Dataset Versions
Versions
Primer proyecto
v34
· 3 years ago
Proyecto 1
v33
· 3 years ago
No daug 1664
v32
· 3 years ago
Trainset normal daug 1664
v31
· 3 years ago
2022-06-06 1:43pm
v30
· 3 years ago
Trainset bbox daug 1664
v29
· 3 years ago
Validset no daug 416 22 img
v28
· 3 years ago
trainset normal daug 416 88 img
v27
· 3 years ago
trainset bbox daug 416 88 img
v26
· 3 years ago
Trainset Bbox Daug 1600 88 img
v25
· 3 years ago
Trainset normal Daug 1600 88 img
v24
· 3 years ago
Dataset normal Daug 1600 72 img
v23
· 3 years ago
Train set no data aug split by 4 416
v22
· 3 years ago
Train set split by 4 416 Normal DAug No noise
v21
· 3 years ago
Dataset split by 4 416 Normal DAug NO noise
v20
· 3 years ago
Dataset split by 4 416 Normal DAug
v19
· 3 years ago
Dataset split by 4 All Bbox 416
v18
· 3 years ago
Dataset split by 4 All Bbox
v16
· 3 years ago
Dataset 220 img All Bbox
v15
· 3 years ago
Dataset NoDAug 1664 22 img
v13
· 3 years ago
Dataset Aug All Bbox 1664
v12
· 3 years ago
Dataset Aug All Bbox 1600
v11
· 3 years ago
Dataset Aug Rotate 1600
v10
· 3 years ago
Dataset Aug Crop 1600
v9
· 3 years ago
Dataset Aug 90 rotate 1600
v8
· 3 years ago
D N Aug 1600 22img
v7
· 3 years ago
2022-04-04 2:11pm
v6
· 3 years ago
Dataset Aug Flip 1600
v5
· 3 years ago
Dataset No DAug 1600
v4
· 3 years ago
Dataset No DAug
v3
· 3 years ago
2022-04-01 7:53pm
v2
· 3 years ago
2022-04-01 7:52pm
v1
· 3 years ago
v19
Dataset split by 4 416 Normal DAug
Generated on Apr 19, 2022
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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928 Total Images
View All Images
Dataset Split
Train Set 93%
864Images
Valid Set 7%
64Images
Test Set %
0Images
Preprocessing
Resize: Stretch to 416x416
Tile: 4 rows x 4 columns
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise
Crop: 15% Minimum Zoom, 35% Maximum Zoom
Rotation: Between -30° and +30°
Shear: ±15° Horizontal, ±15° Vertical
Brightness: Between -30% and +30%
Exposure: Between -25% and +25%
Blur: Up to 2.25px
Noise: Up to 2% of pixels