Related Objects of Interest: * 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, ==============================, for state of the art computer vision training notebooks you can use with this dataset,, roboflow is an end-to-end computer vision platform that helps you, the following pre-processing was applied to each image:
Top 183 Datasets and Models
The datasets below can be used to train fine-tuned models for 183 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 183 datasets below.
by Deneme
3362 images 694 classes
* Auto-contrast via contrast stretching * 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 shear of between -14° to +14° horizontally and -15° to +15° vertically * Resize to 800x800 (Stretch) * Salt and pepper noise was applied to 1.13 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 100 101 102 103 104 105 106 107
by Deneme
3256 images 692 classes
* Auto-contrast via contrast stretching * 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 shear of between -14° to +14° horizontally and -15° to +15° vertically * Resize to 800x800 (Stretch) * Salt and pepper noise was applied to 1.13 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 100 101 102 103 104 105 106 107
218 images 433 classes
529 images 4201 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * 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 100 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 101 1010
9000 images 184 classes
* 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 100 101 102 103 104 105 106 107 108 109 110 111 112
by dartecne
112 images 88 classes
103-74002978941007 104-40265831779924 104-93426496105837 110-14560857379375 116-16716140017084 121-99696794523425 128-91061139044356 13-04654476818908 145-76466696298434 145-86762551249245 160-23557103729541 171-19865856746844 172-8230252590967 175-50403457768726 179-76299547944782 180-33020527316833 183-16340375405775 186-97063065424447 190-72414542320126 191-58404057258554