| 47 | return Xtrain, Ytrain, Xtest, Ytest |
| 48 | |
| 49 | def getCIFAR10(): |
| 50 | Xtrain = np.zeros((50000, 32, 32, 3), dtype=np.uint8) |
| 51 | Ytrain = np.zeros(50000, dtype=np.uint8) |
| 52 | |
| 53 | # train data |
| 54 | for i in range(5): |
| 55 | fn = 'data_batch_%s.mat' % (i+1) |
| 56 | d = loadmat('../large_files/cifar-10-batches-mat/' + fn) |
| 57 | x = d['data'] |
| 58 | y = d['labels'].flatten() |
| 59 | x = x.reshape(10000, 3, 32, 32) |
| 60 | x = np.transpose(x, (0, 2, 3, 1)) |
| 61 | Xtrain[i*10000:(i+1)*10000] = x |
| 62 | Ytrain[i*10000:(i+1)*10000] = y |
| 63 | |
| 64 | # test data |
| 65 | d = loadmat('../large_files/cifar-10-batches-mat/test_batch.mat') |
| 66 | x = d['data'] |
| 67 | y = d['labels'].flatten() |
| 68 | x = x.reshape(10000, 3, 32, 32) |
| 69 | x = np.transpose(x, (0, 2, 3, 1)) |
| 70 | Xtest = x |
| 71 | Ytest = y |
| 72 | |
| 73 | return Xtrain, Ytrain, Xtest, Ytest |
| 74 | |