Dataset Versions
Versions
2024-11-10 5:06am
v30
· a day ago
2024-10-15 1:38pm
v29
· a month ago
2024-10-05 8:44am
v28
· a month ago
2024-10-04 4:09am
v27
· a month ago
2024-09-08 2:10am
v26
· 2 months ago
2024-07-30 7:05am
v25
· 3 months ago
2024-07-19 8:21am
v24
· 4 months ago
2024-07-19 7:53am
v23
· 4 months ago
2024-06-25 1:33am
v22
· 5 months ago
2024-06-25 1:25am
v21
· 5 months ago
2024-06-25 1:19am
v20
· 5 months ago
2024-06-25 12:53am
v19
· 5 months ago
2024-06-24 11:18am
v18
· 5 months ago
2024-04-26 1:27pm
v17
· 7 months ago
sehat 972
v16
· 8 months ago
all class 972
v15
· 8 months ago
2024-02-27 2:30pm
v14
· 8 months ago
520 data 27feb2024
v13
· 8 months ago
251 original data
v12
· 9 months ago
2024-01-31 4:57pm
v11
· 9 months ago
2024-01-17 4:16pm
v10
· 10 months ago
2024-01-12 3:01pm
v9
· 10 months ago
2024-01-10 8:49am
v8
· 10 months ago
2024-01-08 10:00am
v7
· 10 months ago
2024-01-05 4:04pm
v6
· 10 months ago
data asli 2023-12-18 1-50pm
v5
· a year ago
2023-12-01 4:44pm
v4
· a year ago
2023-05-10 2:06pm
v3
· 2 years ago
2023-05-09 10:47am
v2
· 2 years ago
2023-01-11 8:20am
v1
· 2 years ago
v8
2024-01-10 8:49am
Generated on Jan 10, 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.
1092 Total Images
View All Images
Dataset Split
Train Set 92%
1008Images
Valid Set 4%
42Images
Test Set 4%
42Images
Preprocessing
Auto-Adjust Contrast: Using Contrast Stretching
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Shear: ±10° Horizontal, ±10° Vertical
Saturation: Between -19% and +19%
Brightness: Between -15% and +15%
Exposure: Between -15% and +15%