Dataset Versions
Versions
2024-09-02 10:25am
v39
· 3 months ago
2024-08-31 5:39pm
v38
· 3 months ago
2024-08-31 5:38pm
v37
· 3 months ago
2024-08-31 4:17pm
v36
· 3 months ago
2024-08-31 3:30pm
v35
· 3 months ago
2024-08-31 3:22pm
v34
· 3 months ago
2024-08-31 3:20pm
v33
· 3 months ago
2024-08-31 8:21am
v32
· 3 months ago
2024-08-31 8:19am
v31
· 3 months ago
2024-08-31 7:28am
v30
· 3 months ago
2024-08-27 1:21pm
v29
· 3 months ago
2024-08-20 1:47pm
v28
· 3 months ago
2024-08-15 12:47pm
v26
· 3 months ago
2024-08-15 8:37am
v25
· 3 months ago
2024-08-15 8:25am
v24
· 3 months ago
2024-08-14 10:07pm
v23
· 3 months ago
2024-08-14 9:25pm
v22
· 3 months ago
2024-08-14 8:25pm
v20
· 3 months ago
2024-08-14 8:12pm
v19
· 3 months ago
2024-08-14 7:51pm
v17
· 3 months ago
2024-08-14 7:10pm
v16
· 3 months ago
2024-08-14 6:45pm
v15
· 3 months ago
2024-08-14 6:01pm
v14
· 3 months ago
2024-08-14 5:40pm
v13
· 3 months ago
2024-08-14 5:28pm
v12
· 3 months ago
2024-08-14 11:27am
v11
· 3 months ago
Trial1
v7
· 3 months ago
v26
2024-08-15 12:47pm
Generated on Aug 15, 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.
800 Total Images
View All Images
Dataset Split
Train Set 90%
720Images
Valid Set 6%
48Images
Test Set 4%
32Images
Preprocessing
Auto-Orient: Applied
Resize: Fit within 640x640
Auto-Adjust Contrast: Using Contrast Stretching
Tile: 4 rows x 4 columns
Augmentations
Outputs per training example: 3
Rotation: Between -15° and +15°
Shear: ±10° Horizontal, ±10° Vertical
Hue: Between -20° and +20°
Saturation: Between -25% and +25%
Brightness: Between -20% and +20%
Blur: Up to 2.5px