From the training set I took a image('img') of size (3,32,32). I have used plt.imshow(img.T). The image is not clear. Now changes I have to make to image('img') to make it more clearly visible. Thanks.
CIFAR-10 Photo Classification Dataset The dataset is comprised of 60,000 32×32 pixel color photographs of objects from 10 classes, such as frogs, birds, cats, ships, etc. The class labels and their standard associated integer values are listed below.
CIFAR-10 is a labeled subset of the 80 million tiny images dataset.
This file reads the cifar10 dataset and plots individual images using matplotlib
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import _pickle as pickle
import argparse
import numpy as np
import os
import matplotlib.pyplot as plt
cifar10 = "./cifar-10-batches-py/"
parser = argparse.ArgumentParser("Plot training images in cifar10 dataset")
parser.add_argument("-i", "--image", type=int, default=0,
help="Index of the image in cifar10. In range [0, 49999]")
args = parser.parse_args()
def unpickle(file):
with open(file, 'rb') as fo:
data = pickle.load(fo, encoding='bytes')
return data
def cifar10_plot(data, meta, im_idx=0):
im = data[b'data'][im_idx, :]
im_r = im[0:1024].reshape(32, 32)
im_g = im[1024:2048].reshape(32, 32)
im_b = im[2048:].reshape(32, 32)
img = np.dstack((im_r, im_g, im_b))
print("shape: ", img.shape)
print("label: ", data[b'labels'][im_idx])
print("category:", meta[b'label_names'][data[b'labels'][im_idx]])
plt.imshow(img)
plt.show()
def main():
batch = (args.image // 10000) + 1
idx = args.image - (batch-1)*10000
data = unpickle(os.path.join(cifar10, "data_batch_" + str(batch)))
meta = unpickle(os.path.join(cifar10, "batches.meta"))
cifar10_plot(data, meta, im_idx=idx)
if __name__ == "__main__":
main()
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