Datasets:
File size: 2,292 Bytes
bb3d9e6 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 |
Traffic-Object-Detection - v4 2025-01-17 9:24pm ============================== This dataset was exported via roboflow.com on February 23, 2025 at 7:00 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 2460 images. Cars-8u5W are annotated in COCO format. The following pre-processing was applied to each image: * Auto-orientation of pixel data (with EXIF-orientation stripping) * Resize to 640x640 (Stretch) The following augmentation was applied to create 10 versions of each source image: * 50% probability of horizontal flip * 50% probability of vertical flip * Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise, upside-down * Randomly crop between 0 and 40 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 brigthness adjustment of between -15 and +15 percent * Random exposure adjustment of between -10 and +10 percent * Random Gaussian blur of between 0 and 2.5 pixels * Salt and pepper noise was applied to 0.1 percent of pixels The following transformations were applied to the bounding boxes of each image: * 50% probability of horizontal flip * Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise * Randomly crop between 0 and 20 percent of the bounding box * Random rotation of between -15 and +15 degrees * Random shear of between -10° to +10° horizontally and -10° to +10° vertically * Random brigthness adjustment of between -15 and +15 percent * Random exposure adjustment of between -10 and +10 percent * Random Gaussian blur of between 0 and 2.5 pixels * Salt and pepper noise was applied to 0.1 percent of pixels |