Related Objects of Interest: female age- 1, female age- 2, female age- 22, female age- 24, female age- 25, female age- 28, female age- 30, female age- 35, female age- 45, female age- 50
Top 30 Computer Vision Models
The models below have been fine-tuned for various 30 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 30 detection model.
At the bottom of this page, we have guides on how to count 30s in images and videos.
492 images 20 classes
Arret et stationnement interdit Cedez le passage Direction obligatoire Entree de tunnel Interdit au poids lourds Limiteur de vitesse Panneaux de Renseignements Passage interdit Passage obliges pour cyclistes Passage pieton Rond-points Station services Stationnement interdit Stop Vitesse limitee à Vitesse limitee à 30 Vitesse limitee à 40 Vitesse limitee à 60 Vitesse limitee à 70 Zone reservèes
5606 images 36 classes
132 images 11 classes
1371 images 29 classes
3006 images 38 classes
* 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) 13 14 15 16 17 18 19 20 21 22 23 24 25 26
3006 images 38 classes
* 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 time 23 24 25 26 27 28 29 30
2525 images 17 classes
1994 images 37 classes
* 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 time 24 25 26 27 28 29 30 31
by Henk Bert
2476 images 28 classes
by Palles
2477 images 28 classes