Top Up Datasets and Models
The datasets below can be used to train fine-tuned models for up detection. You can explore each dataset in your browser using Roboflow and export the dataset into one of many formats.
At the bottom of this page, we have guides on how to train a model using the up datasets below.
2564 images 58 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Resize to 1000x1000 (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 19 20 21 22 23 24 25 26 27 28 29 30
by Yolo
122 images 122 classes
All motor vehicles prohibited Animals Axle load limit Barrier Blind persons likely on road ahead Built-up area Bullock cart and hand cart prohibited Bullock cart prohibited Bump Chevron Children Compulsory ahead Compulsory ahead or turn left Compulsory ahead or turn right Compulsory cycle track Compulsory keep left Compulsory minimum speed Compulsory sound horn Compulsory turn left Compulsory turn left ahead
by PRoject
3005 images 1919 classes
bottle water (a) Benzyl Penicillin (a) Oxytetracycline (a) Propanolol (b) Benzathine Benzyl Penicillin (b) Chlortetracycline (b) Isopreterenol (c) Doxycycline (c) Procane Benzyl Penicillin (c) Sotalol (d) Dichloro Isopreterenol (d) Phenoxymethylpenicilin (e) cloxacillin (f) Ampicillin (g) Amoxycilin + 0.25mg 0.2mg 0.3mg
by class
77 images 112 classes
179 images 8 classes
3023 images 1940 classes
bottle water (a) Benzyl Penicillin (a) Oxytetracycline (a) Propanolol (b) Benzathine Benzyl Penicillin (b) Chlortetracycline (b) Isopreterenol (c) Doxycycline (c) Procane Benzyl Penicillin (c) Sotalol (d) Dichloro Isopreterenol (d) Phenoxymethylpenicilin (e) cloxacillin (f) Ampicillin (g) Amoxycilin + 0 0.25mg 0.2mg
1149 images 7961 classes
1000 images 5305 classes
6536 images 6 classes
by Ajmodel
1470 images 10 classes
4496 images 10 classes
by go4av05
8659 images 40 classes
* Random Gaussian blur of between 0 and 2.5 pixels * Random brigthness adjustment of between -25 and +25 percent * Random exposure adjustment of between -25 and +25 percent * 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 time 17 18 19 20 21 22 23 24 25 26
889 images 4 classes