Top Stretch Datasets and Models
The datasets below can be used to train fine-tuned models for stretch detection. You can explore each dataset in your browser using Roboflow and export the dataset into one of many formats.
Object Detection
1.32k images
Object Detection
11.3k images
- Auto-orientation of pixel data (with EXIF-orientation stripping)- Resize to 416x416 (Stretch)- collaborate with your team on computer vision projects- understand and search unstructured image data- use active learning to improve your dataset over time==============================A are annotated in YOLOv11 format-Roboflow is an end-to-end computer vision platform that helps youThe dataset includes 11783 images-The following pre-processing was applied to each image:arobo - v19 2024-08-20 5:53amvisit https:--github-com-roboflow-notebooks
Object Detection
567 images
* 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 time19202122232425==============================For state of the art Computer Vision training notebooks you can use with this dataset,Letters-Numbers are annotated in YOLOv8 format.No image augmentation techniques were applied.Roboflow is an end-to-end computer vision platform that helps you
Object Detection
2.91k images·5
* Auto-contrast via contrast stretching* 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 time192021222324252627282930
Object Detection
1.98k images·1 model
- Auto-orientation of pixel data (with EXIF-orientation stripping)- Resize to 640x640 (Stretch)- collaborate with your team on computer vision projects- understand and search unstructured image data- use active learning to improve your dataset over time19202122232425==============================No image augmentation techniques were applied-Roboflow is an end-to-end computer vision platform that helps youThe dataset includes 2143 images-The following pre-processing was applied to each image:VEST - v1 2024-01-16 2:34pmVEST are annotated in YOLOv11 format-visit https:--github-com-roboflow-notebooks
Object Detection
50 images·8
* 50% probability of horizontal flip* 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* use active learning to improve your dataset over time==============================Animal detect - v2 2023-04-25 3:38pmAnimals 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 269 images.The following augmentation was applied to create 3 versions of each source image:The following pre-processing was applied to each image:This dataset was exported via roboflow.com on April 25, 2023 at 10:09 AM GMTTo find over 100k other datasets and pre-trained models, visit https://universe.roboflow.comvisit https://github.com/roboflow/notebooks
Object Detection
631 images
- Auto-orientation of pixel data (with EXIF-orientation stripping)- Random brigthness adjustment of between -12 and +12 percent- Random brigthness adjustment of between -22 and +22 percent- Random exposure adjustment of between -7 and +7 percent- Random rotation of between -0 and +0 degrees- Random shear of between -10° to +10° horizontally and -10° to +10° vertically- Randomly crop between 0 and 0 percent of the image- Randomly crop between 0 and 20 percent of the bounding box- Resize to 640x640 (Stretch)- Salt and pepper noise was applied to 3-51 percent of pixels- collaborate with your team on computer vision projects- understand and search unstructured image data- use active learning to improve your dataset over time011011121314
Object Detection
3.41k images
- Auto-orientation of pixel data (with EXIF-orientation stripping)- Resize to 640x640 (Stretch)- collaborate with your team on computer vision projects- understand and search unstructured image data- use active learning to improve your dataset over time19202122==============================Car_exterior are annotated in YOLOv8 format-No image augmentation techniques were applied-Roboflow is an end-to-end computer vision platform that helps youThe dataset includes 3291 images-The following pre-processing was applied to each image:car-exterior-parts - v1 2024-06-19 11:56amlicense_platevisit https:--github-com-roboflow-notebooks
Object Detection
116 images·1 model
Object Detection
4.15k images
Object Detection
9.95k images·1 model·2
* Auto-orientation of pixel data (with EXIF-orientation stripping)* Random Gaussian blur of between 0 and 5 pixels* Random exposure adjustment of between -20 and +20 percent* Random rotation of between -10 and +10 degrees* Random shear of between -15° to +15° horizontally and -15° to +15° vertically* 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 time2324252627282930
Object Detection
1.73k images
- 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)- collaborate with your team on computer vision projects- understand and search unstructured image data- use active learning to improve your dataset over time25==============================American Sign Language Letters - v1 v1Letters are annotated in YOLOv8 format-Roboflow is an end-to-end computer vision platform that helps youThe dataset includes 1728 images-The following augmentation was applied to create 3 versions of each source image:The following pre-processing was applied to each image:visit https:--github-com-roboflow-notebooks
Object Detection
5.83k images·4 models
* Auto-contrast via contrast stretching* 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 time1920212223242525526272829
Object Detection
1.96k images
* 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 time19202122232425==============================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 youThe dataset includes 2143 images.
Object Detection
6.78k images·1 model
Object Detection
1.98k images
- Random brigthness adjustment of between -25 and +25 percent- Random rotation of between -15 and +15 degrees- Resize to 640x640 (Stretch)- collaborate with your team on computer vision projects- understand and search unstructured image data- use active learning to improve your dataset over time202122232425==============================A are annotated in YOLOv8 Oriented Object Detection format-BBisindo - v2 2025-10-29 3:12pmClas AClass BClass RClass T
Object Detection
1.19k images·1 model·1
* 50% probability of horizontal flip* 50% probability of vertical flip* Auto-orientation of pixel data (with EXIF-orientation stripping)* Random exposure adjustment of between -15 and +15 percent* Random rotation of between -15 and +15 degrees* Random shear of between -15° to +15° horizontally and -15° to +15° vertically* 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 time24252627282930
Object Detection
7.21k images
* 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 time192021222324252627282930
Object Detection
200 images
* Auto-orientation of pixel data (with EXIF-orientation stripping)* Resize to 160x160 (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 time010304050709192021222324
Object Detection
140 images
Object Detection
11.9k images
- Auto-orientation of pixel data (with EXIF-orientation stripping)- Resize to 640x640 (Stretch)- collaborate with your team on computer vision projects- understand and search unstructured image data- use active learning to improve your dataset over time1920212223242526272829==============================Chann-upp-Channel-Up are annotated in YOLOv8 format-Final - v1 2025-07-21 1:42amNo image augmentation techniques were applied-
Object Detection
1.34k images
-- 50- probability of horizontal flip- 50- probability of vertical flip- Auto-orientation of pixel data -with EXIF-orientation stripping-- Grayscale -CRT phosphor-- Random Gaussian blur of between 0 and 0-8 pixels- Random rotation of between -12 and -12 degrees- 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 time100101102103104105
Classification
2.24k images·1 model·2
freshobject* 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 time21222323 242425
Object Detection
118 images
Ab RollerAb StrapsAb crunchAbdominal Crunch MachineAdjustable DumbbellsAdjustable benchAir BikeAnkle Straps AttachmentsAssault BikeAssisted Pull UpBack Extension MachineBarbellBarbell Wrist RollerBattle RopesBelt SquatBiceps Curl MachineBosu BallCable AttatchmentsCable Handle AttachmentCable Machine
Object Detection
1.35k images
Object Detection
316 images
- Auto-orientation of pixel data (with EXIF-orientation stripping)- Grayscale (CRT phosphor)- Resize to 200x50 (Stretch)- collaborate with your team on computer vision projects- understand and search unstructured image data- use active learning to improve your dataset over time2021222324==============================Captcha - v5 2023-12-13 8:17pmCharacters are annotated in YOLOv11 format-No image augmentation techniques were applied-Roboflow is an end-to-end computer vision platform that helps youThe dataset includes 316 images-The following pre-processing was applied to each image:visit https:--github-com-roboflow-notebooks
Object Detection
1.12k images
- Auto-orientation of pixel data (with EXIF-orientation stripping)- Random Gaussian blur of between 0 and 2-5 pixels- Randomly crop between 0 and 20 percent of the image- Resize to 418x418 (Stretch)- Salt and pepper noise was applied to 1-02 percent of pixels- collaborate with your team on computer vision projects- understand and search unstructured image data- use active learning to improve your dataset over time222324252627282930313233
Object Detection
8.71k images·21
* Auto-orientation of pixel data (with EXIF-orientation stripping)* Random rotation of between -17 and +17 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* export, train, and deploy computer vision models* understand and search unstructured image data12122232425262728359
