CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
The Hard Hat
dataset is an object detection dataset of workers in workplace settings that require a hard hat. Annotations also include examples of just "person" and "head," for when an individual may be present without a hard hart.
The original dataset has a 75/25 train-test split.
Example Image:
https://i.imgur.com/7spoIJT.png" alt="Example Image">
One could use this dataset to, for example, build a classifier of workers that are abiding safety code within a workplace versus those that may not be. It is also a good general dataset for practice.
Use the fork
or Download this Dataset
button to copy this dataset to your own Roboflow account and export it with new preprocessing settings (perhaps resized for your model's desired format or converted to grayscale), or additional augmentations to make your model generalize better. This particular dataset would be very well suited for Roboflow's new advanced Bounding Box Only Augmentations.
Image Preprocessing | Image Augmentation | Modify Classes
* v1
(resize-416x416-reflect): generated with the original 75/25 train-test split | No augmentations
* v2
(raw_75-25_trainTestSplit): generated with the original 75/25 train-test split | These are the raw, original images
* v3
(v3): generated with the original 75/25 train-test split | Modify Classes used to drop person
class | Preprocessing and Augmentation applied
* v5
(raw_HeadHelmetClasses): generated with a 70/20/10 train/valid/test split | Modify Classes used to drop person
class
* v8
(raw_HelmetClassOnly): generated with a 70/20/10 train/valid/test split | Modify Classes used to drop head
and person
classes
* v9
(raw_PersonClassOnly): generated with a 70/20/10 train/valid/test split | Modify Classes used to drop head
and helmet
classes
* v10
(raw_AllClasses): generated with a 70/20/10 train/valid/test split | These are the raw, original images
* v11
(augmented3x-AllClasses-FastModel): generated with a 70/20/10 train/valid/test split | Preprocessing and Augmentation applied | 3x image generation | Trained with Roboflow's Fast Model
* v12
(augmented3x-HeadHelmetClasses-FastModel): generated with a 70/20/10 train/valid/test split | Preprocessing and Augmentation applied, Modify Classes used to drop person
class | 3x image generation | Trained with Roboflow's Fast Model
* v13
(augmented3x-HeadHelmetClasses-AccurateModel): generated with a 70/20/10 train/valid/test split | Preprocessing and Augmentation applied, Modify Classes used to drop person
class | 3x image generation | Trained with Roboflow's Accurate Model
* v14
(raw_HeadClassOnly): generated with a 70/20/10 train/valid/test split | Modify Classes used to drop person
class, and remap/relabel helmet
class to head
Choosing Between Computer Vision Model Sizes | Roboflow Train
Roboflow makes managing, preprocessing, augmenting, and versioning datasets for computer vision seamless.
Developers reduce 50% of their code when using Roboflow's workflow, automate annotation quality assurance, save training time, and increase model reproducibility.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Activities of Daily Living Object DatasetOverviewThe ADL (Activities of Daily Living) Object Dataset is a curated collection of images and annotations specifically focusing on objects commonly interacted with during daily living activities. This dataset is designed to facilitate research and development in assistive robotics in home environments.Data Sources and LicensingThe dataset comprises images and annotations sourced from four publicly available datasets:COCO DatasetLicense: Creative Commons Attribution 4.0 International (CC BY 4.0)License Link: https://creativecommons.org/licenses/by/4.0/Citation:Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., & Zitnick, C. L. (2014). Microsoft COCO: Common Objects in Context. European Conference on Computer Vision (ECCV), 740–755.Open Images DatasetLicense: Creative Commons Attribution 4.0 International (CC BY 4.0)License Link: https://creativecommons.org/licenses/by/4.0/Citation:Kuznetsova, A., Rom, H., Alldrin, N., Uijlings, J., Krasin, I., Pont-Tuset, J., Kamali, S., Popov, S., Malloci, M., Duerig, T., & Ferrari, V. (2020). The Open Images Dataset V6: Unified Image Classification, Object Detection, and Visual Relationship Detection at Scale. International Journal of Computer Vision, 128(7), 1956–1981.LVIS DatasetLicense: Creative Commons Attribution 4.0 International (CC BY 4.0)License Link: https://creativecommons.org/licenses/by/4.0/Citation:Gupta, A., Dollar, P., & Girshick, R. (2019). LVIS: A Dataset for Large Vocabulary Instance Segmentation. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 5356–5364.Roboflow UniverseLicense: Creative Commons Attribution 4.0 International (CC BY 4.0)License Link: https://creativecommons.org/licenses/by/4.0/Citation: The following repositories from Roboflow Universe were used in compiling this dataset:Work, U. AI Based Automatic Stationery Billing System Data Dataset. 2022. Accessible at: https://universe.roboflow.com/university-work/ai-based-automatic-stationery-billing-system-data (accessed on 11 October 2024).Destruction, P.M. Pencilcase Dataset. 2023. Accessible at: https://universe.roboflow.com/project-mental-destruction/pencilcase-se7nb (accessed on 11 October 2024).Destruction, P.M. Final Project Dataset. 2023. Accessible at: https://universe.roboflow.com/project-mental-destruction/final-project-wsuvj (accessed on 11 October 2024).Personal. CSST106 Dataset. 2024. Accessible at: https://universe.roboflow.com/personal-pgkq6/csst106 (accessed on 11 October 2024).New-Workspace-kubz3. Pencilcase Dataset. 2022. Accessible at: https://universe.roboflow.com/new-workspace-kubz3/pencilcase-s9ag9 (accessed on 11 October 2024).Finespiralnotebook. Spiral Notebook Dataset. 2024. Accessible at: https://universe.roboflow.com/finespiralnotebook/spiral_notebook (accessed on 11 October 2024).Dairymilk. Classmate Dataset. 2024. Accessible at: https://universe.roboflow.com/dairymilk/classmate (accessed on 11 October 2024).Dziubatyi, M. Domace Zadanie Notebook Dataset. 2023. Accessible at: https://universe.roboflow.com/maksym-dziubatyi/domace-zadanie-notebook (accessed on 11 October 2024).One. Stationery Dataset. 2024. Accessible at: https://universe.roboflow.com/one-vrmjr/stationery-mxtt2 (accessed on 11 October 2024).jk001226. Liplip Dataset. 2024. Accessible at: https://universe.roboflow.com/jk001226/liplip (accessed on 11 October 2024).jk001226. Lip Dataset. 2024. Accessible at: https://universe.roboflow.com/jk001226/lip-uteep (accessed on 11 October 2024).Upwork5. Socks3 Dataset. 2022. Accessible at: https://universe.roboflow.com/upwork5/socks3 (accessed on 11 October 2024).Book. DeskTableLamps Material Dataset. 2024. Accessible at: https://universe.roboflow.com/book-mxasl/desktablelamps-material-rjbgd (accessed on 11 October 2024).Gary. Medicine Jar Dataset. 2024. Accessible at: https://universe.roboflow.com/gary-ofgwc/medicine-jar (accessed on 11 October 2024).TEST. Kolmarbnh Dataset. 2023. Accessible at: https://universe.roboflow.com/test-wj4qi/kolmarbnh (accessed on 11 October 2024).Tube. Tube Dataset. 2024. Accessible at: https://universe.roboflow.com/tube-nv2vt/tube-9ah9t (accessed on 11 October 2024). Staj. Canned Goods Dataset. 2024. Accessible at: https://universe.roboflow.com/staj-2ipmz/canned-goods-isxbi (accessed on 11 October 2024).Hussam, M. Wallet Dataset. 2024. Accessible at: https://universe.roboflow.com/mohamed-hussam-cq81o/wallet-sn9n2 (accessed on 14 October 2024).Training, K. Perfume Dataset. 2022. Accessible at: https://universe.roboflow.com/kdigital-training/perfume (accessed on 14 October 2024).Keyboards. Shoe-Walking Dataset. 2024. Accessible at: https://universe.roboflow.com/keyboards-tjtri/shoe-walking (accessed on 14 October 2024).MOMO. Toilet Paper Dataset. 2024. Accessible at: https://universe.roboflow.com/momo-nutwk/toilet-paper-wehrw (accessed on 14 October 2024).Project-zlrja. Toilet Paper Detection Dataset. 2024. Accessible at: https://universe.roboflow.com/project-zlrja/toilet-paper-detection (accessed on 14 October 2024).Govorkov, Y. Highlighter Detection Dataset. 2023. Accessible at: https://universe.roboflow.com/yuriy-govorkov-j9qrv/highlighter_detection (accessed on 14 October 2024).Stock. Plum Dataset. 2024. Accessible at: https://universe.roboflow.com/stock-qxdzf/plum-kdznw (accessed on 14 October 2024).Ibnu. Avocado Dataset. 2024. Accessible at: https://universe.roboflow.com/ibnu-h3cda/avocado-g9fsl (accessed on 14 October 2024).Molina, N. Detection Avocado Dataset. 2024. Accessible at: https://universe.roboflow.com/norberto-molina-zakki/detection-avocado (accessed on 14 October 2024).in Lab, V.F. Peach Dataset. 2023. Accessible at: https://universe.roboflow.com/vietnam-fruit-in-lab/peach-ejdry (accessed on 14 October 2024).Group, K. Tomato Detection 4 Dataset. 2023. Accessible at: https://universe.roboflow.com/kkabs-group-dkcni/tomato-detection-4 (accessed on 14 October 2024).Detection, M. Tomato Checker Dataset. 2024. Accessible at: https://universe.roboflow.com/money-detection-xez0r/tomato-checker (accessed on 14 October 2024).University, A.S. Smart Cam V1 Dataset. 2023. Accessible at: https://universe.roboflow.com/ain-shams-university-byja6/smart_cam_v1 (accessed on 14 October 2024).EMAD, S. Keysdetection Dataset. 2023. Accessible at: https://universe.roboflow.com/shehab-emad-n2q9i/keysdetection (accessed on 14 October 2024).Roads. Chips Dataset. 2024. Accessible at: https://universe.roboflow.com/roads-rvmaq/chips-a0us5 (accessed on 14 October 2024).workspace bgkzo, N. Object Dataset. 2021. Accessible at: https://universe.roboflow.com/new-workspace-bgkzo/object-eidim (accessed on 14 October 2024).Watch, W. Wrist Watch Dataset. 2024. Accessible at: https://universe.roboflow.com/wrist-watch/wrist-watch-0l25c (accessed on 14 October 2024).WYZUP. Milk Dataset. 2024. Accessible at: https://universe.roboflow.com/wyzup/milk-onbxt (accessed on 14 October 2024).AussieStuff. Food Dataset. 2024. Accessible at: https://universe.roboflow.com/aussiestuff/food-al9wr (accessed on 14 October 2024).Almukhametov, A. Pencils Color Dataset. 2023. Accessible at: https://universe.roboflow.com/almas-almukhametov-hs5jk/pencils-color (accessed on 14 October 2024).All images and annotations obtained from these datasets are released under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This license permits sharing and adaptation of the material in any medium or format, for any purpose, even commercially, provided that appropriate credit is given, a link to the license is provided, and any changes made are indicated.Redistribution Permission:As all images and annotations are under the CC BY 4.0 license, we are legally permitted to redistribute this data within our dataset. We have complied with the license terms by:Providing appropriate attribution to the original creators.Including links to the CC BY 4.0 license.Indicating any changes made to the original material.Dataset StructureThe dataset includes:Images: High-quality images featuring ADL objects suitable for robotic manipulation.Annotations: Bounding boxes and class labels formatted in the YOLO (You Only Look Once) Darknet format.ClassesThe dataset focuses on objects commonly involved in daily living activities. A full list of object classes is provided in the classes.txt file.FormatImages: JPEG format.Annotations: Text files corresponding to each image, containing bounding box coordinates and class labels in YOLO Darknet format.How to Use the DatasetDownload the DatasetUnpack the Datasetunzip ADL_Object_Dataset.zipHow to Cite This DatasetIf you use this dataset in your research, please cite our paper:@article{shahria2024activities, title={Activities of Daily Living Object Dataset: Advancing Assistive Robotic Manipulation with a Tailored Dataset}, author={Shahria, Md Tanzil and Rahman, Mohammad H.}, journal={Sensors}, volume={24}, number={23}, pages={7566}, year={2024}, publisher={MDPI}}LicenseThis dataset is released under the Creative Commons Attribution 4.0 International License (CC BY 4.0).License Link: https://creativecommons.org/licenses/by/4.0/By using this dataset, you agree to provide appropriate credit, indicate if changes were made, and not impose additional restrictions beyond those of the original licenses.AcknowledgmentsWe gratefully acknowledge the use of data from the following open-source datasets, which were instrumental in the creation of our specialized ADL object dataset:COCO Dataset: We thank the creators and contributors of the COCO dataset for making their images and annotations publicly available under the CC BY 4.0 license.Open Images Dataset: We express our gratitude to the Open Images team for providing a comprehensive dataset of annotated images under the CC BY 4.0 license.LVIS Dataset: We appreciate the efforts of the LVIS dataset creators for releasing their extensive dataset under the CC BY 4.0 license.Roboflow Universe:
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
## Overview
QR Codes From Roboflow is a dataset for object detection tasks - it contains QRCodes annotations for 1,582 images.
## Getting Started
You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
## License
This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Football (soccer) player and football (soccer) ball detection dataset from Augmented Startups. * Project Type: Object Detection * Labeled/Annotated with: Bounding boxes
football
, player
This is a great starter-dataset for those wanting to test player and/or ball-tracking for football (soccer) games with the Deploy Tab, or the Deployment device and method of their choice.
Images can also be Cloned to another project to continue iterating on the project and model. World Cup, Premier League, La Liga, Major League Soccer (MLS) and/or Champions League computer vision projects, anyone?
Roboflow offers AutoML model training - Roboflow Train, and the ability to import and export up to 30 different annotation formats. Leaving you flexibility to deploy directly with a Roboflow Train model, or use Roboflow to prepare and manage datasets, and train and deploy with the custom model architecture of your choice + https://github.com/roboflow-ai/notebooks.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
These were published under the Creative Commons Attribution 4.0 International license (CC BY 4.0). See the full license text at https://creativecommons.org/licenses/by/4.0/.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
## Overview
TEZ_ROI_AUG is a dataset for object detection tasks - it contains Kidney Stones annotations for 778 images.
## Getting Started
You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
## License
This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset contains 6,000 example images generated with the process described in Roboflow's How to Create a Synthetic Dataset tutorial.
The images are composed of a background (randomly selected from Google's Open Images dataset) and a number of fruits (from Horea94's Fruit Classification Dataset) superimposed on top with a random orientation, scale, and color transformation. All images are 416x550 to simulate a smartphone aspect ratio.
To generate your own images, follow our tutorial or download the code.
Example:
https://blog.roboflow.ai/content/images/2020/04/synthetic-fruit-examples.jpg" alt="Example Image">
Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
License information was derived automatically
## Overview
舌像 is a dataset for instance segmentation tasks - it contains annotations for 3,373 images.
## Getting Started
You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
## License
This dataset is available under the [BY-NC-SA 4.0 license](https://creativecommons.org/licenses/BY-NC-SA 4.0).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
## Overview
Traffic Sign 40000 Images is a dataset for object detection tasks - it contains Traffic Sign 40000 Images annotations for 10,000 images.
## Getting Started
You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
## License
This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
## Overview
84 is a dataset for object detection tasks - it contains 1 annotations for 1,905 images.
## Getting Started
You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
## License
This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset was originally created by Khaingwintz. To see the current project, which may have been updated since this version, please go here.
This dataset is part of RF100, an Intel-sponsored initiative to create a new object detection benchmark for model generalizability.
Access the RF100 Github repo: https://github.com/roboflow-ai/roboflow-100-benchmark
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
## Overview
SHEL5K New is a dataset for object detection tasks - it contains Hard Hat annotations for 5,000 images.
## Getting Started
You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
## License
This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
## Overview
Box 6500images is a dataset for object detection tasks - it contains Box annotations for 3,969 images.
## Getting Started
You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
## License
This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
## Overview
Eyebrows is a dataset for object detection tasks - it contains Eyebrows annotations for 211 images.
## Getting Started
You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
## License
This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
## Overview
ROBOFLOW + IN HOUSE DATASET is a dataset for object detection tasks - it contains Cones Kmry annotations for 6,312 images.
## Getting Started
You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
## License
This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
## Overview
Marine Dataset is a dataset for object detection tasks - it contains Boats annotations for 5,488 images.
## Getting Started
You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
## License
This dataset is available under the [Public Domain license](https://creativecommons.org/licenses/Public Domain).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
## Overview
Pothole_Segmentation_YOLOv8 is a dataset for instance segmentation tasks - it contains Pothole annotations for 300 images.
## Getting Started
You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
## License
This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
## Overview
Fire Data Annotations is a dataset for object detection tasks - it contains Fire annotations for 1,942 images.
## Getting Started
You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
## License
This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset was originally created by Alex Hyams. To see the current project, which may have been updated since this version, please go here: https://universe.roboflow.com/alex-hyams-cosqx/cash-counter/.
This dataset is part of RF100, an Intel-sponsored initiative to create a new object detection benchmark for model generalizability.
Access the RF100 Github repo: https://github.com/roboflow-ai/roboflow-100-benchmark
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The Open Poetry Vision
dataset is a synthetic dataset created by Roboflow for OCR tasks.
It combines a random image from the Open Images Dataset with text primarily sampled from Gwern's GPT-2 Poetry project. Each image in the dataset contains between 1 and 5 strings in a variety of fonts and colors randomly positioned in the 512x512 canvas. The classes correspond to the font of the text.
Example Image:
https://i.imgur.com/sZT516a.png" alt="Example Image">
A common OCR workflow is to use a neural network to isolate text for input into traditional optical character recognition software. This dataset could make a good starting point for an OCR project like business card parsing or automated paper form-processing.
Alternatively, you could try your hand using this as a neural font identification dataset. Nvidia, amongst others, have had success with this task.
Use the fork
button to copy this dataset to your own Roboflow account and export it with new preprocessing settings (perhaps resized for your model's desired format or converted to grayscale), or additional augmentations to make your model generalize better. This particular dataset would be very well suited for Roboflow's new advanced Bounding Box Only Augmentations.
Roboflow makes managing, preprocessing, augmenting, and versioning datasets for computer vision seamless.
Developers reduce 50% of their code when using Roboflow's workflow, automate annotation quality assurance, save training time, and increase model reproducibility.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
The Hard Hat
dataset is an object detection dataset of workers in workplace settings that require a hard hat. Annotations also include examples of just "person" and "head," for when an individual may be present without a hard hart.
The original dataset has a 75/25 train-test split.
Example Image:
https://i.imgur.com/7spoIJT.png" alt="Example Image">
One could use this dataset to, for example, build a classifier of workers that are abiding safety code within a workplace versus those that may not be. It is also a good general dataset for practice.
Use the fork
or Download this Dataset
button to copy this dataset to your own Roboflow account and export it with new preprocessing settings (perhaps resized for your model's desired format or converted to grayscale), or additional augmentations to make your model generalize better. This particular dataset would be very well suited for Roboflow's new advanced Bounding Box Only Augmentations.
Image Preprocessing | Image Augmentation | Modify Classes
* v1
(resize-416x416-reflect): generated with the original 75/25 train-test split | No augmentations
* v2
(raw_75-25_trainTestSplit): generated with the original 75/25 train-test split | These are the raw, original images
* v3
(v3): generated with the original 75/25 train-test split | Modify Classes used to drop person
class | Preprocessing and Augmentation applied
* v5
(raw_HeadHelmetClasses): generated with a 70/20/10 train/valid/test split | Modify Classes used to drop person
class
* v8
(raw_HelmetClassOnly): generated with a 70/20/10 train/valid/test split | Modify Classes used to drop head
and person
classes
* v9
(raw_PersonClassOnly): generated with a 70/20/10 train/valid/test split | Modify Classes used to drop head
and helmet
classes
* v10
(raw_AllClasses): generated with a 70/20/10 train/valid/test split | These are the raw, original images
* v11
(augmented3x-AllClasses-FastModel): generated with a 70/20/10 train/valid/test split | Preprocessing and Augmentation applied | 3x image generation | Trained with Roboflow's Fast Model
* v12
(augmented3x-HeadHelmetClasses-FastModel): generated with a 70/20/10 train/valid/test split | Preprocessing and Augmentation applied, Modify Classes used to drop person
class | 3x image generation | Trained with Roboflow's Fast Model
* v13
(augmented3x-HeadHelmetClasses-AccurateModel): generated with a 70/20/10 train/valid/test split | Preprocessing and Augmentation applied, Modify Classes used to drop person
class | 3x image generation | Trained with Roboflow's Accurate Model
* v14
(raw_HeadClassOnly): generated with a 70/20/10 train/valid/test split | Modify Classes used to drop person
class, and remap/relabel helmet
class to head
Choosing Between Computer Vision Model Sizes | Roboflow Train
Roboflow makes managing, preprocessing, augmenting, and versioning datasets for computer vision seamless.
Developers reduce 50% of their code when using Roboflow's workflow, automate annotation quality assurance, save training time, and increase model reproducibility.