#About Dataset Content The dataset consists of two files, training and validation. Each folder contains 10 subforders labeled as n0~n9, each corresponding a species form Wikipedia's monkey cladogram. Images are 400x300 px or larger and JPEG format (almost 1400 images). Images were downloaded with help of the googliser open source code.
https://www.kaggle.com/datasets/slothkong/10-monkey-species
#Label mapping: n0, alouattapalliata n1, erythrocebuspatas n2, cacajaocalvus n3, macacafuscata n4, cebuellapygmea n5, cebuscapucinus n6, micoargentatus n7, saimirisciureus n8, aotusnigriceps n9, trachypithecusjohnii
For more information on the monkey species and number of images per class make sure to check monkey_labels.txt file. Aim This dataset is intended as a test case for fine-grain classification tasks, perhaps best used in combination with transfer learning. Hopefully someone can help us expand the number of classes or number of images.
#What I am trying
Apply different model and see how it goes.