Dataset Versions
Versions
2023-04-30 4:28pm
v13
· 2 years ago
batch8
v12
· 2 years ago
2023-04-29 6:37pm
v11
· 2 years ago
200 epochs
v10
· 2 years ago
yolox-img1024
v7
· 2 years ago
yolom-batch16-img1024-epochs100
v6
· 2 years ago
yolon-batch16-img640-epochs100
v5
· 2 years ago
yolos-batch16-img640-epochs100
v4
· 2 years ago
yolom-batch16-img640-epochs100
v3
· 2 years ago
yolol-batch16-img640-epochs100
v2
· 2 years ago
yolox- batch-16- img-640- epochs-100
v1
· 2 years ago
v3
yolom-batch16-img640-epochs100
Generated on Apr 18, 2023
Popular Download Formats
YOLOv11
TXT annotations and YAML config used with YOLOv11.
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.
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1106 Total Images
View All Images
Dataset Split
Train Set 87%
963Images
Valid Set 8%
92Images
Test Set 5%
51Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Histogram Equalization
Modify Classes: 2 remapped, 0 dropped
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Rotation: Between -15° and +15°
Grayscale: Apply to 25% of images
Saturation: Between -40% and +40%
Brightness: Between -25% and +25%
Exposure: Between -25% and +25%
Blur: Up to 7px
Noise: Up to 10% of pixels
Cutout: 5 boxes with 15% size each
Mosaic: Applied