def pilFromData(image_data):
try:
im = Image.open(StringIO(image_data))
im.load()
except IOError:
#PIL couldn't open, so try to read with panda3d which supports DDS:
im = None
tex = textureFromData(image_data)
if tex is not None:
outdata = tex.getRamImageAs('RGB').getData()
try:
im = Image.fromstring('RGB', (tex.getXSize(), tex.getYSize()), outdata)
im.load()
except IOError:
#Any problem with panda3d might generate an invalid image buffer, so don't convert this
im = None
return im
def pilFromData(image_data):
try:
im = Image.open(StringIO(image_data))
im.load()
except IOError:
#PIL couldn't open, so try to read with panda3d which supports DDS:
im = None
tex = textureFromData(image_data)
if tex is not None:
outdata = tex.getRamImageAs('RGB').getData()
try:
im = Image.fromstring('RGB', (tex.getXSize(), tex.getYSize()), outdata)
im.load()
except IOError:
#Any problem with panda3d might generate an invalid image buffer, so don't convert this
im = None
return im
def optimizeTextures(mesh):
previous_images = []
for cimg in mesh.images:
previous_images.append(cimg.path)
pilimg = cimg.pilimage
#PIL doesn't support DDS, so if loading failed, try and load it as a DDS with panda3d
if pilimg is None:
imgdata = cimg.data
#if we can't even load the image's data, can't convert
if imgdata is None:
print("Couldn't load image data", file=sys.stderr)
continue
try:
from panda3d.core import Texture
from panda3d.core import StringStream
from panda3d.core import PNMImage
except ImportError:
#if panda3d isn't installed and PIL failed, can't convert
print('Tried loading image with PIL and DDS and both failed', file=sys.stderr)
continue
t = Texture()
success = t.readDds(StringStream(imgdata))
if success == 0:
#failed to load as DDS, so let's give up
print('Tried loading image as DDS and failed', file=sys.stderr)
continue
#convert DDS to PNG
outdata = t.getRamImageAs('RGB').getData()
try:
im = Image.fromstring('RGB', (t.getXSize(), t.getYSize()), outdata)
im.load()
except IOError:
#Any problem with panda3d might generate an invalid image buffer, so don't convert this
print('Problem loading DDS file with PIL', file=sys.stderr)
continue
pilimg = im
if pilimg.format == 'JPEG':
#PIL image is already in JPG format so don't convert
continue
if 'A' in pilimg.getbands():
alpha = numpy.array(pilimg.split()[-1].getdata())
if not numpy.any(alpha < 255):
alpha = None
#this means that none of the pixels are using alpha, so convert to RGB
pilimg = pilimg.convert('RGB')
if 'A' in pilimg.getbands():
#save textures with an alpha channel in PNG
output_format = 'PNG'
output_extension = '.png'
output_options = {'optimize':True}
else:
if pilimg.format != 'RGB':
pilimg = pilimg.convert("RGB")
#otherwise save as JPEG since it gets
output_format = 'JPEG'
output_extension = '.jpg'
output_options = {'quality':95, 'optimize':True}
if cimg.path.lower()[-len(output_extension):] != output_extension:
dot = cimg.path.rfind('.')
before_ext = cimg.path[0:dot] if dot != -1 else cimg.path
while before_ext + output_extension in previous_images:
before_ext = before_ext + '-x'
cimg.path = before_ext + output_extension
previous_images.append(cimg.path)
outbuf = StringIO()
try:
pilimg.save(outbuf, output_format, **output_options)
except IOError as ex:
print(ex)
cimg.data = outbuf.getvalue()
def getMipMaps(mesh):
mipmaps = {}
for effect in mesh.effects:
for prop in effect.supported:
propval = getattr(effect, prop)
if isinstance(propval, collada.material.Map):
image_name = propval.sampler.surface.image.path
image_data = propval.sampler.surface.image.data
try:
im = Image.open(StringIO(image_data))
im.load()
except IOError:
from panda3d.core import Texture
from panda3d.core import StringStream
from panda3d.core import PNMImage
#PIL failed, so lets try DDS reader with panda3d
t = Texture(image_name)
success = t.readDds(StringStream(image_data))
if success == 0:
raise FilterException("Failed to read image file %s" %
image_name)
#convert DDS to PNG
outdata = t.getRamImageAs('RGBA').getData()
try:
im = Image.fromstring('RGBA',
(t.getXSize(), t.getYSize()),
outdata)
im.load()
except IOError:
raise FilterException("Failed to read image file %s" %
image_name)
#Keep JPG in same format since JPG->PNG is pretty bad
if im.format == 'JPEG':
output_format = 'JPEG'
output_extension = 'jpg'
output_options = {'quality': 95, 'optimize': True}
else:
output_format = 'PNG'
output_extension = 'png'
output_options = {'optimize': True}
#store a copy to the original image so we can resize from it directly each time
orig_im = im
width, height = im.size
#round down to power of 2
width = int(math.pow(2, int(math.log(width, 2))))
height = int(math.pow(2, int(math.log(height, 2))))
pil_images = []
while True:
im = orig_im.resize((width, height), Image.ANTIALIAS)
pil_images.insert(0, im)
if width == 1 and height == 1:
break
width = max(width / 2, 1)
height = max(height / 2, 1)
tar_buf = StringIO()
tar = tarfile.TarFile(fileobj=tar_buf, mode='w')
cur_offset = 0
byte_ranges = []
for i, pil_img in enumerate(pil_images):
buf = StringIO()
pil_img.save(buf, output_format, **output_options)
file_len = buf.tell()
cur_name = '%dx%d.%s' % (pil_img.size[0], pil_img.size[1],
output_extension)
tar_info = tarfile.TarInfo(name=cur_name)
tar_info.size = file_len
buf.seek(0)
tar.addfile(tarinfo=tar_info, fileobj=buf)
#tar files have a 512 byte header
cur_offset += 512
file_start = cur_offset
byte_ranges.append({
'offset': file_start,
'length': file_len,
'width': pil_img.size[0],
'height': pil_img.size[1]
})
#file lengths are rounded up to nearest 512 multiple
file_len = 512 * ((file_len + 512 - 1) / 512)
cur_offset += file_len
tar.close()
mipmaps[propval.sampler.surface.image.path] = (
tar_buf.getvalue(), byte_ranges)
return mipmaps
def getMipMaps(mesh):
mipmaps = {}
for effect in mesh.effects:
for prop in effect.supported:
propval = getattr(effect, prop)
if isinstance(propval, collada.material.Map):
image_name = propval.sampler.surface.image.path
image_data = propval.sampler.surface.image.data
try:
im = Image.open(StringIO(image_data))
im.load()
except IOError:
from panda3d.core import Texture
from panda3d.core import StringStream
from panda3d.core import PNMImage
#PIL failed, so lets try DDS reader with panda3d
t = Texture(image_name)
success = t.readDds(StringStream(image_data))
if success == 0:
raise FilterException("Failed to read image file %s" % image_name)
#convert DDS to PNG
outdata = t.getRamImageAs('RGBA').getData()
try:
im = Image.fromstring('RGBA', (t.getXSize(), t.getYSize()), outdata)
im.load()
except IOError:
raise FilterException("Failed to read image file %s" % image_name)
#Keep JPG in same format since JPG->PNG is pretty bad
if im.format == 'JPEG':
output_format = 'JPEG'
output_extension = 'jpg'
output_options = {'quality': 95, 'optimize':True}
else:
output_format = 'PNG'
output_extension = 'png'
output_options = {'optimize':True}
#store a copy to the original image so we can resize from it directly each time
orig_im = im
width, height = im.size
#round down to power of 2
width = int(math.pow(2, int(math.log(width, 2))))
height = int(math.pow(2, int(math.log(height, 2))))
pil_images = []
while True:
im = orig_im.resize((width, height), Image.ANTIALIAS)
pil_images.insert(0, im)
if width == 1 and height == 1:
break
width = max(width / 2, 1)
height = max(height / 2, 1)
tar_buf = StringIO()
tar = tarfile.TarFile(fileobj=tar_buf, mode='w')
cur_offset = 0
byte_ranges = []
for i, pil_img in enumerate(pil_images):
buf = StringIO()
pil_img.save(buf, output_format, **output_options)
file_len = buf.tell()
cur_name = '%dx%d.%s' % (pil_img.size[0], pil_img.size[1], output_extension)
tar_info = tarfile.TarInfo(name=cur_name)
tar_info.size=file_len
buf.seek(0)
tar.addfile(tarinfo=tar_info, fileobj=buf)
#tar files have a 512 byte header
cur_offset += 512
file_start = cur_offset
byte_ranges.append({'offset':file_start,
'length':file_len,
'width':pil_img.size[0],
'height':pil_img.size[1]})
#file lengths are rounded up to nearest 512 multiple
file_len = 512 * ((file_len + 512 - 1) / 512)
cur_offset += file_len
tar.close()
mipmaps[propval.sampler.surface.image.path] = (tar_buf.getvalue(), byte_ranges)
return mipmaps
