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anomaly-detection - v2 2023-08-30 4:52pm |
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This dataset was exported via roboflow.com on August 30, 2023 at 2:58 PM GMT |
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Roboflow is an end-to-end computer vision platform that helps you |
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* collaborate with your team on computer vision projects |
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* collect & organize images |
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* understand and search unstructured image data |
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* annotate, and create datasets |
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* export, train, and deploy computer vision models |
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* 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, |
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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 381 images. |
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Boxes-anomaly are annotated in YOLOv8 format. |
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The following pre-processing was applied to each image: |
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* Auto-orientation of pixel data (with EXIF-orientation stripping) |
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The following augmentation was applied to create 3 versions of each source image: |
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* 50% probability of horizontal flip |
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* Random rotation of between -5 and +5 degrees |
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* Random brigthness adjustment of between -25 and +25 percent |
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* Random exposure adjustment of between -6 and +6 percent |
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* Random Gaussian blur of between 0 and 1.75 pixels |
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