Bottles and Cups Detection Image Dataset
Versions
2023-12-03 9:36pm
v27
Dec 3, 2023
2023-12-03 3:06pm
v24
Dec 3, 2023
30 epochs fliphori-rotate90-brightness-20-blur2px-noise5-cutout5 10-mosaic
v23
Dec 2, 2023
30 epochs fliphori-rotate90-brightness-20-blur2px-noise5-cutout5 10-mosaic
v22
Dec 2, 2023
30 epochs roate90 - brightness20 - blur2.5 - noise10 - cutout4 15 - mosaic
v21
Nov 30, 2023
50 epochs rotate90-brightness -20- blur2.5- noise10- cutout4 15- mosaic
v20
Nov 29, 2023
same as 15 but no mosaic 35 epochs
v19
Nov 19, 2023
v27
2023-12-03 9:36pm
Generated on Dec 3, 2023
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YOLOv9
TXT annotations and YAML config used with YOLOv9.
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COCO JSON
COCO JSON annotations are used with EfficientDet Pytorch and Detectron 2.
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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.
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12900 Total Images
View All Images
Dataset Split
Train Set 88%
11289Images
Valid Set 8%
1074Images
Test Set 4%
537Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 1280x960
Augmentations
Outputs per training example: 3
Flip: Horizontal
90° Rotate: Clockwise, Counter-Clockwise
Brightness: Between -25% and +25%
Exposure: Between -30% and +30%
Blur: Up to 1.75px
Noise: Up to 5% of pixels
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