Improvement: Add predefined blur kernels

- Add a few predefined blur kernels, requested by jerri in #104.

- Add compton-convgen.py to generate blur kernels.
This commit is contained in:
Richard Grenville 2013-04-29 22:42:46 +08:00
parent abd559c512
commit a3f6f4442b
2 changed files with 161 additions and 1 deletions

132
bin/compton-convgen.py Executable file
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@ -0,0 +1,132 @@
#! /usr/bin/env python3
# -*- coding: utf-8 -*-
# vim:fileencoding=utf-8
import math, argparse
class CGError(Exception):
def __init__(self, value):
self.value = value
def __str__(self):
return repr(self.value)
class CGBadArg(CGError): pass
class CGInternal(CGError): pass
def mbuild(width, height):
"""Build a NxN matrix filled with 0."""
result = list()
for i in range(height):
result.append(list())
for j in range(width):
result[i].append(0.0)
return result
def mdump(matrix):
"""Dump a matrix in natural format."""
for col in matrix:
print("[ ", end = '');
for ele in col:
print(format(ele, "13.6g") + ", ", end = " ")
print("],")
def mdumpcompton(matrix):
"""Dump a matrix in compton's format."""
width = len(matrix[0])
height = len(matrix)
print("{},{},".format(width, height), end = '')
for i in range(height):
for j in range(width):
if int(height / 2) == i and int(width / 2) == j:
continue;
print(format(matrix[i][j], ".6f"), end = ",")
print()
def mnormalize(matrix):
"""Scale a matrix according to the value in the center."""
width = len(matrix[0])
height = len(matrix)
factor = 1.0 / matrix[int(height / 2)][int(width / 2)]
if 1.0 == factor: return matrix
for i in range(height):
for j in range(width):
matrix[i][j] *= factor
return matrix
def mmirror4(matrix):
"""Do a 4-way mirroring on a matrix from top-left corner."""
width = len(matrix[0])
height = len(matrix)
for i in range(height):
for j in range(width):
x = min(i, height - 1 - i)
y = min(j, width - 1 - j)
matrix[i][j] = matrix[x][y]
return matrix
def gen_gaussian(width, height, factors):
"""Build a Gaussian blur kernel."""
if width != height:
raise CGBadArg("Cannot build an uneven Gaussian blur kernel.")
size = width
sigma = float(factors.get('sigma', 0.84089642))
result = mbuild(size, size)
for i in range(int(size / 2) + 1):
for j in range(int(size / 2) + 1):
diffx = i - int(size / 2);
diffy = j - int(size / 2);
result[i][j] = 1.0 / (2 * math.pi * sigma) * pow(math.e, - (diffx * diffx + diffy * diffy) / (2 * sigma * sigma))
mnormalize(result)
mmirror4(result)
return result
def gen_box(width, height, factors):
"""Build a box blur kernel."""
result = mbuild(width, height)
for i in range(height):
for j in range(width):
result[i][j] = 1.0
return result
def gen_invalid(width, height, factors):
raise CGBadArg("Unknown kernel type.")
def args_readfactors(lst):
"""Parse the factor arguments."""
factors = dict()
if lst:
for s in lst:
res = s.partition('=')
if not res[0]:
raise CGBadArg("Factor has no key.")
if not res[2]:
raise CGBadArg("Factor has no value.")
factors[res[0]] = float(res[2])
return factors
parser = argparse.ArgumentParser(description='Build a convolution kernel.')
parser.add_argument('type', help='Type of convolution kernel. May be "gaussian" (factor sigma = 0.84089642) or "box".')
parser.add_argument('width', type=int, help='Width of convolution kernel. Must be an odd number.')
parser.add_argument('height', nargs='?', type=int, help='Height of convolution kernel. Must be an odd number. Equals to width if omitted.')
parser.add_argument('-f', '--factor', nargs='+', help='Factors of the convolution kernel, in name=value format.')
parser.add_argument('--dump-compton', action='store_true', help='Dump in compton format.')
args = parser.parse_args()
width = args.width
height = args.height
if not height:
height = width
if not (width > 0 and height > 0):
raise CGBadArg("Invalid width/height.")
factors = args_readfactors(args.factor)
funcs = dict(gaussian = gen_gaussian, box = gen_box)
matrix = (funcs.get(args.type, gen_invalid))(width, height, factors)
if args.dump_compton:
mdumpcompton(matrix)
else:
mdump(matrix)

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@ -4237,6 +4237,9 @@ usage(void) {
" --blur-background-fixed.\n" " --blur-background-fixed.\n"
" A 7x7 Guassian blur kernel looks like:\n" " A 7x7 Guassian blur kernel looks like:\n"
" --blur-kern '7,7,0.000003,0.000102,0.000849,0.001723,0.000849,0.000102,0.000003,0.000102,0.003494,0.029143,0.059106,0.029143,0.003494,0.000102,0.000849,0.029143,0.243117,0.493069,0.243117,0.029143,0.000849,0.001723,0.059106,0.493069,0.493069,0.059106,0.001723,0.000849,0.029143,0.243117,0.493069,0.243117,0.029143,0.000849,0.000102,0.003494,0.029143,0.059106,0.029143,0.003494,0.000102,0.000003,0.000102,0.000849,0.001723,0.000849,0.000102,0.000003'\n" " --blur-kern '7,7,0.000003,0.000102,0.000849,0.001723,0.000849,0.000102,0.000003,0.000102,0.003494,0.029143,0.059106,0.029143,0.003494,0.000102,0.000849,0.029143,0.243117,0.493069,0.243117,0.029143,0.000849,0.001723,0.059106,0.493069,0.493069,0.059106,0.001723,0.000849,0.029143,0.243117,0.493069,0.243117,0.029143,0.000849,0.000102,0.003494,0.029143,0.059106,0.029143,0.003494,0.000102,0.000003,0.000102,0.000849,0.001723,0.000849,0.000102,0.000003'\n"
" May also be one the predefined kernels: 3x3box (default), 5x5box,\n"
" 7x7box, 3x3gaussian, 5x5gaussian, 7x7gaussian, 9x9gaussian,\n"
" 11x11gaussian.\n"
"--blur-background-exclude condition\n" "--blur-background-exclude condition\n"
" Exclude conditions for background blur.\n" " Exclude conditions for background blur.\n"
"--resize-damage integer\n" "--resize-damage integer\n"
@ -4589,6 +4592,31 @@ parse_matrix_err:
return NULL; return NULL;
} }
/**
* Parse a convolution kernel.
*/
static inline XFixed *
parse_conv_kern(session_t *ps, const char *src) {
static const struct {
const char *name;
const char *kern_str;
} CONV_KERN_PREDEF[] = {
{ "3x3box", "3,3,1,1,1,1,1,1,1,1," },
{ "5x5box", "5,5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1," },
{ "7x7box", "7,7,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1," },
{ "3x3gaussian", "3,3,0.243117,0.493069,0.243117,0.493069,0.493069,0.243117,0.493069,0.243117," },
{ "5x5gaussian", "5,5,0.003493,0.029143,0.059106,0.029143,0.003493,0.029143,0.243117,0.493069,0.243117,0.029143,0.059106,0.493069,0.493069,0.059106,0.029143,0.243117,0.493069,0.243117,0.029143,0.003493,0.029143,0.059106,0.029143,0.003493," },
{ "7x7gaussian", "7,7,0.000003,0.000102,0.000849,0.001723,0.000849,0.000102,0.000003,0.000102,0.003493,0.029143,0.059106,0.029143,0.003493,0.000102,0.000849,0.029143,0.243117,0.493069,0.243117,0.029143,0.000849,0.001723,0.059106,0.493069,0.493069,0.059106,0.001723,0.000849,0.029143,0.243117,0.493069,0.243117,0.029143,0.000849,0.000102,0.003493,0.029143,0.059106,0.029143,0.003493,0.000102,0.000003,0.000102,0.000849,0.001723,0.000849,0.000102,0.000003," },
{ "9x9gaussian", "9,9,0.000000,0.000000,0.000001,0.000006,0.000012,0.000006,0.000001,0.000000,0.000000,0.000000,0.000003,0.000102,0.000849,0.001723,0.000849,0.000102,0.000003,0.000000,0.000001,0.000102,0.003493,0.029143,0.059106,0.029143,0.003493,0.000102,0.000001,0.000006,0.000849,0.029143,0.243117,0.493069,0.243117,0.029143,0.000849,0.000006,0.000012,0.001723,0.059106,0.493069,0.493069,0.059106,0.001723,0.000012,0.000006,0.000849,0.029143,0.243117,0.493069,0.243117,0.029143,0.000849,0.000006,0.000001,0.000102,0.003493,0.029143,0.059106,0.029143,0.003493,0.000102,0.000001,0.000000,0.000003,0.000102,0.000849,0.001723,0.000849,0.000102,0.000003,0.000000,0.000000,0.000000,0.000001,0.000006,0.000012,0.000006,0.000001,0.000000,0.000000," },
{ "11x11gaussian", "11,11,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000001,0.000006,0.000012,0.000006,0.000001,0.000000,0.000000,0.000000,0.000000,0.000000,0.000003,0.000102,0.000849,0.001723,0.000849,0.000102,0.000003,0.000000,0.000000,0.000000,0.000001,0.000102,0.003493,0.029143,0.059106,0.029143,0.003493,0.000102,0.000001,0.000000,0.000000,0.000006,0.000849,0.029143,0.243117,0.493069,0.243117,0.029143,0.000849,0.000006,0.000000,0.000000,0.000012,0.001723,0.059106,0.493069,0.493069,0.059106,0.001723,0.000012,0.000000,0.000000,0.000006,0.000849,0.029143,0.243117,0.493069,0.243117,0.029143,0.000849,0.000006,0.000000,0.000000,0.000001,0.000102,0.003493,0.029143,0.059106,0.029143,0.003493,0.000102,0.000001,0.000000,0.000000,0.000000,0.000003,0.000102,0.000849,0.001723,0.000849,0.000102,0.000003,0.000000,0.000000,0.000000,0.000000,0.000000,0.000001,0.000006,0.000012,0.000006,0.000001,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000," },
};
for (int i = 0;
i < sizeof(CONV_KERN_PREDEF) / sizeof(CONV_KERN_PREDEF[0]); ++i)
if (!strcmp(CONV_KERN_PREDEF[i].name, src))
return parse_matrix(ps, CONV_KERN_PREDEF[i].kern_str);
return parse_matrix(ps, src);
}
/** /**
* Parse a condition list in configuration file. * Parse a condition list in configuration file.
*/ */
@ -5097,7 +5125,7 @@ get_cfg(session_t *ps, int argc, char *const *argv, bool first_pass) {
case 301: case 301:
// --blur-kern // --blur-kern
free(ps->o.blur_kern); free(ps->o.blur_kern);
if (!(ps->o.blur_kern = parse_matrix(ps, optarg))) if (!(ps->o.blur_kern = parse_conv_kern(ps, optarg)))
exit(1); exit(1);
case 302: case 302:
// --resize-damage // --resize-damage