Dataset Versions
Versions
2023-12-20 4:06am
v38
· a year ago
2023-12-19 11:42am
v37
· a year ago
2023-12-18 11:45am
v36
· a year ago
2023-12-18 9:30am
v35
· a year ago
2023-12-17 10:35pm
v34
· a year ago
2023-12-17 10:30pm
v33
· a year ago
2023-12-17 9:57pm
v32
· a year ago
2023-12-17 9:42pm
v31
· a year ago
2023-12-17 2:35pm
v30
· a year ago
2023-12-17 2:21pm
v29
· a year ago
2023-12-17 1:31pm
v28
· a year ago
2023-12-17 1:17pm
v27
· a year ago
2023-12-17 12:05pm
v26
· a year ago
2023-12-17 11:51am
v25
· a year ago
2023-12-15 4:31pm
v24
· a year ago
2023-12-15 4:23pm
v23
· a year ago
2023-12-15 1:45pm
v22
· a year ago
2023-12-15 1:33pm
v21
· a year ago
2023-12-15 1:33pm
v20
· a year ago
2023-12-15 1:27pm
v19
· a year ago
2023-12-15 1:07pm
v18
· a year ago
2023-12-15 1:05pm
v17
· a year ago
2023-12-15 1:04pm
v16
· a year ago
2023-12-15 12:47pm
v15
· a year ago
2023-12-13 2:11pm
v14
· a year ago
2023-12-13 1:56pm
v13
· a year ago
2023-12-13 10:09am
v12
· a year ago
2023-12-13 3:48am
v11
· a year ago
2023-12-13 2:44am
v10
· a year ago
2023-12-13 1:44am
v9
· a year ago
2023-12-13 12:17am
v8
· a year ago
2023-12-13 12:15am
v7
· a year ago
2023-12-11 4:18pm
v6
· a year ago
2023-12-10 7:49pm
v5
· a year ago
2023-12-10 6:58pm
v4
· a year ago
2023-12-10 6:34pm
v3
· a year ago
2023-12-10 6:29pm
v2
· a year ago
the good version
v1
· a year ago
v8
2023-12-13 12:17am
Generated on Dec 12, 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.
2824 Total Images
View All Images
Dataset Split
Train Set 87%
2448Images
Valid Set 9%
256Images
Test Set 4%
120Images
Preprocessing
Auto-Orient: Applied
Isolate Objects: Applied
Resize: Fit within 640x640
Auto-Adjust Contrast: Using Contrast Stretching
Tile: 2 rows x 2 columns
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Grayscale: Apply to 25% of images
Blur: Up to 2.5px
Noise: Up to 5% of pixels
Cutout: 10 boxes with 15% size each
Mosaic: Applied
Bounding Box: Flip: Horizontal, Vertical
Bounding Box: Rotation: Between -15° and +15°
Bounding Box: Shear: ±15° Horizontal, ±15° Vertical
Bounding Box: Brightness: Between -25% and +25%
Bounding Box: Exposure: Between -25% and +25%
Bounding Box: Blur: Up to 2.5px
Bounding Box: Noise: Up to 5% of pixels