转载自：http://blog.csdn.net/qq_16949707/article/details/56306720import os
import glob
image_dir = "D:\\data\\ADEChallengeData2016"
file_glob = os.path.join(image_dir, "images", "training", '*.' + 'jpg')
file_list = []
file_list.extend(glob.glob(file_glob))
file_list_test = file_list[0:10]
import random
random.shuffle(file_list_test)
import numpy as np
import scipy.misc as misc
def read_and_transform(filename):
image = misc.imread(filename)
resize_image = misc.imresize(image,[224, 224], interp='nearest')
return np.array(resize_image)
images = np.array([read_and_transform(filename) for filename in file_list_test])
def find_annotations_image_path(image_path):
return image_path.replace("images","annotations").replace("jpg","png")
annotations_file_list_test = [find_annotations_image_path(image_path) for image_path in file_list_test]
annotations = np.array([np.expand_dims(read_and_transform(filename), axis=3) for filename in annotations_file_list_test])
batch_offset = 0
def next_batch(batch_size,batch_offset,images,annotations,epochs_completed):
start = batch_offset
batch_offset += batch_size
if batch_offset > images.shape[0]:
epochs_completed += 1
print("****************** Epochs completed: " + str(epochs_completed) + "******************")
perm = np.arange(images.shape[0])
np.random.shuffle(perm)
images = images[perm]
annotations = annotations[perm]
start = 0
batch_offset = batch_size
end = batch_offset
print start,end
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2 测试
2.1 测试next_batch送数据
next_batch(2,0,images,annotations,0)
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next_batch(2,2,images,annotations,0)
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next_batch(2,10,images,annotations,0)
****************** Epochs completed: 1******************
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2.2 测试shuffle打乱数据
perm = np.arange(images.shape[0])
print perm
[0 1 2 3 4 5 6 7 8 9]
np.random.shuffle(perm)
print perm
[5 3 9 4 8 6 2 1 7 0]
images[0]
array([[[ 92, 57, 27],
[181, 145, 113],
[227, 189, 153],
...,
[100, 77, 71],
[200, 177, 171],
[194, 174, 167]],
[[ 82, 45, 18],
[ 85, 46, 17],
[176, 136, 101],
...,
[200, 177, 171],
[192, 172, 165],
[180, 160, 153]],
[[ 88, 47, 25],
[ 93, 53, 28],
[131, 90, 60],
...,
[202, 182, 175],
[201, 181, 174],
[163, 144, 137]],
...,
[[ 99, 48, 31],
[ 84, 33, 16],
[ 81, 30, 13],
...,
[170, 134, 108],
[166, 130, 104],
[163, 127, 101]],
[[ 67, 16, 0],
[ 98, 47, 30],
[ 97, 46, 29],
...,
[168, 132, 106],
[173, 137, 111],
[168, 132, 106]],
[[ 62, 11, 0],
[ 83, 32, 15],
[ 65, 14, 0],
...,
[169, 133, 107],
[164, 128, 102],
[165, 129, 103]]], dtype=uint8)
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images = images[perm]
annotations = annotations[perm]
images[0]
array([[[ 50, 75, 80],
[ 50, 75, 80],
[ 51, 76, 81],
...,
[135, 165, 176],
[133, 163, 174],
[133, 163, 174]],
[[ 50, 75, 80],
[ 50, 75, 80],
[ 51, 76, 81],
...,
[135, 165, 176],
[133, 163, 174],
[133, 163, 174]],
[[ 49, 74, 79],
[ 49, 74, 79],
[ 50, 75, 80],
...,
[135, 165, 176],
[133, 163, 174],
[133, 163, 174]],
...,
[[ 4, 16, 12],
[ 4, 16, 12],
[ 4, 16, 12],
...,
[176, 196, 205],
[177, 197, 206],
[178, 198, 207]],
[[ 4, 16, 12],
[ 4, 16, 12],
[ 4, 16, 12],
...,
[175, 195, 204],
[176, 196, 205],
[176, 196, 205]],
[[ 4, 16, 12],
[ 4, 16, 12],
[ 4, 16, 12],
...,
[177, 197, 206],
[176, 196, 205],
[176, 196, 205]]], dtype=uint8)
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2.3 测试np.expand_dims
annotations1 = np.array([read_and_transform(filename) for filename in annotations_file_list_test])
annotations1.shape
(10L, 224L, 224L)
annotations.shape
(10L, 224L, 224L, 1L)
annotations_file_list_test[0]
'D:\\data\\ADEChallengeData2016\\annotations\\training\\ADE_train_00000007.png'
file_list_test[0]
'D:\\data\\ADEChallengeData2016\\images\\training\\ADE_train_00000007.jpg'
image_path = annotations_file_list_test[0]
annotations_image = read_and_transform(image_path)
annotations_image.shape
(224L, 224L)
annotations_image
array([[ 0, 1, 1, ..., 6, 6, 6],
[135, 135, 135, ..., 6, 6, 6],
[ 0, 135, 135, ..., 6, 6, 6],
...,
[ 0, 11, 11, ..., 4, 4, 4],
[ 0, 11, 11, ..., 4, 4, 4],
[ 0, 11, 11, ..., 4, 4, 4]], dtype=uint8)
np.expand_dims(annotations_image,axis=3)
array([[[ 0],
[ 1],
[ 1],
...,
[ 6],
[ 6],
[ 6]],
[[135],
[135],
[135],
...,
[ 6],
[ 6],
[ 6]],
[[ 0],
[135],
[135],
...,
[ 6],
[ 6],
[ 6]],
...,
[[ 0],
[ 11],
[ 11],
...,
[ 4],
[ 4],
[ 4]],
[[ 0],
[ 11],
[ 11],
...,
[ 4],
[ 4],
[ 4]],
[[ 0],
[ 11],
[ 11],
...,
[ 4],
[ 4],
[ 4]]], dtype=uint8)
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image_path.replace("images","annotations").replace("jpg","png")
'D:\\data\\ADEChallengeData2016\\annotations\\training\\ADE_train_00000007.png'
annotations_image_path = image_path.replace("images","annotations").replace("jpg","png")
annotations_image_dir = "D:\\data\\ADEChallengeData2016"
annotations_file_glob = os.path.join(image_dir, "annotations", "training", '*.' + 'png')
annotations_file_list = []
annotations_file_list.extend(glob.glob(file_glob))
len(annotations_file_list)
20210
annotations = np.array([np.expand_dims(read_and_transform(filename), axis=3) for filename in file_list_test])
annotations.shape
(10L, 224L, 224L, 3L, 1L)
len(images)
10
image_array = read_and_transform(file_list_test[0])
len(image_array)
224
image_array[0][:][:].shape
(224L, 3L)
image_array.shape
(224L, 224L, 3L)
2.4 测试misc的imread以及imresize
image = misc.imread(file_list_test[0])
image.shape
(735L, 512L, 3L)
resize_image = misc.imresize(image,[224, 224], interp='nearest')
import matplotlib.pyplot as plt
plt.figure()
plt.imshow(image)
plt.show()
import matplotlib.pyplot as plt
plt.figure()
plt.imshow(resize_image)
plt.show()
misc.imshow(image)
---------------------------------------------------------------------------
RuntimeError Traceback (most recent call last)
<ipython-input-15-69d081592f64> in <module>()
----> 1 misc.imshow(image)
D:\software\Anaconda2\lib\site-packages\scipy\misc\pilutil.pyc in imshow(arr)
440 os.unlink(fname)
441 if status != 0:
--> 442 raise RuntimeError('Could not execute image viewer.')
443
444
RuntimeError: Could not execute image viewer.