for line in file:\r
linedata = line.split(" ")\r
if linedata[0] == self._tag and linedata[1] == self._value:\r
- src = linedata[2].split(",")\r
- contrast = src[4]\r
+ contrast = int(linedata[4])\r
\r
return contrast\r
\r
\r
# Find this layer's predetermined contrast\r
lyr_contrast = self.findLayerContrast()\r
+ if lyr_contrast != 0:\r
+ mstr_msg("layergen", "Applying contrast value: " + str(lyr_contrast))\r
\r
# Should this not exist yet, we need to create it\r
#if os.path.isfile(gensrc_ptc) == False:\r
self._tag == "landuse" and self._value == "residential"):\r
amt = randrange(2, 9)\r
masks = glob.glob(mstr_datafolder + "textures/tile/completion/*.png")\r
+ patchtags = [\r
+ ["landuse", "meadow"],\r
+ ["landuse", "grass"],\r
+ ["natural", "heath"],\r
+ ["natural", "scrub"]\r
+ ]\r
for i in range(1, amt + 1):\r
pick = randrange(0, len(masks))\r
patchmask = Image.open(masks[pick])\r
+ patchmask = patchmask.rotate(randrange(0, 360), expand=True)\r
patchpix = patchmask.load()\r
# Pick from possible tags and values for the patches\r
- patchtags = [\r
- ["landuse", "meadow"],\r
- ["landuse", "grass"],\r
- ["natural", "heath"],\r
- ["natural", "scrub"]\r
- ]\r
-\r
numbers = list(range(1, 16))\r
src = random.sample(numbers, 5)\r
\r
nc = ( oc[0], oc[1], oc[2], ptc_msk[3] )\r
lp_pix[x,y] = nc\r
\r
- layerpatch = layerpatch.rotate(randrange(0, 360), expand=True)\r
+ #layerpatch = layerpatch.rotate(randrange(0, 360), expand=True)\r
\r
lx = randrange(self._imgsize - layerpatch.width)\r
ly = randrange(self._imgsize - layerpatch.height)\r
d = randrange(41, 61)\r
layer_comp_pix[x, y] = ( d,d,d,a[3] )\r
if self._tag == "highway" and self._value != "motorway":\r
- d = randrange(0, 36)\r
- dr = 90+d\r
- dg = 90+d\r
- db = 95+d\r
+ d = randrange(0, 6)\r
+ dr = 80+d\r
+ dg = 80+d\r
+ db = 85+d\r
da = a[3]\r
layer_comp_pix[x, y] = ( dr,dg,db,da )\r
if self._tag == "highway" and self._value == "motorway":\r
- d = randrange(0, 36)\r
- dr = 57+d\r
- dg = 68+d\r
- db = 70+d\r
+ d = randrange(0, 46)\r
+ dr = 47+d\r
+ dg = 58+d\r
+ db = 60+d\r
layer_comp_pix[x, y] = ( dr,dg,db,a[3] )\r
if self._tag == "highway" and (self._value == "footway" or self._value == "track" or self._value == "path"):\r
dr = randrange(158, 183)\r
ptc_src = []\r
\r
# Find this layer's predetermined contrast\r
- lyr_contrast = self.findLayerContrast()\r
+ lyr_contrast = randrange(1, 4)\r
\r
rg = mstr_resourcegen(self._tag, self._value, src)\r
rg.setLayerContrast(int(lyr_contrast))\r
\r
import os\r
from PIL import Image, ImageFilter, ImageEnhance, ImageFile\r
+\r
from defines import *\r
from layergen import *\r
from log import *\r
if c < len(cpl)-1:\r
cplstr = cplstr + "_"\r
\r
- # Should this not exist yet, we need to create it\r
- rg = mstr_resourcegen("landuse", "meadow", cpl)\r
- rg.setLayerContrast(randrange(1,4))\r
- ptcimg = rg.gensource()\r
-\r
- ptc_src = [ptcimg[0]]\r
- samples = 250 # <- We need this in a moment\r
- for i in range(samples):\r
- imgid = 0\r
- if len(ptc_src) == 1: imgid = 0\r
- l = 0 - int(ptc_src[imgid].width / 2)\r
- r = cmpl.width - int(ptc_src[imgid].width / 2)\r
- t = 0 - int(ptc_src[imgid].height / 2)\r
- b = cmpl.height - int(ptc_src[imgid].height / 2)\r
- cmpl.alpha_composite(ptc_src[imgid], (randrange(l, r), randrange(t, b)))\r
-\r
- brd_img = ptcimg[1]\r
- cmpl.alpha_composite(brd_img)\r
+ # Find the right color catalogue\r
+ cpl_catalog = 0\r
+ for c in range(len(mstr_completion_colors)):\r
+ if mstr_completion_colors[c][0] == edn:\r
+ cpl_catalog = c\r
+\r
+ # Put in some pixels\r
+ cmpl_bg = Image.new("RGBA", (self._tile.width, self._tile.height))\r
+ cmpl_pix = cmpl_bg.load()\r
+ for y in range(0, self._tile.height):\r
+ for x in range(0, self._tile.width):\r
+ idx = randrange(0, len(mstr_completion_colors[cpl_catalog][1]))\r
+ clr = mstr_completion_colors[cpl_catalog][1][idx]\r
+ cmpl_pix[x,y] = clr\r
+ cmpl_bg = ImageEnhance.Contrast(cmpl_bg).enhance(0.8)\r
+ cmpl_bg = cmpl_bg.filter(ImageFilter.GaussianBlur(radius=1))\r
+ cmpl_bg.alpha_composite(self._tile)\r
+ self._tile = cmpl_bg\r
\r
# Patches to add from other sources. If they don't exist, we also need to make them\r
masks = glob.glob(mstr_datafolder + "textures/tile/completion/*.png")\r
amt = randrange(5, 16)\r
+ patchtags = [\r
+ ["landuse", "meadow"],\r
+ ["landuse", "grass"],\r
+ ["natural", "heath"],\r
+ ["natural", "scrub"]\r
+ ]\r
+\r
for i in range(1, amt + 1):\r
pick = randrange(0, len(masks))\r
patchmask = Image.open(masks[pick])\r
+ patchmask = patchmask.rotate(randrange(0, 360), expand=True)\r
patchpix = patchmask.load()\r
- # Pick from possible tags and values for the patches\r
- patchtags = [\r
- ["landuse", "meadow"],\r
- ["landuse", "grass"],\r
- ["natural", "heath"],\r
- ["natural", "scrub"]\r
- ]\r
\r
+ # Pick from possible tags and values for the patches\r
numbers = list(range(1, 16))\r
src = random.sample(numbers, 5)\r
\r
nc = (oc[0], oc[1], oc[2], ptc_msk[3])\r
lp_pix[x, y] = nc\r
\r
- layerpatch = layerpatch.rotate(randrange(0, 360), expand=True)\r
+ #layerpatch = layerpatch.rotate(randrange(0, 360), expand=True)\r
\r
- lx = randrange(self._imgsize - layerpatch.width)\r
- ly = randrange(self._imgsize - layerpatch.height)\r
+ lx = randrange(0, self._imgsize - layerpatch.width)\r
+ ly = randrange(0, self._imgsize - layerpatch.height)\r
cmpl.alpha_composite(layerpatch, (lx, ly))\r
\r
# Merge the images\r
marstr / marstr / orthographic.git / commitdiff