Dex Mac Dataset
Versions
2022-10-11 11:22pm
v13
· 2 years ago
2022-10-11 11:22pm
v12
· 2 years ago
2022-10-11 11:06pm
v11
· 2 years ago
2022-10-10 10:10pm
v10
· 2 years ago
2022-10-10 8:45pm
v9
· 2 years ago
2022-10-10 8:13pm
v7
· 2 years ago
2022-10-10 7:08pm
v6
· 2 years ago
2022-10-10 7:04pm
v5
· 2 years ago
2022-10-10 12:39am
v4
· 2 years ago
2022-10-09 11:35pm
v3
· 2 years ago
2022-10-09 11:33pm
v2
· 2 years ago
v9
2022-10-10 8:45pm
Generated on Oct 10, 2022
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.
2870 Total Images
View All Images
Dataset Split
Train Set 96%
2750Images
Valid Set 3%
76Images
Test Set 2%
44Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 832x832
Tile: 2 rows x 2 columns
Filter Null: Require all images to contain annotations.
Augmentations
Outputs per training example: 10
Flip: Horizontal
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Rotation: Between -15° and +15°
Shear: ±15° Horizontal, ±15° Vertical
Grayscale: Apply to 25% of images
Hue: Between -25° and +25°
Saturation: Between -25% and +25%
Brightness: Between -25% and +25%
Exposure: Between -25% and +25%
Blur: Up to 10px
Noise: Up to 5% of pixels
Cutout: 3 boxes with 10% size each
Mosaic: Applied
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