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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 , * 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, , the following pre-processing was applied to each image:
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Top 1229 Datasets and Models
The datasets below can be used to train fine-tuned models for 1229 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 1229 datasets below.
1958 images
* Auto-orientation of pixel data (with EXIF-orientation stripping)* 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 and search unstructured image data* use active learning to improve your dataset over time1001000100110021003100410051006100710081009101
45 images2 models
maskperson-0-0-100-64878048780469-1000-0022505626407-1000-1762127875611-1000-8264462809908-1001-0032508127034-1001-8777110212488-1002-3880414131419-1003-4712241544406-1003-5545789548756-1003-9399267094751-1005-1809269702934-1005-4692262573712-1007-4300071058922-1008-9999999999981-1009-4100906134347-1009-4150672768247-1009-6934516720788
529 images1 model
* 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 time10010001001100210031004100510061007100810091011010
800 images
* 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 rotation of between -11 and +11 degrees* Random shear of between -15° to +15° horizontally and -15° to +15° vertically* Resize to 640x640 (Stretch)* Salt and pepper noise was applied to 5 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 time10010001001100210031004
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