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Related Objects of Interest: * annotate, and create datasets , * collaborate with your team on computer vision projects , * export, train, and deploy computer vision models , * collect & organize images , * 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: , * resize to 640x640 (stretch) , * understand and search unstructured image data
Top 119 Datasets and Models
The datasets below can be used to train fine-tuned models for 119 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 119 datasets below.
3200 images
* 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 time100101102103104105106107108109110111112
2640 images
* 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 time100101102103104105106107108109110111112
3200 images
* 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 time100101102103104105106107108109110111112
1600 images
* Random Gaussian blur of between 0 and 1.25 pixels* Random brigthness adjustment of between -49 and 0 percent* Resize to 340x340 (Stretch)* Salt and pepper noise was applied to 4 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 unstructured image data* use active learning to improve your dataset over time100101102103104105106107108109
1722 images
* Resize to 800x800 (Stretch)* Salt and pepper noise was applied to 0.89 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 time0110100101102103104105106107108
9123 images
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
