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Corrections to patch generation code for some features

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This commit is contained in:
Marcus Str. 2024-12-18 09:57:24 +01:00
parent 70e895692c
commit 5cc9819dba
2 changed files with 50 additions and 46 deletions
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39
layergen.py
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@ -159,8 +159,7 @@ class mstr_layergen:
for line in file:
linedata = line.split(" ")
if linedata[0] == self._tag and linedata[1] == self._value:
src = linedata[2].split(",")
contrast = src[4]
contrast = int(linedata[4])
return contrast
@ -295,6 +294,8 @@ class mstr_layergen:
# Find this layer's predetermined contrast
lyr_contrast = self.findLayerContrast()
if lyr_contrast != 0:
mstr_msg("layergen", "Applying contrast value: " + str(lyr_contrast))
# Should this not exist yet, we need to create it
#if os.path.isfile(gensrc_ptc) == False:
@ -376,18 +377,18 @@ class mstr_layergen:
self._tag == "landuse" and self._value == "residential"):
amt = randrange(2, 9)
masks = glob.glob(mstr_datafolder + "textures/tile/completion/*.png")
patchtags = [
["landuse", "meadow"],
["landuse", "grass"],
["natural", "heath"],
["natural", "scrub"]
]
for i in range(1, amt + 1):
pick = randrange(0, len(masks))
patchmask = Image.open(masks[pick])
patchmask = patchmask.rotate(randrange(0, 360), expand=True)
patchpix = patchmask.load()
# Pick from possible tags and values for the patches
patchtags = [
["landuse", "meadow"],
["landuse", "grass"],
["natural", "heath"],
["natural", "scrub"]
]
numbers = list(range(1, 16))
src = random.sample(numbers, 5)
@ -411,7 +412,7 @@ class mstr_layergen:
nc = ( oc[0], oc[1], oc[2], ptc_msk[3] )
lp_pix[x,y] = nc
layerpatch = layerpatch.rotate(randrange(0, 360), expand=True)
#layerpatch = layerpatch.rotate(randrange(0, 360), expand=True)
lx = randrange(self._imgsize - layerpatch.width)
ly = randrange(self._imgsize - layerpatch.height)
@ -546,17 +547,17 @@ class mstr_layergen:
d = randrange(41, 61)
layer_comp_pix[x, y] = ( d,d,d,a[3] )
if self._tag == "highway" and self._value != "motorway":
d = randrange(0, 36)
dr = 90+d
dg = 90+d
db = 95+d
d = randrange(0, 6)
dr = 80+d
dg = 80+d
db = 85+d
da = a[3]
layer_comp_pix[x, y] = ( dr,dg,db,da )
if self._tag == "highway" and self._value == "motorway":
d = randrange(0, 36)
dr = 57+d
dg = 68+d
db = 70+d
d = randrange(0, 46)
dr = 47+d
dg = 58+d
db = 60+d
layer_comp_pix[x, y] = ( dr,dg,db,a[3] )
if self._tag == "highway" and (self._value == "footway" or self._value == "track" or self._value == "path"):
dr = randrange(158, 183)
@ -690,7 +691,7 @@ class mstr_layergen:
ptc_src = []
# Find this layer's predetermined contrast
lyr_contrast = self.findLayerContrast()
lyr_contrast = randrange(1, 4)
rg = mstr_resourcegen(self._tag, self._value, src)
rg.setLayerContrast(int(lyr_contrast))

57
photogen.py
View File

@ -1,6 +1,7 @@
import os
from PIL import Image, ImageFilter, ImageEnhance, ImageFile
from defines import *
from layergen import *
from log import *
@ -92,40 +93,42 @@ class mstr_photogen:
if c < len(cpl)-1:
cplstr = cplstr + "_"
# Should this not exist yet, we need to create it
rg = mstr_resourcegen("landuse", "meadow", cpl)
rg.setLayerContrast(randrange(1,4))
ptcimg = rg.gensource()
# Find the right color catalogue
cpl_catalog = 0
for c in range(len(mstr_completion_colors)):
if mstr_completion_colors[c][0] == edn:
cpl_catalog = c
ptc_src = [ptcimg[0]]
samples = 250 # <- We need this in a moment
for i in range(samples):
imgid = 0
if len(ptc_src) == 1: imgid = 0
l = 0 - int(ptc_src[imgid].width / 2)
r = cmpl.width - int(ptc_src[imgid].width / 2)
t = 0 - int(ptc_src[imgid].height / 2)
b = cmpl.height - int(ptc_src[imgid].height / 2)
cmpl.alpha_composite(ptc_src[imgid], (randrange(l, r), randrange(t, b)))
brd_img = ptcimg[1]
cmpl.alpha_composite(brd_img)
# Put in some pixels
cmpl_bg = Image.new("RGBA", (self._tile.width, self._tile.height))
cmpl_pix = cmpl_bg.load()
for y in range(0, self._tile.height):
for x in range(0, self._tile.width):
idx = randrange(0, len(mstr_completion_colors[cpl_catalog][1]))
clr = mstr_completion_colors[cpl_catalog][1][idx]
cmpl_pix[x,y] = clr
cmpl_bg = ImageEnhance.Contrast(cmpl_bg).enhance(0.8)
cmpl_bg = cmpl_bg.filter(ImageFilter.GaussianBlur(radius=1))
cmpl_bg.alpha_composite(self._tile)
self._tile = cmpl_bg
# Patches to add from other sources. If they don't exist, we also need to make them
masks = glob.glob(mstr_datafolder + "textures/tile/completion/*.png")
amt = randrange(5, 16)
patchtags = [
["landuse", "meadow"],
["landuse", "grass"],
["natural", "heath"],
["natural", "scrub"]
]
for i in range(1, amt + 1):
pick = randrange(0, len(masks))
patchmask = Image.open(masks[pick])
patchmask = patchmask.rotate(randrange(0, 360), expand=True)
patchpix = patchmask.load()
# Pick from possible tags and values for the patches
patchtags = [
["landuse", "meadow"],
["landuse", "grass"],
["natural", "heath"],
["natural", "scrub"]
]
# Pick from possible tags and values for the patches
numbers = list(range(1, 16))
src = random.sample(numbers, 5)
@ -149,10 +152,10 @@ class mstr_photogen:
nc = (oc[0], oc[1], oc[2], ptc_msk[3])
lp_pix[x, y] = nc
layerpatch = layerpatch.rotate(randrange(0, 360), expand=True)
#layerpatch = layerpatch.rotate(randrange(0, 360), expand=True)
lx = randrange(self._imgsize - layerpatch.width)
ly = randrange(self._imgsize - layerpatch.height)
lx = randrange(0, self._imgsize - layerpatch.width)
ly = randrange(0, self._imgsize - layerpatch.height)
cmpl.alpha_composite(layerpatch, (lx, ly))
# Merge the images