使用 PIL 从字典创建图像
Creating an image from a dictionary using PIL
我有一个字典，可以将坐标元组（在 (0,0) 到 (199, 199) 范围内）映射到灰度值（0 到 255 之间的整数）。是否有创建 PIL 图像的好方法在指定的坐标处有指定的值？我更喜欢只使用 PIL 的解决方案而不是使用 scipy.
的解决方案
您可以尝试image.putpixel()更改特定位置像素的颜色。示例代码-
from PIL import Image
from random import randint
d = {(x,y):randint(0,255) for x in range(200) for y in range(200)}
im = Image.new('L',(200,200))
for i in d:
im.putpixel(i,d[i])
im.save('blah.png')
它给了我这样的结果 -
您可以使用 putpixel() 来完成，但这可能涉及数以万计的调用。这有多重要取决于字典中定义了多少个坐标元组。我已经包含了每个当前答案中显示的方法进行比较（包括在添加任何基准测试之前我自己的方法，但刚才我对它初始化数据缓冲区的方式做了一个小改动，这明显加快了速度）。
为了营造公平的竞争环境，出于测试目的，输入字典仅随机选择图像中 ½ 的可能像素进行定义，并允许将其余像素设置为默认 background 颜色。 Anand S Kumar 的回答目前不支持后者，但下面显示的稍作修改的版本支持。
所有人都从数据中生成相同的图像。
from __future__ import print_function
import sys
from textwrap import dedent
import timeit
N = 100 # number of executions of each algorithm
R = 3 # number of repeations of executions
# common setup for all algorithms - is not included in algorithm timing
setup = dedent("""
from random import randint, sample, seed
from PIL import Image
seed(42)
background = 0 # default color of pixels not defined in dictionary
width, height = 200, 200
# create test dict of input data defining half of the pixel coords in image
coords = sample([(x,y) for x in xrange(width) for y in xrange(height)],
width * height // 2)
d = {coord: randint(0, 255) for coord in coords}
""")
algorithms = {
"Anand S Kumar": dedent("""
im = Image.new('L', (width, height), color=background) # set bgrd
for i in d:
im.putpixel(i, d[i])
"""),
"martineau": dedent("""
data = bytearray([background] * width * height)
for (x, y), v in d.iteritems():
data[x + y*width] = v
im = Image.frombytes('L', (width, height), str(data))
"""),
"PM 2Ring": dedent("""
data = [background] * width * height
for i in d:
x, y = i
data[x + y * width] = d[i]
im = Image.new('L', (width, height))
im.putdata(data)
"""),
}
# execute and time algorithms, collecting results
timings = [
(label,
min(timeit.repeat(algorithms[label], setup=setup, repeat=R, number=N)),
) for label in algorithms
]
print('fastest to slowest execution speeds (Python {}.{}.{})\n'.format(
*sys.version_info[:3]),
' ({:,d} executions, best of {:d} repetitions)\n'.format(N, R))
longest = max(len(timing[0]) for timing in timings) # length of longest label
ranked = sorted(timings, key=lambda t: t[1]) # ascending sort by execution time
fastest = ranked[0][1]
for timing in ranked:
print("{:>{width}} : {:9.6f} secs, rel speed {:4.2f}x, {:6.2f}% slower".
format(timing[0], timing[1], round(timing[1]/fastest, 2),
round((timing[1]/fastest - 1) * 100, 2), width=longest))
输出：
fastest to slowest execution speeds (Python 2.7.10)
(100 executions, best of 3 repetitions)
martineau : 0.255203 secs, rel speed 1.00x, 0.00% slower
PM 2Ring : 0.307024 secs, rel speed 1.20x, 20.31% slower
Anand S Kumar : 1.835997 secs, rel speed 7.19x, 619.43% slower
正如 martineau 所建议的那样，当您修改一些随机像素时，putpixel() 是可以的，但对于构建整个图像来说效率不高。我的方法与他的类似，只是我使用了一个整数列表和 .putdata()。这里有一些代码来测试这 3 种不同的方法。
from PIL import Image
from random import seed, randint
width, height = 200, 200
background = 0
seed(42)
d = dict(((x, y), randint(0, 255)) for x in range(width) for y in range(height))
algorithm = 2
print('Algorithm', algorithm)
if algorithm == 0:
im = Image.new('L', (width, height))
for i in d:
im.putpixel(i, d[i])
elif algorithm == 1:
buff = bytearray((background for _ in xrange(width * height)))
for (x,y), v in d.items():
buff[y*width + x] = v
im = Image.frombytes('L', (width,height), str(buff))
elif algorithm == 2:
data = [background] * width * height
for i in d:
x, y = i
data[x + y * width] = d[i]
im = Image.new('L', (width, height))
im.putdata(data)
#im.show()
fname = 'qrand%d.png' % algorithm
im.save(fname)
print(fname, 'saved')
这是我的 2GHz 机器上的典型时序 运行 Python 2.6.6
$ time ./qtest.py
Algorithm 0
qrand0.png saved
real 0m0.926s
user 0m0.768s
sys 0m0.040s
$ time ./qtest.py
Algorithm 1
qrand1.png saved
real 0m0.733s
user 0m0.548s
sys 0m0.020s
$ time ./qtest.py
Algorithm 2
qrand2.png saved
real 0m0.638s
user 0m0.520s
sys 0m0.032s
我有一个字典，可以将坐标元组（在 (0,0) 到 (199, 199) 范围内）映射到灰度值（0 到 255 之间的整数）。是否有创建 PIL 图像的好方法在指定的坐标处有指定的值？我更喜欢只使用 PIL 的解决方案而不是使用 scipy.
的解决方案您可以尝试image.putpixel()更改特定位置像素的颜色。示例代码-
from PIL import Image
from random import randint
d = {(x,y):randint(0,255) for x in range(200) for y in range(200)}
im = Image.new('L',(200,200))
for i in d:
im.putpixel(i,d[i])
im.save('blah.png')
它给了我这样的结果 -
您可以使用 putpixel() 来完成，但这可能涉及数以万计的调用。这有多重要取决于字典中定义了多少个坐标元组。我已经包含了每个当前答案中显示的方法进行比较（包括在添加任何基准测试之前我自己的方法，但刚才我对它初始化数据缓冲区的方式做了一个小改动，这明显加快了速度）。
为了营造公平的竞争环境，出于测试目的，输入字典仅随机选择图像中 ½ 的可能像素进行定义，并允许将其余像素设置为默认 background 颜色。 Anand S Kumar 的回答目前不支持后者，但下面显示的稍作修改的版本支持。
所有人都从数据中生成相同的图像。
from __future__ import print_function
import sys
from textwrap import dedent
import timeit
N = 100 # number of executions of each algorithm
R = 3 # number of repeations of executions
# common setup for all algorithms - is not included in algorithm timing
setup = dedent("""
from random import randint, sample, seed
from PIL import Image
seed(42)
background = 0 # default color of pixels not defined in dictionary
width, height = 200, 200
# create test dict of input data defining half of the pixel coords in image
coords = sample([(x,y) for x in xrange(width) for y in xrange(height)],
width * height // 2)
d = {coord: randint(0, 255) for coord in coords}
""")
algorithms = {
"Anand S Kumar": dedent("""
im = Image.new('L', (width, height), color=background) # set bgrd
for i in d:
im.putpixel(i, d[i])
"""),
"martineau": dedent("""
data = bytearray([background] * width * height)
for (x, y), v in d.iteritems():
data[x + y*width] = v
im = Image.frombytes('L', (width, height), str(data))
"""),
"PM 2Ring": dedent("""
data = [background] * width * height
for i in d:
x, y = i
data[x + y * width] = d[i]
im = Image.new('L', (width, height))
im.putdata(data)
"""),
}
# execute and time algorithms, collecting results
timings = [
(label,
min(timeit.repeat(algorithms[label], setup=setup, repeat=R, number=N)),
) for label in algorithms
]
print('fastest to slowest execution speeds (Python {}.{}.{})\n'.format(
*sys.version_info[:3]),
' ({:,d} executions, best of {:d} repetitions)\n'.format(N, R))
longest = max(len(timing[0]) for timing in timings) # length of longest label
ranked = sorted(timings, key=lambda t: t[1]) # ascending sort by execution time
fastest = ranked[0][1]
for timing in ranked:
print("{:>{width}} : {:9.6f} secs, rel speed {:4.2f}x, {:6.2f}% slower".
format(timing[0], timing[1], round(timing[1]/fastest, 2),
round((timing[1]/fastest - 1) * 100, 2), width=longest))
输出：
fastest to slowest execution speeds (Python 2.7.10)
(100 executions, best of 3 repetitions)
martineau : 0.255203 secs, rel speed 1.00x, 0.00% slower
PM 2Ring : 0.307024 secs, rel speed 1.20x, 20.31% slower
Anand S Kumar : 1.835997 secs, rel speed 7.19x, 619.43% slower
正如 martineau 所建议的那样，当您修改一些随机像素时，putpixel() 是可以的，但对于构建整个图像来说效率不高。我的方法与他的类似，只是我使用了一个整数列表和 .putdata()。这里有一些代码来测试这 3 种不同的方法。
from PIL import Image
from random import seed, randint
width, height = 200, 200
background = 0
seed(42)
d = dict(((x, y), randint(0, 255)) for x in range(width) for y in range(height))
algorithm = 2
print('Algorithm', algorithm)
if algorithm == 0:
im = Image.new('L', (width, height))
for i in d:
im.putpixel(i, d[i])
elif algorithm == 1:
buff = bytearray((background for _ in xrange(width * height)))
for (x,y), v in d.items():
buff[y*width + x] = v
im = Image.frombytes('L', (width,height), str(buff))
elif algorithm == 2:
data = [background] * width * height
for i in d:
x, y = i
data[x + y * width] = d[i]
im = Image.new('L', (width, height))
im.putdata(data)
#im.show()
fname = 'qrand%d.png' % algorithm
im.save(fname)
print(fname, 'saved')
这是我的 2GHz 机器上的典型时序 运行 Python 2.6.6
$ time ./qtest.py
Algorithm 0
qrand0.png saved
real 0m0.926s
user 0m0.768s
sys 0m0.040s
$ time ./qtest.py
Algorithm 1
qrand1.png saved
real 0m0.733s
user 0m0.548s
sys 0m0.020s
$ time ./qtest.py
Algorithm 2
qrand2.png saved
real 0m0.638s
user 0m0.520s
sys 0m0.032s