Sensitive Content Dataset
v2
2024-09-11 11:53am
Generated on Sep 11, 2024
Popular Download Formats
YOLOv9
TXT annotations and YAML config used with YOLOv9.
YOLOv8
TXT annotations and YAML config used with YOLOv8.
YOLOv5
TXT annotations and YAML config used with YOLOv5.
YOLOv7
TXT annotations and YAML config used with YOLOv7.
COCO JSON
COCO JSON annotations are used with EfficientDet Pytorch and Detectron 2.
YOLO Darknet
Darknet TXT annotations used with YOLO Darknet (both v3 and v4) and YOLOv3 PyTorch.
Pascal VOC XML
Common XML annotation format for local data munging (pioneered by ImageNet).
TFRecord
TFRecord binary format used for both Tensorflow 1.5 and Tensorflow 2.0 Object Detection models.
PaliGemma
PaliGemma JSONL format used for fine-tuning PaliGemma, Google's open multimodal vision model.
CreateML JSON
CreateML JSON format is used with Apple's CreateML and Turi Create tools.
Other Formats
Choose another format.
5002 Total Images
View All Images
Dataset Split
Train Set 87%
4338Images
Valid Set 8%
411Images
Test Set 5%
253Images
Preprocessing
Auto-Orient: Applied
Static Crop: 25-75% Horizontal Region, 25-75% Vertical Region
Resize: Stretch to 640x640
Tile: 2 rows x 2 columns
Filter Null: Require all images to contain annotations.
Augmentations
Outputs per training example: 3
90° Rotate: Clockwise, Counter-Clockwise
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Rotation: Between -15° and +15°
Shear: ±15° Horizontal, ±15° Vertical
Grayscale: Apply to 16% of images
Blur: Up to 2.5px
Noise: Up to 1.92% of pixels
Cutout: 7 boxes with 16% size each
Bounding Box: Shear: ±12° Horizontal, ±12° Vertical
Bounding Box: Blur: Up to 2.5px
Bounding Box: Noise: Up to 0.34% of pixels