def imread(filename, format_="float32"):
"""Reads an image. Supports exr, hdr, cr2, tiff, jpg, png and
everything SciPy/PIL supports.
:filename: file path.
:format_: format in which to return the value. If set to "native", the
native format of the file will be given (e.g. uint8 for jpg).
"""
ldr = False
_, ext = os.path.splitext(filename.lower())
if ext == '.exr':
im = ezexr.imread(filename)
elif ext in ['.hdr', '.pic']:
im = _hdr_read(filename)
elif ext in ['.cr2', '.nef', '.raw']:
im = _raw_read(filename)
elif ext in ['.tiff', '.tif']:
try:
import tifffile as tiff
except ImportError:
#print('Install tifffile for better tiff support. Fallbacking to scipy.')
im = scipy_io.imread(filename)
else:
im = tiff.imread(filename)
else:
im = scipy_io.imread(filename)
ldr = True
if format_ == "native":
return im
elif ldr and not 'int' in format_:
return im.astype(format_) / 255.
else:
return im.astype(format_)
ts = time.time()
with open("output.npz", "rb") as fhdl:
data = np.load(fhdl)
T = data["arr_0"]
normals = data["arr_1"]
img_size = data["arr_2"]
print("time: {:.03f}".format(time.time() - ts))
# Save the normals
imsave('normals.png', (normals + 1) / 2)
#from matplotlib import pyplot as plt
#plt.imshow((normals + 1)/2); plt.show()
# Load the envmap
ts = time.time()
envmap = imread("envmap.exr", rgb=True)
envmap = zoom(envmap, (128 / envmap.shape[0], 256 / envmap.shape[1], 1),
order=1,
prefilter=True)
envmap = envmap[:64, :, :]
print("time: {:.03f}".format(time.time() - ts))
for i in range(256):
envmap = np.roll(envmap, shift=1, axis=1)
# Perform the rendering
ts = time.time()
im = T.dot(envmap.reshape((-1, 3)))
# Tonemap & reshape
im = im.reshape((img_size[0], img_size[1], 3))**(1. / 2.2)
print("Render performed in {:.3f}s".format(time.time() - ts))