PKLot Dataset 640

Export Created

4 years ago

2021-01-05 6:16pm

Export Size

12416 images

Annotations

spaces

Available Download Formats

COCO JSON annotations are used with EfficientDet Pytorch and Detectron 2.

COCO-MMDetection

COCO-MMDetection JSON annotations are used with MMDetection.

CreateML JSON format is used with Apple's CreateML and Turi Create tools.

PaliGemma JSONL

PaliGemma format is used with Google's Multimodal Vision Model.

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).

Scaled YOLOv4 TXT annotations used with Scaled-YOLOv4.

YOLOv5 Oriented Bounding Boxes TXT annotations used with YOLOv5-OBB.

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.

YOLOv8 Oriented Bounding Boxes TXT annotations used with YOLOv8-OBB.

TXT annotations and YAML config used with YOLOv9.

TXT annotations and YAML config used with YOLOv11.

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.

Multiclass Classification

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.

Tensorflow TFRecord

TFRecord binary format used for both Tensorflow 1.5 and Tensorflow 2.0 Object Detection models.

Preview

Train/Test Split

Your images are split at upload time. Learn more.

Preprocessing Options

Applied to all images in dataset

Auto-Orient

Resize

Stretch to 640x640

Preprocessing can decrease training time and increase inference speed. Learn more on our blog.

Augmentation Options

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.