Mercurial > pylearn
view pylearn/datasets/flickr.py @ 600:e56303df3c77
initial flickr
author | James Bergstra <bergstrj@iro.umontreal.ca> |
---|---|
date | Wed, 14 Jan 2009 15:54:39 -0500 |
parents | |
children | fd95ff96dd47 |
line wrap: on
line source
""" Routines to load variations on the Flickr image dataset. """ from __future__ import absolute_import import os import numpy from ..io import filetensor from .config import data_root from .dataset import Dataset def test_10class(): #TODO: make path an option, #TODO: make default path relative to data_root() f = open('flickr_10classes_test.ft') data = filetensor.read(f) return data.T.copy() #put in to one example per row, row major def train_10class(): #TODO: make path an option, #TODO: make default path relative to data_root() f = open('flickr_10classes_train.ft') data = filetensor.read(f) return data.T.copy() #put in to one example per row, row major def valid_10class(): #TODO: make path an option, #TODO: make default path relative to data_root() f = open('flickr_10classes_valid.ft') data = filetensor.read(f) return data.T.copy() #put in to one example per row, row major def basic_10class(): """Return the basic flickr image classification problem. The images are 75x75, and there are 7500 training examples. """ train = train_10class() valid = valid_10class() test = test_10class() rval = Dataset() rval.train = Dataset.Obj( x=train[:, 0:-1], y=numpy.asarray(train[:, -1], dtype='int64')) rval.valid = Dataset.Obj( x=valid[:, 0:-1], y=numpy.asarray(valid[:, -1], dtype='int64')) rval.test = Dataset.Obj( x=test[:, 0:-1], y=numpy.asarray(test[:, -1], dtype='int64')) rval.n_classes = 10 rval.img_shape = (75,75) return rval def translations_10class(): raise NotImplementedError('TODO')