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Related Objects of Interest: ============================== , the following pre-processing was applied to each image: , * auto-orientation of pixel data (with exif-orientation stripping) , * use active learning to improve your dataset over time , * 50% probability of horizontal flip , * annotate, and create datasets , * collaborate with your team on computer vision projects , * export, train, and deploy computer vision models , * understand and search unstructured image data , visit https://github.com/roboflow/notebooks
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Top Equal Computer Vision Models
The models below have been fine-tuned for various equal detection tasks. You can try out each model in your browser, or test an edge deployment solution (i.e. to an NVIDIA Jetson). You can use the datasets associated with the models below as a starting point for building your own equal detection model.
At the bottom of this page, we have guides on how to count equals in images and videos.
7221 images1 model
* 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 2.5 pixels* Resize to 640x640 (Stretch)* annotate, and create datasets* collaborate with your team on computer vision projects* export, train, and deploy computer vision models* understand and search unstructured image data* use active learning to improve your dataset over time222324262729==============================AxeBazookaGunKatana
200 images1 model
* 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* Resize to 600x600 (Fit (white edges))* 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==============================Chocolates are annotated in YOLOv8 format.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 youThe dataset includes 267 images.The following augmentation was applied to create 5 versions of each source image:The following pre-processing was applied to each image:This dataset was exported via roboflow.com on June 4, 2023 at 12:27 PM GMTTo find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com
3006 images1 model
* 50% probability of horizontal flip* Auto-orientation of pixel data (with EXIF-orientation stripping)* Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise* Random rotation of between -15 and +15 degrees* Randomly crop between 0 and 20 percent of the image* Resize to 416x416 (Stretch)1314151617181920212223242526
3006 images1 model
* 50% probability of horizontal flip* Auto-orientation of pixel data (with EXIF-orientation stripping)* Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise* Random rotation of between -15 and +15 degrees* 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 and search unstructured image data* use active learning to improve your dataset over time2324252627282930
246 images1 model
* 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 0.5 pixels* Random brigthness adjustment of between -16 and +16 percent* Random exposure adjustment of between -6 and +6 percent* Resize to 600x600 (Fit (white edges))15161718192021==============================Chocolates are annotated in YOLO v5 PyTorch format.Dark MarzipanIt includes 267 images.Milk California Brittle
4856 images1 model
chickentrain#-Healthy-and-Sick-Chicken-Detection->-2023-02-04-2:29pm*-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*-Random-exposure-adjustment-of-between--25-and-+25-percent*-Resize-to-416x416-(Stretch)*-annotate*-collaborate-with-your-team-on-computer-vision-projects*-collect-&-organize-images*-export*-understand-and-search-unstructured-image-data*-use-active-learning-to-improve-your-dataset-over-time1WOC-are-annotated-in-Tensorflow-Object-Detection-format.2024-at-10:31-AM-GMT==============================For-state-of-the-art-Computer-Vision-training-notebooks-you-can-use-with-this-datasetHealthy-and-Sick-Chicken-Detection---v18-2023-02-04-2:29pm
67 images1 model
Austria - 50th Anniversary of the Austrian State TreatyBelgium - 200th Anniversary of birth of Louis Braille 2009Belgium - 60th anniversary of the Universal Declaration of Human Rights 2008Belgium - Belgian Presidency of the Council of the European Union in 2010Belgium - Belgium-Luxembourg Economic Union 2005Belgium - Renovation of the Atomium in Brussels 2006Eurozone - 10th Anniversary of the Introduction of the Euro 2009Eurozone - 50th anniversary of the Treaty of Rome 2007Finland - 150th anniversary of Finnish currency 2010Finland - 1st Centenary of the Introduction of Universal and Equal Suffrage 2006Finland - 200 years of Finnish autonomy 2009Finland - 60th Anniversary of the Establishment of the United Nations and 50th Anniversary of Finland's UN Membership 2005Finland - 60th Anniversary of the Universal Declaration of Human Rights 2008Finland - 90th Anniversary of Finland's Independence 2007Finland - Fifth Enlargement of the European Union 2004France - 70th Anniversary of the Appeal of June 18 by General de Gaulle 2010France - French Presidency of the Council of the European Union 2008Germany - Federal state of Bremen 2010Germany - Federal state of North Rhine-Westphalia 2011Germany - Holstentor in Lübeck (Schleswig-Holstein) 2006
28 images3 models
Bus-StopChildren-PresentContainers-OnlyCustoms-CheckpointDangerous-TurnEqual-level-IntersectionGo-StraightHeight-LimitIntersectionIntersection-with-T-JunctionIntersection-with-Uncontrolled-RoadLane-AllocationLeft-TurnLevel-Crossing-with-BarriersLow-ClearanceMotorcycles-OnlyNarrow-Road-on-the-LeftNarrow-Road-on-the-RightNo turrn left or backNo-Cars-Allowed
3200 images1 model
Bus StopChildren PresentContainers OnlyCustoms CheckpointDangerous TurnEqual-level IntersectionGo StraightHeight LimitIntersectionIntersection with T-JunctionIntersection with Uncontrolled RoadLane AllocationLeft TurnLevel Crossing with BarriersLow ClearanceMotorcycles OnlyNarrow Road on the LeftNarrow Road on the RightNo Cars AllowedNo Containers Allowed
80 images1 model
* 50% probability of horizontal 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 -15 and +15 degrees* Resize to 416x416 (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 unstructured image data* use active learning to improve your dataset over time2021222324252627
1430 images1 model
7635 images1 model
object* 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* Random Gaussian blur of between 0 and 1.5 pixels* Random brigthness adjustment of between -25 and +25 percent* Random brigthness adjustment of between -30 and +30 percent* Random rotation of between -23 and +23 degrees* 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 time282930
9335 images3 models
* 50% probability of horizontal flip* Auto-orientation of pixel data (with EXIF-orientation stripping)* Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise* Random rotation of between -15 and +15 degrees* 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 and search unstructured image data* use active learning to improve your dataset over time2324252627282930
3155 images1 model
Bus StopChildren PresentDangerous TurnEqual-level IntersectionGo StraightHeight LimitIntersectionIntersection with T-JunctionIntersection with Uncontrolled RoadLane AllocationLeft TurnLevel Crossing with BarriersLow ClearanceNarrow Road on the LeftNarrow Road on the RightNo Cars AllowedNo Containers AllowedNo EntryNo Left TurnNo Left Turn for Motorcycles
101 images2 models
* 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* Equal probability of one of the following 90-degree rotations: none, clockwise, upside-down* Random Gaussian blur of between 0 and 1.6 pixels* Random Gaussian blur of between 0 and 10.2 pixels* Random brigthness adjustment of between -40 and +40 percent* Random brigthness adjustment of between -53 and +53 percent* Random exposure adjustment of between -27 and +27 percent* Random exposure adjustment of between -41 and +41 percent* Random rotation of between -35 and +35 degrees* Random rotation of between -45 and +45 degrees* Random shear of between -16° to +16° horizontally and -22° to +22° vertically* Random shear of between -37° to +37° horizontally and -29° to +29° vertically* Randomly crop between 22 and 61 percent of the bounding box* Randomly crop between 5 and 18 percent of the image* Resize to 640x640 (Stretch)* Salt and pepper noise was applied to 0.81 percent of pixels* Salt and pepper noise was applied to 4.62 percent of pixels
1994 images1 model
* 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* Resize to 180x300 (Stretch)* Salt and pepper noise was applied to 1 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 time2425262728293031
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