ballrdpooldetect Image Dataset
Versions!
2024-06-16 12:57pm
v41
· 11 days ago
323
2024-06-15 4:54am
v40
· 13 days ago
2940
640x640
Stretch to
2024-06-14 2:21am
v39
· 14 days ago
2856
640x640
Stretch to
2024-06-11 4:41pm
v38
· 16 days ago
2672
2024-06-10 12:23pm
v37
· 17 days ago
655
2024-06-10 6:26am
v36
· 17 days ago
601
2024-06-05 7:55am
v35
· 22 days ago
601
2024-06-03 7:42pm
v34
· 24 days ago
555
2024-06-03 5:34am
v33
· 24 days ago
555
2024-06-02 4:03pm
v32
· 25 days ago
498
2024-06-02 8:09am
v31
· 25 days ago
500
2024-06-01 10:33pm
v30
· a month ago
469
2024-06-01 7:15am
v26
· a month ago
495
2024-05-31 9:08am
v25
· a month ago
218
2024-05-27 11:19am
v22
· a month ago
506
2024-05-02 5:49am
v14
· 2 months ago
984
Accurate
ballrdpooldetect/13
2024-05-01 5:47am
v13
· 2 months ago
1016
Accurate
ballrdpooldetect/11
2024-04-30 11:21am
v11
· 2 months ago
460
Accurate
ballrdpooldetect/4
2024-04-28 3:51pm
v4
· 2 months ago
79
Accurate
ballrdpooldetect/2
2024-03-24 6:02pm
v3
· 3 months ago
63
Fast
COCOn
v13
2024-05-01 5:47am
Generated on May 1, 2024
Popular Download Formats
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.
1016 Total Images
View All Images
Dataset Split
Train Set 89%
900Images
Valid Set 8%
80Images
Test Set 4%
36Images
Preprocessing
Auto-Orient: Applied
Static Crop: 0-100% Horizontal Region, 0-100% Vertical Region
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Contrast Stretching
Tile: 2 rows x 2 columns
Augmentations
Outputs per training example: 5
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Hue: Between -15° and +15°
Saturation: Between -20% and +20%
Exposure: Between -10% and +10%
Blur: Up to 0.4px
Noise: Up to 0.1% of pixels
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