def blend_im_mask_to_exr(exr_filename, im_mask, clip_min=-1, clip_max=1):
exrfile = exr.InputFile(exr_filename)
#print(exrfile.header())
dw = exrfile.header()['dataWindow']
isize = (dw.max.y - dw.min.y + 1, dw.max.x - dw.min.x + 1)
channels = ['R', 'G', 'B']
channelData = dict()
for c in channels:
C = exrfile.channel(c, Imath.PixelType(Imath.PixelType.FLOAT))
C_arr = np.fromstring(C, dtype=np.float32)
#C_arr = np.reshape(C_arr, isize)
C_arr = np.clip(C_arr, a_min=clip_min, a_max=clip_max)
channelData[c] = array.array(
'f',
C_arr.astype(np.float32).flatten().tostring())
# alpha channel with im_mask data
channelData['A'] = array.array(
'f',
im_mask.astype(np.float32).flatten().tostring())
os.remove(exr_filename)
new_header = exr.Header(args.reso, args.reso)
new_header['channel'] = {
'R': Imath.Channel(Imath.PixelType(exr.FLOAT)),
'G': Imath.Channel(Imath.PixelType(exr.FLOAT)),
'B': Imath.Channel(Imath.PixelType(exr.FLOAT)),
'A': Imath.Channel(Imath.PixelType(exr.FLOAT))
}
exr_out = exr.OutputFile(exr_filename.replace('0001', ''), new_header)
exr_out.writePixels(channelData)
return
def write_openexr_image(filename, image):
"""Save image in OpenEXR file format from numpy array."""
height = len(image)
width = len(image[0])
channels = len(image[0][0])
# Default header only has RGB channels
hdr = OpenEXR.Header(width, height)
if channels == 4:
data_r = image[:, :, 0].tobytes()
data_g = image[:, :, 1].tobytes()
data_b = image[:, :, 2].tobytes()
data_a = image[:, :, 3].tobytes()
image_data = {"R": data_r, "G": data_g, "B": data_b, "A": data_a}
# Add alpha channel to header
alpha_channel = {"A": Imath.Channel(Imath.PixelType(OpenEXR.FLOAT))}
hdr["channels"].update(alpha_channel)
elif channels == 3:
data_r = image[:, :, 0].tobytes()
data_g = image[:, :, 1].tobytes()
data_b = image[:, :, 2].tobytes()
image_data = {"R": data_r, "G": data_g, "B": data_b}
else:
raise RuntimeError("Invalid number of channels of starmap image.")
file_handler = OpenEXR.OutputFile(str(filename), hdr)
file_handler.writePixels(image_data)
file_handler.close()
def save_exr(img, filename):
c, h, w = img.shape
if c == 1:
img = img.reshape(w * h)
Gs = array.array('f', img).tostring()
out = OpenEXR.OutputFile(filename, OpenEXR.Header(w, h))
out.writePixels({'G': Gs})
else:
data = np.array(img).reshape(c, w * h)
Rs = array.array('f', data[0, :]).tostring()
Gs = array.array('f', data[1, :]).tostring()
Bs = array.array('f', data[2, :]).tostring()
out = OpenEXR.OutputFile(filename, OpenEXR.Header(w, h))
out.writePixels({'R': Rs, 'G': Gs, 'B': Bs})
def test_multipart_out(self):
if not hasattr(OpenEXR, 'MultiPartOutputFile'):
return
data = [
array('f', [0.7] * (100 * 100)).tobytes(),
array('f', [0.1] * (100 * 100)).tobytes()
]
headers = []
for i in range(2):
h = OpenEXR.Header(100, 100)
h['channels'] = {
'Z': Imath.Channel(Imath.PixelType(Imath.PixelType.FLOAT))
}
# Multipart headers require a name
h['name'] = 'image_{0:02d}'.format(i).encode(
encoding='ascii'
) # Header strings must be ASCII (Should probably support unicode...)
print(type(h['name']))
headers.append(h)
x = OpenEXR.MultiPartOutputFile('out-multipart.exr', headers)
for i in range(2):
pixels = {'Z': data[i]}
x.writePixels(i, pixels)
x.close()
def saveEXR_grey_np(img, filename):
img = img.astype(numpy.float32) # comment this out if we have problems
d = len(img.shape)
if d >= 3:
w, h, _ = img.shape
else:
w, h = img.shape
assert d == 3 or d == 4 or d == 2
# get the channels
if d == 2:
intensity = numpy.array(img[:, :]).data
else:
red = numpy.array(img[:, :, 0])
green = numpy.array(img[:, :, 1])
blue = numpy.array(img[:, :, 2])
itentensity_temp = (red + green + blue) / 3
intensity = itentensity_temp.data
intensity = intensity.tobytes()
# Write the three color channels to the output file
out = OpenEXR.OutputFile(filename, OpenEXR.Header(h, w))
dict = {'R': intensity, 'G': intensity, 'B': intensity}
out.writePixels(dict)
def createLandAlbedoMap(band_num, landAlbedoRasterFile, out_exr_file):
band_start = const.get_value("NO_BAND_WIDTH_MODE_BAND_START")
band_end = const.get_value("NO_BAND_WIDTH_MODE_BAND_END")
wavelengths = np.linspace(band_start, band_end, band_num + 1)
import gdal
dataset = gdal.Open(landAlbedoRasterFile)
imgXsize = dataset.RasterXSize
imgYSize = dataset.RasterYSize
band_dict = dict()
half_chan = Imath.Channel(Imath.PixelType(Imath.PixelType.FLOAT))
chaneldict = dict()
for i in range(0, band_num):
start = wavelengths[i]
end = wavelengths[i + 1]
band_name = "%.2f" % start + "-" + "%.2fnm" % end
band = dataset.GetRasterBand(i+1)
singleband = band.ReadAsArray(0, 0, imgXsize, imgYSize)
singleband = np.fliplr(singleband)
singleband = np.reshape(singleband, (imgXsize * imgYSize))
radiance_str = array.array('f', singleband).tostring() # generate arr
band_dict[band_name] = radiance_str
chaneldict[band_name] = half_chan
header = OpenEXR.Header(imgXsize, imgYSize)
header["channels"] = chaneldict
out = OpenEXR.OutputFile(out_exr_file, header)
out.writePixels(band_dict)
def imwrite(img, filename, normalize=False):
directory = os.path.dirname(filename)
if directory != '' and not os.path.exists(directory):
os.makedirs(directory)
if isinstance(img, torch.Tensor):
img = img.cpu().data.numpy()
if normalize:
img_rng = np.max(img) - np.min(img)
if img_rng > 0:
img = (img - np.min(img)) / img_rng
if len(img.shape) == 2:
img = img.reshape((img.shape[0], img.shape[1], 1))
if img.shape[2] == 1:
img = np.tile(img, (1, 1, 3))
if filename[-4:] == '.exr':
img_r = img[:, :, 0]
img_g = img[:, :, 1]
img_b = img[:, :, 2]
pixels_r = img_r.astype(np.float16).tostring()
pixels_g = img_g.astype(np.float16).tostring()
pixels_b = img_b.astype(np.float16).tostring()
HEADER = OpenEXR.Header(img.shape[1], img.shape[0])
half_chan = Imath.Channel(Imath.PixelType(Imath.PixelType.HALF))
HEADER['channels'] = dict([(c, half_chan) for c in "RGB"])
exr = OpenEXR.OutputFile(filename, HEADER)
exr.writePixels({'R': pixels_r, 'G': pixels_g, 'B': pixels_b})
exr.close()
else:
img = np.power(np.clip(img, 0.0, 1.0), 1.0 / 2.2)
img = (img * 255.0).astype('uint8')
skimage.io.imsave(filename, img)
def xtest_multiView(self):
h = OpenEXR.Header(640, 480)
for views in [[], ['single'], ['left', 'right'], list("abcdefghijklmnopqrstuvwxyz")]:
h['multiView'] = views
x = OpenEXR.OutputFile("out0.exr", h)
x.close()
self.assertEqual(OpenEXR.InputFile('out0.exr').header()['multiView'], views)
def test_put_img_together_exr(self):
for chunks in [1, 5, 7, 11, 13, 31, 57, 100]:
res_y = 0
self.bt.collected_file_names = {}
for i in range(1, chunks + 1): # Subtask numbers start from 1.
y = randrange(1, 100)
res_y += y
file1 = self.temp_file_name('chunk{}.exr'.format(i))
exr = OpenEXR.OutputFile(file1,
OpenEXR.Header(self.bt.res_x, y))
data = array.array('f', [1.0] * (self.bt.res_x * y)).tostring()
exr.writePixels({
'R': data,
'G': data,
'B': data,
'F': data,
'A': data
})
exr.close()
self.bt.collected_file_names[i] = file1
self.bt.res_y = res_y
self.bt._put_image_together()
self.assertTrue(path.isfile(self.bt.output_file))
img = Image.open(self.bt.output_file)
img_x, img_y = img.size
img.close()
self.assertTrue(self.bt.res_x == img_x and res_y == img_y)
self.bt.restart()
assert self.bt.preview_updater.chunks == {}
assert self.bt.preview_updater.perfectly_placed_subtasks == 0
assert self.bt.preview_updater.perfect_match_area_y == 0
def test_one(self):
oexr = OpenEXR.InputFile("GoldenGate.exr")
#for k,v in sorted(oexr.header().items()):
# print "%20s: %s" % (k, v)
first_header = oexr.header()
default_size = len(oexr.channel('R'))
half_size = len(
oexr.channel('R', Imath.PixelType(Imath.PixelType.HALF)))
float_size = len(
oexr.channel('R', Imath.PixelType(Imath.PixelType.FLOAT)))
uint_size = len(
oexr.channel('R', Imath.PixelType(Imath.PixelType.UINT)))
self.assertTrue(default_size in [half_size, float_size, uint_size])
self.assertTrue(float_size == uint_size)
self.assertTrue((float_size / 2) == half_size)
self.assertTrue(
len(
oexr.channel(
'R', pixel_type=self.FLOAT, scanLine1=10, scanLine2=10)) ==
(4 * (first_header['dataWindow'].max.x + 1)))
data = b" " * (4 * 100 * 100)
h = OpenEXR.Header(100, 100)
x = OpenEXR.OutputFile("out.exr", h)
x.writePixels({'R': data, 'G': data, 'B': data})
x.close()
def test_code_loopback(self):
""" Verify timeCode and keyCode field transit """
data = b" " * (4 * 100 * 100)
h = OpenEXR.Header(100, 100)
timecodes = [
Imath.TimeCode(1, 2, 3, 4, 0, 0, 0, 0, 0, 0),
Imath.TimeCode(1, 2, 3, 4, 1, 0, 0, 0, 0, 0),
Imath.TimeCode(1, 2, 3, 4, 0, 1, 0, 0, 0, 0),
Imath.TimeCode(1, 2, 3, 4, 0, 0, 1, 0, 0, 0),
Imath.TimeCode(1, 2, 3, 4, 0, 0, 0, 1, 0, 0),
Imath.TimeCode(1, 2, 3, 4, 0, 0, 0, 0, 1, 0),
Imath.TimeCode(1, 2, 3, 4, 0, 0, 0, 0, 0, 1),
Imath.TimeCode(1, 2, 3, 4, 1, 1, 1, 1, 1, 1),
]
keycode = Imath.KeyCode(1, 2, 3, 4, 5, 6, 60)
for timecode in timecodes:
h['keyCode'] = keycode
h['timeCode'] = timecode
x = OpenEXR.OutputFile("out2.exr", h)
x.writePixels({'R': data, 'G': data, 'B': data})
x.close()
h = OpenEXR.InputFile("out2.exr").header()
self.assertEqual(h['keyCode'], keycode)
self.assertEqual(h['timeCode'], timecode)
def test_put_img_together_exr_to_exr(self):
self.bt.output_format = "EXR"
self.bt.output_file += ".EXR"
for chunks in [1, 5, 7, 11, 13, 31, 57]:
res_y = 0
self.bt.collected_file_names = {}
for i in range(1, chunks + 1): # Subtask numbers start from 1.
y = randrange(1, 100)
res_y += y
file1 = self.temp_file_name('chunk{}.exr'.format(i))
exr = OpenEXR.OutputFile(file1,
OpenEXR.Header(self.bt.res_x, y))
data = array.array('f', [1.0] * (self.bt.res_x * y)).tostring()
exr.writePixels({
'R': data,
'G': data,
'B': data,
'F': data,
'A': data
})
exr.close()
self.bt.collected_file_names[i] = file1
self.bt.res_y = res_y
self.bt._put_image_together()
self.assertTrue(path.isfile(self.bt.output_file))
img = load_img(self.bt.output_file)
img_x, img_y = img.get_size()
self.assertEqual(self.bt.res_x, img_x)
self.assertEqual(self.bt.res_y, img_y)
img.close()
def save_rgb(image, filePath, comp=OexrCompression.ZIP):
'''Saves the rgb (image) in OpenEXR format. Expects a 3-chan uint32 image.'''
if len(image.shape) != 3:
raise Exception("Incorrect dimensions!")
h, w, c = image.shape # expects Numpy convention (row, col) -> (height, width)
if c != 3:
raise Exception("Incorrect number of channels!")
if image.dtype != "uint32":
raise Exception("Incorrect type!, expected uint32")
try:
header = oe.Header(w, h)
header["channels"] = {
"R": im.Channel(im.PixelType(oe.UINT)),
"G": im.Channel(im.PixelType(oe.UINT)),
"B": im.Channel(im.PixelType(oe.UINT))
}
header['compression'] = im.Compression(comp)
of = oe.OutputFile(filePath, header)
r_data = image[:, :, 0].tostring()
g_data = image[:, :, 1].tostring()
b_data = image[:, :, 2].tostring()
of.writePixels({"R": r_data, "G": g_data, "B": b_data})
of.close()
except:
raise
def exr2ctl2arr(im, im_rows, im_columns, ctl_transforms):
#creating OpenEXR file
pixels = im.astype(numpy.float16).tostring()
HEADER = OpenEXR.Header(im_rows, im_columns)
half_chan = Imath.Channel(Imath.PixelType(Imath.PixelType.HALF))
HEADER['channels'] = dict([(c, half_chan) for c in "RGB"])
exr = OpenEXR.OutputFile("exr_in.exr", HEADER)
exr.writePixels({'R': pixels, 'G': pixels, 'B': pixels})
exr.close()
# #calling CTL Render function
call_ctl_min = colour.utilities.ctl_render("./exr_in.exr", "./exr_out.exr", ctl_transforms)
#opening newly formed OpenEXR file with transformed applied
im = OpenEXR.InputFile('exr_out.exr')
(r,g,b) = im.channels("RGB")
dw = im.header()['dataWindow']
size = (dw.max.x - dw.min.x + 1, dw.max.y - dw.min.y + 1)
#reshaping and reformating image channels to put into new array
red = numpy.reshape(numpy.fromstring(r, dtype=numpy.float16), (size[0], size[1]))
green = numpy.reshape(numpy.fromstring(g, dtype=numpy.float16), (size[0], size[1]))
blue = numpy.reshape(numpy.fromstring(b, dtype=numpy.float16), (size[0], size[1]))
image = numpy.stack((blue, green, red), axis=-1)
test = numpy.array(2**16)
cv2.imwrite('cv1.tif', test)
return image
def save_depth(image, filePath, comp=OexrCompression.ZIP):
'''
Saves the zBuffer (image) in OpenEXR format. Expects a 1-chann float32
image.
'''
if len(image.shape) != 2:
raise Exception("Incorrect dimensions!")
if image.dtype != "float32":
raise Exception("Incorrect type!, expected float32")
try:
h, w = image.shape
header = oe.Header(w, h)
header["channels"] = {"Z": im.Channel(im.PixelType(oe.FLOAT))}
header['compression'] = im.Compression(comp)
of = oe.OutputFile(filePath, header)
image_data = image.tostring()
of.writePixels({"Z": image_data})
of.close()
except:
raise
def test_header_bytes(self):
ctype = Imath.Channel(Imath.PixelType(Imath.PixelType.HALF))
target = 'test_exr.exr'
data = {}
chans = {}
channels = list('RGBA')
for c in channels:
chan = c.upper()
data[chan] = b'X' * (10 * 5 * 2)
chans[chan] = ctype
header = OpenEXR.Header(10, 5)
header['channels'] = chans
header['foo1'] = b'bar'
header['foo2'] = 'bar'.encode('ascii')
header['foo3'] = 'bar'.encode('utf-8')
file_ = OpenEXR.OutputFile(target, header)
file_.writePixels(data)
file_.close()
# Read them back and confirm they are all b'bar'
infile = OpenEXR.InputFile(target)
h = infile.header()
infile.close()
self.assertEqual(h["foo1"], b'bar')
self.assertEqual(h["foo2"], b'bar')
self.assertEqual(h["foo3"], b'bar')
def write_exr(filename, values, channel_names):
"""Writes the values in a multi-channel ndarray into an EXR file.
Args:
filename: The filename of the output file
values: A numpy ndarray with shape [height, width, channels]
channel_names: A list of strings with length = channels
Raises:
TypeError: If the numpy array has an unsupported type.
ValueError: If the length of the array and the length of the channel names
list do not match.
"""
if values.shape[-1] != len(channel_names):
raise ValueError(
'Number of channels in values does not match channel names (%d, %d)'
% (values.shape[-1], len(channel_names)))
header = OpenEXR.Header(values.shape[1], values.shape[0])
try:
exr_channel_type = Imath.PixelType(_np_to_exr[values.dtype.type])
except KeyError:
raise TypeError('Unsupported numpy type: %s' % str(values.dtype))
header['channels'] = {
n: Imath.Channel(exr_channel_type)
for n in channel_names
}
channel_data = [values[..., i] for i in range(values.shape[-1])]
exr = OpenEXR.OutputFile(filename, header)
exr.writePixels(
dict((n, d.tobytes()) for n, d in zip(channel_names, channel_data)))
exr.close()
def write_exr(data, path):
''' data를 exr파일로 저장
Args:
path: 경로 + 파일 이름.exr
data: 3차원 이미지 데이터
'''
assert data.ndim == 3, "exr 파일 write하려는데 차원 수가 다름" + str(data.shape)
if not os.path.isdir(os.path.dirname(path)):
os.makedirs(os.path.dirname(path))
h, w, c = data.shape
if c == 3:
channel_list = ['B', 'G', 'R']
else:
channel_list = ['B']
header = OpenEXR.Header(w, h)
header['compression'] = Imath.Compression(
Imath.Compression.PIZ_COMPRESSION)
# header['channels'] = {c: pixel_type#Imath.Channel(Imath.PixelType.FLOAT)
# for c in channel_list}
out = OpenEXR.OutputFile(path, header)
ch_data = {
ch: data[:, :, index].astype(np.float32).tostring()
for index, ch in enumerate(channel_list)
}
out.writePixels(ch_data)
def save_exr(fname, r=None, g=None, b=None, comments=''):
"""saves exr file. Copied from freemovr_engine.exr"""
r = np.array(r)
assert r.ndim == 2
g = np.array(g)
assert g.ndim == 2
assert g.shape == r.shape
b = np.array(b)
assert b.ndim == 2
assert b.shape == r.shape
header = OpenEXR.Header(r.shape[1], r.shape[0])
header['channels'] = {
'R': Imath.Channel(FREEMOVR_EXR_PIXEL_TYPE),
'G': Imath.Channel(FREEMOVR_EXR_PIXEL_TYPE),
'B': Imath.Channel(FREEMOVR_EXR_PIXEL_TYPE),
}
header['comments'] = comments
out = OpenEXR.OutputFile(fname, header)
data = {
'R': r.astype(np.float32).tostring(),
'G': g.astype(np.float32).tostring(),
'B': b.astype(np.float32).tostring()
}
out.writePixels(data)
out.close()
def writeEXR(image, name):
R = image[:, :, 0].reshape(-1)
G = image[:, :, 1].reshape(-1)
B = image[:, :, 2].reshape(-1)
(Rs, Gs, Bs) = [array.array('f', Chan).tobytes() for Chan in (R, G, B)]
out = OpenEXR.OutputFile(name,
OpenEXR.Header(image.shape[1], image.shape[0]))
out.writePixels({'R': Rs, 'G': Gs, 'B': Bs})
def save_exr_from_numpy(filename, image_as_array):
""" saves an exr image (depth image) form a numpy array"""
width = image_as_array.shape[1]
height = image_as_array.shape[0]
data = image_as_array.tostring()
exr = OpenEXR.OutputFile(filename, OpenEXR.Header(width, height))
exr.writePixels({'R': data, 'G': data, 'B': data})
exr.close()
def saveEXRfromMatrix(file, data, size):
output = OpenEXR.OutputFile(file, OpenEXR.Header(*size))
data = np.moveaxis(data, -1, 0)
output.writePixels({
"R": data[0].tostring(),
"G": data[1].tostring(),
"B": data[2].tostring(),
# "A": data[3].tostring()
})
def writeexr(path, image):
"""Write image to path as an EXR file"""
header = OpenEXR.Header(image.shape[1], image.shape[0])
out = OpenEXR.OutputFile(path, header)
out.writePixels({
'R': image[:, :, 0].tostring(),
'G': image[:, :, 1].tostring(),
'B': image[:, :, 2].tostring()
})
def create_envmap_fun(input, output):
band_start = const.get_value("NO_BAND_WIDTH_MODE_BAND_START")
band_end = const.get_value("NO_BAND_WIDTH_MODE_BAND_END")
band_num = const.get_value("NO_BAND_WIDTH_MODE_BAND_NUM")
resolution_width = const.get_value("env_map_resolution")
resolution_height = int(resolution_width / 2)
# golden = OpenEXR.InputFile(out_file)
# b1 = golden.channel("400.0-404.0nm")
# print OpenEXR.InputFile(out_file).header()
#
# sys.exit(0)
# read data
f = open(input, 'r')
theta_phi = []
band_data = []
for line in f:
arr = line.split(" ")
theta = float(line[0])
phi = float(line[1])
theta_phi.append([theta, phi])
if len(arr[2:]) != band_num:
log("band number does not equal.")
sys.exit(0)
band_data.append(list(map(lambda x: float(x), arr[2:])))
# band_data = map(list, zip(*band_data)) # [[band1_p1,band1_p2,...],[band2_p1,band2_p2,...]]
wavelengths = np.linspace(band_start, band_end, band_num + 1)
radiance_map = np.zeros((resolution_height, resolution_width, band_num))
factor_y = 180 / resolution_height # lat for each pixel
factor_x = 2 * 180 / resolution_width # lon for each pixel
for i in range(0, resolution_height / 2):
c_theta = i * factor_y
for j in range(0, resolution_width):
c_phi = (j + 0.5) * factor_x
nearest_pos = get_nearest_theta_phi(c_theta, c_phi, theta_phi)
radiance_map[i, j, :] = band_data[nearest_pos]
# write this into exr file
band_dict = dict()
half_chan = Imath.Channel(Imath.PixelType(Imath.PixelType.FLOAT))
chaneldict = dict()
for i in range(0, band_num):
start = wavelengths[i]
end = wavelengths[i + 1]
band_name = "%.2f" % start + "-" + "%.2fnm" % end
singleband = radiance_map[:, :, i]
singleband = np.reshape(singleband, (resolution_width * resolution_height))
radiance_str = array.array('f', singleband).tostring() # generate arr
band_dict[band_name] = radiance_str
chaneldict[band_name] = half_chan
header = OpenEXR.Header(resolution_width, resolution_height)
header["channels"] = chaneldict
out = OpenEXR.OutputFile(output, header)
out.writePixels(band_dict)
def test_fileobject(self):
f = io.StringIO()
(w, h) = (640, 480)
data = array.array('f', [0 for x in range(w * h)]).tostring()
hdr = OpenEXR.Header(w, h)
x = OpenEXR.OutputFile(f, hdr)
x.writePixels({'R': data, 'G': data, 'B': data})
x.close()
f.seek(0)
self.assertEqual(hdr, OpenEXR.InputFile(f).header())
def writeexr(I, path):
"""EXR write helper. Requires OpenEXR."""
import OpenEXR
import Imath
h, w = I.shape[:2]
head = OpenEXR.Header(w, h)
head["compression"] = Imath.Compression(Imath.Compression.DWAB_COMPRESSION)
of = OpenEXR.OutputFile(path, head)
R, G, B = [I[:,:,c].tobytes() for c in [0,1,2]]
of.writePixels({'R': R, 'G': G, 'B': B})
def test_write_buffer_object(self):
(w, h) = (640, 480)
a = array('f', [(i % w) / float(w) for i in range(w * h)])
data = bytearray(a.tobytes())
hdr = OpenEXR.Header(w, h)
x = OpenEXR.OutputFile("out3.exr", hdr)
x.writePixels({'R': data, 'G': data, 'B': data})
x.close()
r = self.load_red("out3.exr")
self.assertTrue(r == data)
def writeEXR(rgb, filenameEXR):
size = rgb.shape
header = OpenEXR.Header(size[0], size[1])
rgbYX = np.swapaxes(rgb, 0, 1) #(y,x,c) -> (x,y,c)
header['channels'] = {
c: Imath.Channel(Imath.PixelType(Imath.PixelType.FLOAT))
for c in "RGB"
} #shouldn't we check the type of rgb's elements?
exr = OpenEXR.OutputFile(filenameEXR, header)
exr.writePixels(rgb2rgbdict(rgbYX))
exr.close()
def write_exr(out_file, data):
exr = OpenEXR.OutputFile(out_file,
OpenEXR.Header(data.shape[1], data.shape[0]))
red = data[:, :, 0]
green = data[:, :, 1]
blue = data[:, :, 2]
exr.writePixels({
'R': red.tostring(),
'G': green.tostring(),
'B': blue.tostring()
})
def save_masked_depth(depth, mask, comp_id, out_paths):
comp_id = os.path.splitext(comp_id)[0]
depth_array = np.asarray(depth).astype(np.float32)
mask_array = np.asarray(mask).copy()
mask_array[mask_array > 0] = 1
mask_array = np.ones_like(mask_array) - mask_array
depth_data = depth_array * mask_array.astype(np.float32)
exr = OpenEXR.OutputFile(
os.path.join(out_paths['depth'], comp_id + '.exr'),
OpenEXR.Header(depth.size[0], depth.size[1]))
exr.writePixels({'R': depth_data, 'G': depth_data, 'B': depth_data})
