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Traffic-Object-Detection - v4 2025-01-17 9:24pm |
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This dataset was exported via roboflow.com on February 23, 2025 at 7:00 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 2460 images. |
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Cars-8u5W are annotated in COCO 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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* Resize to 640x640 (Stretch) |
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The following augmentation was applied to create 10 versions of each source image: |
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* 50% probability of horizontal flip |
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* 50% probability of vertical flip |
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* Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise, upside-down |
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* Randomly crop between 0 and 40 percent of the image |
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* Random rotation of between -15 and +15 degrees |
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* Random shear of between -10° to +10° horizontally and -10° to +10° vertically |
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* Random brigthness adjustment of between -15 and +15 percent |
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* Random exposure adjustment of between -10 and +10 percent |
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* Random Gaussian blur of between 0 and 2.5 pixels |
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* Salt and pepper noise was applied to 0.1 percent of pixels |
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The following transformations were applied to the bounding boxes of each image: |
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* 50% probability of horizontal flip |
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* Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise |
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* Randomly crop between 0 and 20 percent of the bounding box |
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* Random rotation of between -15 and +15 degrees |
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* Random shear of between -10° to +10° horizontally and -10° to +10° vertically |
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* Random brigthness adjustment of between -15 and +15 percent |
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* Random exposure adjustment of between -10 and +10 percent |
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* Random Gaussian blur of between 0 and 2.5 pixels |
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* Salt and pepper noise was applied to 0.1 percent of pixels |
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