Guys, I'm looking for a bit of assistance. I'm a newbie programmer and one of the problems I'm having at the minute is trying to convert a black & white .jpg
image into a list which I can then modulate into an audio signal. This is part of a lager project to create a python SSTV program.
I have imported the PIL module and am trying to call the built-in function: list(im.getdata())
. When I call it, python crashes. Is there some way of breaking down the image (always 320x240) into 240 lines to make the computations easier? Or am I just calling the wrong function.
If anyone has any suggestions please fire away. If anyone has experience of generating modulated audio tones using python I would gladly accept any 'pearls of wisdom' they are willing to impart. Thanks in advance
This question is related to
python
image
python-imaging-library
Not PIL, but scipy.misc.imread
might still be interesting:
import scipy.misc
im = scipy.misc.imread('um_000000.png', flatten=False, mode='RGB')
print(im.shape)
gives
(480, 640, 3)
so it is (height, width, channels). So you can iterate over it by
for y in range(im.shape[0]):
for x in range(im.shape[1]):
color = tuple(im[y][x])
r, g, b = color
Looks like PILlow may have changed tostring()
to tobytes()
. When trying to extract RGBA pixels to get them into an OpenGL texture, the following worked for me (within the glTexImage2D
call which I omit for brevity).
from PIL import Image
img = Image.open("mandrill.png").rotate(180).transpose(Image.FLIP_LEFT_RIGHT)
# use img.convert("RGBA").tobytes() as texels
I assume you are getting an error like.. TypeError: 'PixelAccess' object is not iterable
...?
See the Image.load documentation for how to access pixels..
Basically, to get the list of pixels in an image, using PIL
:
from PIL import Image
i = Image.open("myfile.png")
pixels = i.load() # this is not a list, nor is it list()'able
width, height = i.size
all_pixels = []
for x in range(width):
for y in range(height):
cpixel = pixels[x, y]
all_pixels.append(cpixel)
That appends every pixel to the all_pixels
- if the file is an RGB image (even if it only contains a black-and-white image) these will be a tuple, for example:
(255, 255, 255)
To convert the image to monochrome, you just average the three values - so, the last three lines of code would become..
cpixel = pixels[x, y]
bw_value = int(round(sum(cpixel) / float(len(cpixel))))
# the above could probably be bw_value = sum(cpixel)/len(cpixel)
all_pixels.append(bw_value)
Or to get the luminance (weighted average):
cpixel = pixels[x, y]
luma = (0.3 * cpixel[0]) + (0.59 * cpixel[1]) + (0.11 * cpixel[2])
all_pixels.append(luma)
Or pure 1-bit looking black and white:
cpixel = pixels[x, y]
if round(sum(cpixel)) / float(len(cpixel)) > 127:
all_pixels.append(255)
else:
all_pixels.append(0)
There is probably methods within PIL to do such RGB -> BW
conversions quicker, but this works, and isn't particularly slow.
If you only want to perform calculations on each row, you could skip adding all the pixels to an intermediate list.. For example, to calculate the average value of each row:
from PIL import Image
i = Image.open("myfile.png")
pixels = i.load() # this is not a list
width, height = i.size
row_averages = []
for y in range(height):
cur_row_ttl = 0
for x in range(width):
cur_pixel = pixels[x, y]
cur_pixel_mono = sum(cur_pixel) / len(cur_pixel)
cur_row_ttl += cur_pixel_mono
cur_row_avg = cur_row_ttl / width
row_averages.append(cur_row_avg)
print "Brighest row:",
print max(row_averages)
pixVals = list(pilImg.getdata())
output is a list of all RGB values from the picture:
[(248, 246, 247), (246, 248, 247), (244, 248, 247), (244, 248, 247), (246, 248, 247), (248, 246, 247), (250, 246, 247), (251, 245, 247), (253, 244, 247), (254, 243, 247)]
If you have numpy installed you can try:
data = numpy.asarray(im)
(I say "try" here, because it's unclear why getdata()
isn't working for you, and I don't know whether asarray
uses getdata, but it's worth a test.)
Or if you want to count white or black pixels
This is also a solution:
from PIL import Image
import operator
img = Image.open("your_file.png").convert('1')
black, white = img.getcolors()
print black[0]
print white[0]
As I commented above, problem seems to be the conversion from PIL internal list format to a standard python list type. I've found that Image.tostring() is much faster, and depending on your needs it might be enough. In my case, I needed to calculate the CRC32 digest of image data, and it suited fine.
If you need to perform more complex calculations, tom10 response involving numpy might be what you need.
Python shouldn't crash when you call getdata(). The image might be corrupted or there is something wrong with your PIL installation. Try it with another image or post the image you are using.
This should break down the image the way you want:
from PIL import Image
im = Image.open('um_000000.png')
pixels = list(im.getdata())
width, height = im.size
pixels = [pixels[i * width:(i + 1) * width] for i in xrange(height)]
data = numpy.asarray(im)
Notice:In PIL, img is RGBA. In cv2, img is BGRA.
My robust solution:
def cv_from_pil_img(pil_img):
assert pil_img.mode=="RGBA"
return cv2.cvtColor(np.array(pil_img), cv2.COLOR_RGBA2BGRA)
Source: Stackoverflow.com