Dataset Versions
Versions
2024-05-05 11:24am
v30
· 7 months ago
2024-05-05 11:24am
v29
· 7 months ago
2024-05-05 11:24am
v28
· 7 months ago
2024-05-05 10:08am
v27
· 7 months ago
2024-05-03 12:01pm
v26
· 7 months ago
2024-04-29 11:45am
v25
· 7 months ago
2024-04-29 11:45am
v24
· 7 months ago
2024-04-29 11:45am
v23
· 7 months ago
2024-04-29 11:45am
v22
· 7 months ago
2024-04-29 11:45am
v21
· 7 months ago
2024-04-29 11:45am
v20
· 7 months ago
2024-04-29 11:24am
v19
· 7 months ago
2024-04-28 1:46am
v18
· 7 months ago
2024-04-28 12:31am
v17
· 7 months ago
2024-04-28 12:25am
v16
· 7 months ago
2024-04-28 12:21am
v15
· 7 months ago
2024-04-27 9:37pm
v14
· 7 months ago
2024-04-27 9:35pm
v13
· 7 months ago
2024-04-27 9:34pm
v12
· 7 months ago
2024-04-27 5:10am
v11
· 7 months ago
2024-04-27 4:35am
v10
· 7 months ago
2024-04-27 1:16pm
v9
· 7 months ago
2024-04-27 11:23am
v8
· 7 months ago
2024-04-25 5:49am
v7
· 7 months ago
2024-04-25 5:37am
v6
· 7 months ago
2024-04-24 11:09pm
v5
· 7 months ago
2024-04-24 11:01pm
v4
· 7 months ago
2024-04-24 10:56pm
v3
· 7 months ago
2024-04-24 10:54pm
v2
· 7 months ago
2024-04-24 10:53pm
v1
· 7 months ago
v23
2024-04-29 11:45am
Generated on Apr 29, 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.
988 Total Images
View All Images
Dataset Split
Train Set 87%
864Images
Valid Set 9%
84Images
Test Set 4%
40Images
Preprocessing
Auto-Orient: Applied
Static Crop: 25-75% Horizontal Region, 25-75% Vertical Region
Resize: Stretch to 640x640
Grayscale: Applied
Tile: 2 rows x 2 columns
Augmentations
Outputs per training example: 3
Flip: Horizontal
90° Rotate: Clockwise, Counter-Clockwise
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Rotation: Between -15° and +15°
Shear: ±10° Horizontal, ±10° Vertical
Grayscale: Apply to 15% of images
Hue: Between -23° and +23°
Saturation: Between -25% and +25%
Brightness: Between -15% and +15%
Exposure: Between -10% and +10%
Blur: Up to 2.5px
Noise: Up to 0.1% of pixels