Dataset Versions
Versions
2024-02-07 10:09pm
v20
· 10 months ago
2024-02-07 10:08pm
v19
· 10 months ago
2024-02-07 12:27pm
v18
· 10 months ago
2024-02-07 12:26pm
v17
· 10 months ago
2024-02-07 12:23pm
v16
· 10 months ago
2024-02-07 12:22pm
v15
· 10 months ago
2024-02-07 12:19pm
v14
· 10 months ago
2024-02-07 12:18pm
v13
· 10 months ago
2024-02-07 12:16pm
v12
· 10 months ago
2024-02-07 12:13pm
v11
· 10 months ago
2024-02-07 12:09pm
v10
· 10 months ago
2024-02-07 12:08pm
v9
· 10 months ago
2024-02-07 12:05pm
v8
· 10 months ago
2024-02-07 11:55am
v7
· 10 months ago
2024-02-07 11:50am
v6
· 10 months ago
2024-02-07 11:48am
v5
· 10 months ago
2024-02-07 11:43am
v4
· 10 months ago
2024-02-07 11:12am
v3
· 10 months ago
2024-02-07 8:28am
v2
· 10 months ago
2024-02-07 12:58am
v1
· 10 months ago
v2
2024-02-07 8:28am
Generated on Feb 7, 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.
Other Formats
Choose another format.
6052 Total Images
View All ImagesDataset Split
Train Set 100%
6036Images
Valid Set 0%
4Images
Test Set 0%
12Images
Preprocessing
Auto-Orient: Applied
Static Crop: 25-75% Horizontal Region, 25-75% Vertical Region
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Adaptive Equalization
Grayscale: Applied
Tile: 2 rows x 2 columns
Augmentations
Outputs per training example: 3
Flip: Horizontal
Rotation: Between -15° and +15°
Hue: Between -15° and +15°
Saturation: Between -25% and +25%
Exposure: Between -10% and +10%
Blur: Up to 2.5px
Noise: Up to 0.1% of pixels