batik Dataset
Versions
6 nov-2 bounding box flip hapus
v27
· a year ago
6 nov-1 ver22 valid 105
v26
· a year ago
5 nov-4 ver 22 - valid nambah jd 113
v25
· a year ago
5 nov-3 ver23 - rotation
v24
· a year ago
5 nov-2 ver22-bounding box rotate 90
v23
· a year ago
5 nov-1 versi bounding box flip
v22
· a year ago
4 nov-6 versi nambah valid
v21
· a year ago
4 nov-5 versi v18 tambah shear-crop
v20
· a year ago
4 nov -4 versi v18 tambah augmentasi exposure
v19
· a year ago
4 nov -3 versi v11 - tambah augmentasi brighness-shear
v18
· a year ago
4 nov -2 versi valid v11
v17
· a year ago
4 nov -1
v16
· a year ago
3 nov versi valid 150
v15
· a year ago
3 nov versi dataset full- valid 104
v14
· a year ago
1 nov anotate v2 -2-
v13
· a year ago
1 nov anotate v2
v12
· a year ago
31 okt dah kelar semua anotate v1
v11
· a year ago
27 okt blm fix
v10
· a year ago
revisi 26 okt part 2
v9
· a year ago
revisi 26 okt
v7
· a year ago
revisi 25 okt -benerin annotate blm fix semua-
v6
· a year ago
reg
v5
· a year ago
21okt
v4
· a year ago
2023-10-19 7:16pm
v3
· a year ago
2023-10-19 4:02pm
v2
· a year ago
2023-09-14 3:29pm
v1
· a year ago
v11
31 okt dah kelar semua anotate v1
Generated on Oct 31, 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.
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591 Total Images
View All Images
Dataset Split
Train Set 88%
518Images
Valid Set 12%
73Images
Test Set %
0Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Adaptive Equalization
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Saturation: Between -53% and +53%