Dataset Versions
Versions
2023-02-28 10:50pm
v31
· 2 years ago
2023-02-25 11:30pm
v30
· 2 years ago
2023-02-18 6:25pm
v29
· 2 years ago
2023-02-18 4:55pm
v28
· 2 years ago
2023-02-09 10:34pm
v27
· 2 years ago
2023-02-09 10:31pm
v26
· 2 years ago
2023-02-09 4:42pm
v25
· 2 years ago
2023-02-09 4:41pm
v24
· 2 years ago
2022-10-20 3:26pm
v23
· 2 years ago
2022-10-19 8:55am
v22
· 2 years ago
2022-10-19 8:55am
v21
· 2 years ago
2022-10-19 8:55am
v20
· 2 years ago
2022-10-19 8:54am
v19
· 2 years ago
2022-10-19 8:54am
v18
· 2 years ago
2022-10-19 8:54am
v17
· 2 years ago
2022-10-19 8:54am
v16
· 2 years ago
2022-10-19 8:31am
v14
· 2 years ago
2022-10-19 8:31am
v13
· 2 years ago
2022-10-19 8:30am
v12
· 2 years ago
2022-10-19 8:30am
v11
· 2 years ago
2022-10-19 8:30am
v10
· 2 years ago
2022-10-19 8:30am
v9
· 2 years ago
2022-10-19 8:30am
v8
· 2 years ago
v12
2022-10-19 8:30am
Generated on Oct 19, 2022
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.
165 Total Images
View All Images
Dataset Split
Train Set 87%
144Images
Valid Set 8%
13Images
Test Set 5%
8Images
Preprocessing
Resize: Stretch to 416x416
Auto-Adjust Contrast: Using Adaptive Equalization
Augmentations
Outputs per training example: 3
Grayscale: Apply to 25% of images
Brightness: Between -25% and +25%
Blur: Up to 10px
Noise: Up to 5% of pixels