Top With Datasets and Models
The datasets below can be used to train fine-tuned models for with 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 with datasets below.
by PRoject
2905 images 1917 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
296 images 2 classes
3023 images 1935 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
1505 images 1813 classes
by KARY
1270 images 51 classes
* 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 time 19 20 21 22 23 24 25 26 27 28 29 30
by SnapCycle
2010 images 13 classes
by kary
400 images 40 classes
* 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 time 19 ============================== For state of the art Computer Vision training notebooks you can use with this dataset, IRIS RECONIGTION PFE_essai - v1 IRISDATA_COMPL IRIS-83ep are annotated in YOLOv8 format. IRIS52 IRIS53 IRIS54 IRIS55 IRIS56 IRIS57 IRIS59
by HADJEM
1238 images 103 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Random brigthness adjustment of between -1 and +1 percent * Random rotation of between -1 and +1 degrees * Random shear of between -1° to +1° horizontally and -0° to +0° 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 time 22 23 24 25 26 27 28 29 30
4390 images 16 classes
by ppetesting
494 images 3 classes
by EPI
216 images 13 classes
607 images 3 classes
280 images 2 classes
153 images 4 classes
by ocrdetection
325 images 132 classes
dot * 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 time - 0 1 19 2 20 21 22 23 24 25
by UNITEN
4462 images 6 classes
by ppetesting
746 images 6 classes