Learn more on our blog.