Top 4 Datasets and Models

The datasets below can be used to train fine-tuned models for 4 detection. You can explore each dataset in your browser using Roboflow and export the dataset into one of many formats.

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Helmet and Vest Project project thumbnail
Classification
2.1k images
- Auto-orientation of pixel data (with EXIF-orientation stripping)- Resize to 640x640 (Stretch) - annotate, and create datasets - understand and search unstructured image data 22 24- Resize to 640x640 (Stretch) - annotate, and create datasets - understand and search unstructured image data 22 24 25- Resize to 640x640 (Stretch) - annotate, and create datasets - understand and search unstructured image data 24- Resize to 640x640 (Stretch) - annotate, and create datasets 22 24- Resize to 640x640 (Stretch) - annotate, and create datasets 24- Resize to 640x640 (Stretch) - annotate, and create datasets 24 The following pre-processing was applied to each image:- Resize to 640x640 (Stretch) - understand and search unstructured image data 22 24- Resize to 640x640 (Stretch) - understand and search unstructured image data 25 VEST are annotated in YOLOv8 format-- Resize to 640x640 (Stretch) - understand and search unstructured image data The dataset includes 2127 images- VEST are annotated in YOLOv8 format-- Resize to 640x640 (Stretch) 20 24- Resize to 640x640 (Stretch) 22 24- Resize to 640x640 (Stretch) 22 24 25- Resize to 640x640 (Stretch) 24- Resize to 640x640 (Stretch) 24 25- Resize to 640x640 (Stretch) 24 visit https:--github-com-roboflow-notebooks- annotate, and create datasets - use active learning to improve your dataset over time 24- annotate, and create datasets 24- collaborate with your team on computer vision projects- collaborate with your team on computer vision projects ============================== Roboflow is an end-to-end computer vision platform that helps you
mani project thumbnail
Object Detection
743 images2 models1
kiosk project thumbnail
Object Detection
697 images1 model6
idk project thumbnail
Object Detection
6.67k images2 models1
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