Dataset Versions
Versions
2023-11-12 1:25pm
v36
· a year ago
2023-10-23 7:58pm
v35
· a year ago
2023-10-17 4:44pm
v31
· a year ago
2023-10-17 4:12pm
v30
· a year ago
2023-10-16 7:52pm
v29
· a year ago
2023-10-16 7:01pm
v28
· a year ago
2023-10-16 6:32pm
v27
· a year ago
2023-10-16 6:02pm
v26
· a year ago
2023-10-16 5:34pm
v25
· a year ago
2023-10-16 5:14pm
v24
· a year ago
2023-10-16 4:25pm
v23
· a year ago
2023-10-16 3:28pm
v22
· a year ago
2023-10-15 6:17pm
v21
· a year ago
2023-10-15 5:07pm
v20
· a year ago
2023-10-12 4:48pm
v19
· a year ago
2023-10-12 2:21pm
v18
· a year ago
2023-10-11 5:53pm
v17
· a year ago
2023-10-11 5:38pm
v16
· a year ago
2023-10-10 7:47pm
v15
· a year ago
2023-10-10 6:29pm
v14
· a year ago
2023-10-09 8:36pm
v13
· a year ago
55 PIC scaled to 640x640
v12
· a year ago
2023-09-28 5:59pm
v11
· a year ago
2023-09-21 3:49pm
v10
· a year ago
2023-09-21 12:48pm
v9
· a year ago
v35
2023-10-23 7:58pm
Generated on Oct 23, 2023
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.
147 Total Images
View All Images
Dataset Split
Train Set 97%
142Images
Valid Set 3%
5Images
Test Set %
0Images
Preprocessing
Auto-Orient: Applied
Auto-Adjust Contrast: Using Adaptive Equalization
Modify Classes: 0 remapped, 80 dropped
Augmentations
Outputs per training example: 3
Bounding Box: Flip: Horizontal, Vertical
Bounding Box: Brightness: Between -5% and +5%
Bounding Box: Noise: Up to 2% of pixels