diff --git a/anomaly-detection.cardboard.anomalib/README.dataset.txt b/anomaly-detection.cardboard.anomalib/README.dataset.txt new file mode 100644 index 0000000000000000000000000000000000000000..65858f5f95455ed671ee3df37990ca0be221af0a --- /dev/null +++ b/anomaly-detection.cardboard.anomalib/README.dataset.txt @@ -0,0 +1,6 @@ +# anomaly-detection > 2023-08-30 4:52pm +https://universe.roboflow.com/t3lab/anomaly-detection-zbp45 + +Provided by a Roboflow user +License: CC BY 4.0 + diff --git a/anomaly-detection.cardboard.anomalib/README.roboflow.txt b/anomaly-detection.cardboard.anomalib/README.roboflow.txt new file mode 100644 index 0000000000000000000000000000000000000000..09473e023784a124c9f1aad930396ca4ed1658e4 --- /dev/null +++ b/anomaly-detection.cardboard.anomalib/README.roboflow.txt @@ -0,0 +1,33 @@ + +anomaly-detection - v2 2023-08-30 4:52pm +============================== + +This dataset was exported via roboflow.com on August 30, 2023 at 2:58 PM GMT + +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 + +For state of the art Computer Vision training notebooks you can use with this dataset, +visit https://github.com/roboflow/notebooks + +To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com + +The dataset includes 381 images. +Boxes-anomaly are annotated in YOLOv8 format. + +The following pre-processing was applied to each image: +* Auto-orientation of pixel data (with EXIF-orientation stripping) + +The following augmentation was applied to create 3 versions of each source image: +* 50% probability of horizontal flip +* Random rotation of between -5 and +5 degrees +* Random brigthness adjustment of between -25 and +25 percent +* Random exposure adjustment of between -6 and +6 percent +* Random Gaussian blur of between 0 and 1.75 pixels + + diff --git a/anomaly-detection.cardboard.anomalib/data.yaml b/anomaly-detection.cardboard.anomalib/data.yaml new file mode 100644 index 0000000000000000000000000000000000000000..43efe02ebb3a3d7edbaa2f4df3690c93a2152a91 --- /dev/null +++ b/anomaly-detection.cardboard.anomalib/data.yaml @@ -0,0 +1,13 @@ +train: ../train/images +val: ../valid/images +test: ../test/images + +nc: 1 +names: ['anomaly'] + +roboflow: + workspace: t3lab + project: anomaly-detection-zbp45 + version: 2 + license: CC BY 4.0 + url: https://universe.roboflow.com/t3lab/anomaly-detection-zbp45/dataset/2 \ No newline at end of file diff --git a/anomaly-detection.cardboard.anomalib/test/defect/20230522124933_png.rf.772ed368a13a7581d41b25f229af4fcd.jpg b/anomaly-detection.cardboard.anomalib/test/defect/20230522124933_png.rf.772ed368a13a7581d41b25f229af4fcd.jpg new file mode 100644 index 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data +* annotate, and create datasets +* export, train, and deploy computer vision models +* use active learning to improve your dataset over time + +For state of the art Computer Vision training notebooks you can use with this dataset, +visit https://github.com/roboflow/notebooks + +To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com + +The dataset includes 381 images. +Boxes-anomaly are annotated in YOLOv8 format. + +The following pre-processing was applied to each image: +* Auto-orientation of pixel data (with EXIF-orientation stripping) + +The following augmentation was applied to create 3 versions of each source image: +* 50% probability of horizontal flip +* Random rotation of between -5 and +5 degrees +* Random brigthness adjustment of between -25 and +25 percent +* Random exposure adjustment of between -6 and +6 percent +* Random Gaussian blur of between 0 and 1.75 pixels + + diff --git a/anomaly-detection.v2i.yolov8/data.yaml 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