Dataset Versions
Versions
2024-06-21 9:13am
v32
· 6 months ago
1-12noise
v31
· 6 months ago
1-11blur
v30
· 6 months ago
1-10exploe
v29
· 6 months ago
1-9bright
v28
· 6 months ago
1-8sat
v27
· 6 months ago
1-7hue
v26
· 6 months ago
1-6gray
v25
· 6 months ago
1-5shear
v24
· 6 months ago
1-4rotate15d
v23
· 6 months ago
1-3crop
v22
· 6 months ago
1-2rotate90d
v21
· 6 months ago
1-1flip
v20
· 6 months ago
1-2-1
v18
· 6 months ago
1-2-2
v17
· 6 months ago
1-2-3
v16
· 6 months ago
1-2-4
v15
· 6 months ago
1-2-4ExposureBrightness
v14
· 6 months ago
1-2-3SaturationGrayscale
v13
· 6 months ago
2024-06-20 4:00pm
v12
· 6 months ago
1-2-2ShearRotation
v11
· 6 months ago
1-2-1cropFlip
v10
· 6 months ago
1-2-1crop
v9
· 6 months ago
2024-06-20 3:40pm
v8
· 6 months ago
2024-06-20 2:31pm
v7
· 6 months ago
shearbrightness
v6
· 6 months ago
CropGrayscaleSaturation
v5
· 6 months ago
2024-06-17 4:55pm
v4
· 6 months ago
2024-06-17 4:44pm
v3
· 6 months ago
2024-06-17 4:16pm
v2
· 6 months ago
2024-06-17 3:56pm
v1
· 6 months ago
v9
1-2-1crop
Generated on Jun 20, 2024
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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791 Total Images
View All ImagesDataset Split
Train Set 82%
652Images
Valid Set 12%
93Images
Test Set 6%
46Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Augmentations
Outputs per training example: 2
Flip: Horizontal
Crop: 0% Minimum Zoom, 20% Maximum Zoom