Dataset Versions
Versions
2024-06-07 10:03am
v20
· 6 months ago
2024-06-07 9:48am
v19
· 6 months ago
2024-05-29 9:52pm
v18
· 6 months ago
2024-05-29 8:18pm
v17
· 6 months ago
2024-05-28 8:34pm
v16
· 6 months ago
2024-05-24 7:27pm
v15
· 6 months ago
2024-05-24 11:12am
v14
· 6 months ago
2024-05-24 1:30am
v13
· 6 months ago
2024-05-24 12:03am
v12
· 6 months ago
2024-05-23 10:30pm
v11
· 6 months ago
2024-05-23 9:58pm
v10
· 6 months ago
2024-05-23 7:30pm
v9
· 6 months ago
2024-05-23 3:47pm
v8
· 6 months ago
2024-05-23 3:37pm
v7
· 6 months ago
2024-05-23 1:18pm
v6
· 6 months ago
2024-05-23 1:08pm
v5
· 6 months ago
2024-05-18 10:34am
v4
· 6 months ago
2024-04-18 8:57am
v3
· 7 months ago
2024-04-18 8:48am
v2
· 7 months ago
2023-10-20 10:10pm
v1
· a year ago
v5
2024-05-23 1:08pm
Generated on May 23, 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.
838 Total Images
View All Images
Dataset Split
Train Set 86%
720Images
Valid Set 9%
76Images
Test Set 5%
42Images
Preprocessing
Auto-Orient: Applied
Isolate Objects: Applied
Static Crop: 25-75% Horizontal Region, 25-87% Vertical Region
Dynamic Crop: Class: Burung Branjangan
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Histogram Equalization
Grayscale: Applied
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
Crop: 0% Minimum Zoom, 30% Maximum Zoom
Shear: ±12° Horizontal, ±14° Vertical
Grayscale: Apply to 16% of images
Blur: Up to 2.5px
Bounding Box: 90° Rotate: Clockwise, Counter-Clockwise
Bounding Box: Noise: Up to 0.1% of pixels