Related Objects of Interest: * annotate, and create datasets, * auto-orientation of pixel data (with exif-orientation stripping), * collaborate with your team on computer vision projects, * collect & organize images, * export, train, and deploy computer vision models, * use active learning to improve your dataset over time, ==============================, roboflow is an end-to-end computer vision platform that helps you, the following pre-processing was applied to each image:, * 50% probability of horizontal flip
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Top Are Datasets and Models
The datasets below can be used to train fine-tuned models for are detection. You can explore each dataset in your browser using Roboflow and export the dataset into one of many formats.
At the bottom of this page, we have guides on how to train a model using the are datasets below.
by Marco
9560 images 52 classes
* 50% probability of horizontal flip * 50% probability of vertical flip * Auto-orientation of pixel data (with EXIF-orientation stripping) * Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise, upside-down * Random Gaussian blur of between 0 and 1.75 pixels * Random brigthness adjustment of between -25 and +25 percent * Random exposure adjustment of between -15 and +15 percent * Random rotation of between -10 and +10 degrees * Random shear of between -2° to +2° horizontally and -2° to +2° vertically * Randomly crop between 0 and 15 percent of the image * Resize to 640x640 (Stretch) * Salt and pepper noise was applied to 2 percent of pixels * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 29 30
by AI
2240 images 34 classes
object * 50% probability of horizontal flip * 50% probability of vertical flip * Auto-orientation of pixel data (with EXIF-orientation stripping) * Resize to 640x640 (Stretch) * annotate, and create datasets * annotate, and create datasets * collect & organize images * annotate, and create datasets * understand and search unstructured image data * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 21 22 23 23 24 24 25 26
1720 images 26 classes
* 50% probability of horizontal flip * Auto-orientation of pixel data (with EXIF-orientation stripping) * Random Gaussian blur of between 0 and 1.25 pixels * Random brigthness adjustment of between -25 and +25 percent * Random rotation of between -5 and +5 degrees * Random shear of between -5° to +5° horizontally and -5° to +5° vertically * Randomly crop between 0 and 20 percent of the image * Resize to 416x416 (Stretch) * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand unstructured image data * use active learning to improve your dataset over time 22 23 24 25 ============================== American Sign Language Letters - v1 v1
by MyDatas
18280 images 23 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Resize to 640x640 (Stretch) * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 19 20 21 22 ============================== For state of the art Computer Vision training notebooks you can use with this dataset, No image augmentation techniques were applied. Roboflow is an end-to-end computer vision platform that helps you The dataset includes 18310 images. The following pre-processing was applied to each image: Thing are annotated in YOLOv8 format. This dataset was exported via roboflow.com on May 8, 2024 at 8:52 PM GMT
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