Dataset Versions
Versions
2024-07-31 9:22am
v26
· 4 months ago
2023-10-24 9-52am all s 5e
v25
· a year ago
2023-10-16 4-56pm testModelBudCell_10e n
v23
· a year ago
2023-10-16 4-55pm testModelBudCell_10e s
v22
· a year ago
2023-10-16 4-54pm testModelBudCell_10e m
v21
· a year ago
2023-10-16 4-41pm testModelBudBox_10e n
v20
· a year ago
2023-10-16 4-39pm testModelBudBox_10e s
v19
· a year ago
2023-10-16 4-26pm testModelBudBox_10e m
v18
· a year ago
2023-10-16 1:36pm
v17
· a year ago
2023-09-26 2-28pm budCell s 20e
v16
· a year ago
2023-09-26 1-49pm budBox m 25e
v15
· a year ago
2023-09-06 11-09am bud m 25e
v14
· a year ago
2023-09-06 10-37am buddingz m 20e
v13
· a year ago
2023-09-06 9-28am all m 25e
v12
· a year ago
2023-09-06 9-07am all m 15e
v11
· a year ago
2023-09-05 1-59pm cell-budcell
v10
· a year ago
2023-09-05 9-13am s 30e
v9
· a year ago
2023-09-05 9-03am m 20e
v8
· a year ago
2023-09-05 8-54am m 10e
v7
· a year ago
2023-09-04 2:15pm
v5
· a year ago
2023-09-04 1:54pm
v3
· a year ago
2023-09-01 2:51pm
v1
· a year ago
v16
2023-09-26 2-28pm budCell s 20e
Generated on Sep 26, 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.
1296 Total Images
View All Images
Dataset Split
Train Set 88%
1136Images
Valid Set 8%
107Images
Test Set 4%
53Images
Preprocessing
Auto-Orient: Applied
Static Crop: 10-90% Horizontal Region, 10-90% Vertical Region
Resize: Stretch to 800x800
Modify Classes: 1 remapped, 4 dropped
Augmentations
Outputs per training example: 3
90° Rotate: Clockwise, Counter-Clockwise
Hue: Between -25° and +25°
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