Here's some code that does the trick.
It returns a tuple:
(coefficient, (luminance_coefficient,luminance_error),
(chrominance_coefficient,chrominance_error))
Note:
- The 2nd and 3rd returned items are only useful if you're interested in the
error (sometimes the error is 0 if the program used a JPEG table that is the
same as the one used by PIL).
- Fredrik: You can freely use the code and embed it in PIL if you're satisfied
with its quality
Code:
def get_jpeg_quantization_tables(f):
"""Returns the JPEG quantization tables of a filename or file descriptor"""
from functools import partial
import Image
import numpy as N
fd = Image.open(f)
if fd.format == 'BMP':
return N.ones((8,8)),N.ones((8,8))
q = fd.quantization
ql,qc =
map(partial(N.array,dtype='uint8'),(q.get(0,N.zeros(64)),q.get(1,N.zeros(64))))
# Now reorder the JPEG quantification coefficients as 8x8 matrices
jpeg_natural_order = N.array([ 0, 1, 8, 16, 9, 2, 3, 10, 17, 24, 32,
25, 18, 11, 4, 5, 12,
19, 26, 33, 40, 48, 41, 34, 27, 20, 13, 6,
7, 14, 21, 28, 35, 42,
49, 56, 57, 50, 43, 36, 29, 22, 15, 23, 30,
37, 44, 51, 58, 59, 52,
45, 38, 31, 39, 46, 53, 60, 61, 54, 47, 55,
62, 63])
rql = N.zeros(64,'f')
rqc = N.zeros(64,'f')
for x,y in N.ndenumerate(jpeg_natural_order):
rql[y] = ql[x]
rqc[y] = qc[x]
return rql.reshape(8,8),rqc.reshape(8,8) # Luminance/Chrominance
def guess_jpeg_quality(f,ctables=[]):
from StringIO import StringIO
import numpy as N
import Image
# Compute the tables for quality = 1..100 by saving fakes files in memory
if not ctables:
tables = N.zeros((100,2,8,8),'f')
for x in xrange(100):
fd = StringIO()
Image.new('RGB',(64,64)).save(fd,"jpeg",quality=1+x)
fd.seek(0)
ql,qc = get_jpeg_quantization_tables(fd)
tables[x][0] = ql
tables[x][1] = qc
ctables.append(tables)
else:
tables = ctables[0]
# Use a weighting matrix w to put more emphasis on the comparison of lower
DCT harmonics
w = 1./N.outer(1+N.arange(8)/7.,1+N.arange(8)/7.)
ql,qc = get_jpeg_quantization_tables(f)
# Compute errors on Luminance and Chrominance tables
errsl,errsc = [],[]
for x in xrange(100):
errsl.append((N.square((ql-tables[x][0])*w).mean(),x))
errsc.append((N.square((qc-tables[x][1])*w).mean(),x))
# Select minimal error coefficients
lmin = min(errsl)
cmin = min(errsc)
# Weight coefficients average (more emphasis put on luminance since it
affects most visual perception)
q = int(round(lmin[1]*.8 + cmin[1]*.2))
return q,lmin,cmin
________________________________
From: Fredrik Lundh <fred...@pythonware.com>
To: qiaohl <qia...@ucweb.com>
Cc: image-sig <image-sig@python.org>
Sent: Monday, September 28, 2009 5:43:00 AM
Subject: Re: [Image-SIG] How to get quality of picture
The quality setting is used to create a quantization table which is
then used by the compression algorithm. There's no pre-defined
mapping between quality and the contents of the quantization table for
JPEG (different implementations do different things), but some
applications attempt to guess by comparing the quantization tables in
the file with known mapping algorithms. I'm not aware of any such
code for Python.
If you want to tinker with this, you can access the quantization table
of an opened JPEG file via the "quantization" attribute.
</F>
On Mon, Sep 28, 2009 at 9:08 AM, qiaohl <qia...@ucweb.com> wrote:
> Hi,all
> Is there any function in PIL to get the value of JPEG quality(1-100)? I
> know there are functions to set this value, But I found no function to get
> this value of an existing JPEG file.
>
> Thanks!
>
>
> 2009-09-28
> ________________________________
> qiaohl
> _______________________________________________
> Image-SIG maillist - Image-SIG@python.org
> http://mail.python.org/mailman/listinfo/image-sig
>
>
_______________________________________________
Image-SIG maillist - Image-SIG@python.org
http://mail.python.org/mailman/listinfo/image-sig
_______________________________________________
Image-SIG maillist - Image-SIG@python.org
http://mail.python.org/mailman/listinfo/image-sig
