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| dominos - v3 2024-09-14 3:51pm |
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| This dataset was exported via roboflow.com on September 14, 2024 at 3:57 PM GMT |
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| Roboflow is an end-to-end computer vision platform that helps you |
| * collaborate with your team on computer vision projects |
| * collect & organize images |
| * understand and search unstructured image data |
| * annotate, and create datasets |
| * export, train, and deploy computer vision models |
| * use active learning to improve your dataset over time |
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| For state of the art Computer Vision training notebooks you can use with this dataset, |
| visit https://github.com/roboflow/notebooks |
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| To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com |
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| The dataset includes 274 images. |
| Dominos are annotated in COCO format. |
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| The following pre-processing was applied to each image: |
| * Auto-orientation of pixel data (with EXIF-orientation stripping) |
| * Resize to 640x640 (Stretch) |
| * Grayscale (CRT phosphor) |
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| The following augmentation was applied to create 3 versions of each source image: |
| * 50% probability of horizontal flip |
| * Randomly crop between 0 and 20 percent of the image |
| * Random rotation of between -15 and +15 degrees |
| * Random shear of between -10° to +10° horizontally and -10° to +10° vertically |
| * Random Gaussian blur of between 0 and 1.5 pixels |
| * Salt and pepper noise was applied to 0.1 percent of pixels |
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