Dataset Versions
Versions
2024-11-09 6:12pm
v25
· 24 days ago
2024-09-14 5:44am
v24
· 3 months ago
2024-09-14 5:26am
v23
· 3 months ago
2024-09-14 5:24am
v22
· 3 months ago
2024-09-02 9:14pm
v21
· 3 months ago
Paper_pieces
v20
· 4 months ago
cardboard_LDPE
v19
· 4 months ago
small_piece_bottle
v18
· 4 months ago
yolov9
v17
· 4 months ago
greyscale
v16
· 4 months ago
greyscale
v12
· 4 months ago
2024-08-06 6:15am
v11
· 4 months ago
2024-08-03 9:47pm
v10
· 4 months ago
2024-08-03 9:45pm
v9
· 4 months ago
2024-07-28 5:53am
v8
· 4 months ago
2024-07-27 9:28pm
v7
· 4 months ago
2024-07-27 4:48am
v6
· 4 months ago
2024-07-26 6:57am
v5
· 4 months ago
2024-07-26 2:12am
v4
· 4 months ago
2024-07-25 3:55am
v3
· 4 months ago
2024-07-10 9:20pm
v2
· 5 months ago
2024-07-05 7:49am
v1
· 5 months ago
v10
2024-08-03 9:47pm
Generated on Aug 3, 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.
1186 Total Images
View All Images
Dataset Split
Train Set 88%
1041Images
Valid Set 9%
101Images
Test Set 4%
44Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Filter Null: Require all images to contain annotations.
Filter by Tag: 0 required, 1 dropped
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Rotation: Between -15° and +15°
Shear: ±10° Horizontal, ±10° Vertical
Cutout: 3 boxes with 8% size each