Python Dataset 예제들

예제 #1

parser = optparse.OptionParser()
parser.add_option("-l", "--linear", dest="linear", action="store_true", default=False)
parser.add_option("-c", "--distribution", dest="distribution", default=None, type="string")
parser.add_option("-r", "--samples", dest="samples", default=128, type="int")
parser.add_option("-d", "--direct-samples", dest="directSamples", default=4, type="int")
parser.add_option("-i", "--iteration", dest="iteration", default=None, type="int")
parser.add_option("-s", "--super-iteration", dest="superiteration", default=0, type="int")
parser.add_option("-v", "--verbose", dest="verbose", action="store_true", default=False)
parser.add_option("--direct-only", dest="directOnly", action="store_true", default=False)


(options, args) = parser.parse_args()

directory = args[0]

dataset = Dataset(directory)
testset = dataset.testSet()

if options.directOnly:
    idirpath = directory + "/renders/direct-targets"
else:
    idirpath = directory + "/renders/indirect-targets"

if not os.path.exists(idirpath):
    os.mkdir(idirpath)

meshfile = testset.targetMeshPath
paramlist = testset.parameterList()
bsdf = toMap(paramlist, testset.targetBSDF())

for k in range(dataset.testSet().numLights()):

예제 #2

파일: render-bsdf-sphere.py 프로젝트: cmu-ci-lab/multibounce_reflectometry

parser.add_option("-I", "--super-iteration", dest="superIndex", default=-1)
parser.add_option("-i", "--iteration", dest="index", default=-1)
parser.add_option("-s", "--sample-count", dest="sampleCount", default=256)
parser.add_option("-c",
                  "--distribution",
                  dest="distribution",
                  default=None,
                  type="str")
parser.add_option("-o", "--output", dest="output", type="str")
parser.add_option("-d", "--dry-run", action="store_true", dest="dryRun")

(options, args) = parser.parse_args()

directory = args[0]

dataset = Dataset(directory)
if options.superIndex == -1 and options.index == -1:
    targetBSDF = dataset.lastAvailableBSDF()
else:
    targetBSDF = dataset.BSDFAt(iteration=options.index,
                                superiteration=options.superIndex)
print targetBSDF

if options.dryRun:
    sys.exit(0)

testset = dataset.testSet()

sphereXML = os.path.dirname(__file__) + "/data/sphere-embeddable.xml"
sphereXMLP = os.path.dirname(__file__) + "/data/sphere-postprocessed.xml"
testset.embedOnto(sphereXML, sphereXMLP)

예제 #3

파일: highsp-last-image.py 프로젝트: cmu-ci-lab/multibounce_reflectometry

    m3 = dict(m1)
    for k in m2:
        m3[k] = m2[k]
    return m3

from dataset_reader import Dataset, Testset

# Plots high sample count last image.
parser = optparse.OptionParser()
parser.add_option("-s", "--samples", dest="samples", default=2048, type="int")
parser.add_option("-c", "--distribution", dest="distribution", default=None)

(options, args) = parser.parse_args()

directory = args[0]
dataset = Dataset(directory)

# TODO: Temporary
copyfile(dataset.testSet().targetMeshPath, "/tmp/mts_mesh_intensity_slot_0.ply")

renderable = dataset.testSet().renderable(1)
pt0 = np.array(dataset.lastAvailableBSDF())
pt1 = np.array(dataset.testSet().targetBSDF())

paramList = dataset.testSet().parameterList()
#print paramList
#print pt0
#print toMap(paramList, pt1)
if dataset.testSet().bsdfAdaptiveSampled:
    adaptiveParamList = dataset.bsdfAdaptiveSamplingParameterList
    print adaptiveParamList

예제 #4

                  type="int")
parser.add_option("--layout-columns",
                  dest="layoutColumns",
                  default=5,
                  type="int")
parser.add_option("--layout-rows", dest="layoutRows", default=5, type="int")
parser.add_option("--adaptive-mode",
                  dest="adaptiveMode",
                  default=None,
                  type="string")

(options, args) = parser.parse_args()

directory = args[0]

dataset = Dataset(directory)
testset = dataset.testSet()

gdirpath = directory + "/images/raw-bsdf-gradients"

lr = options.layoutRows
lc = options.layoutColumns

if not os.path.exists(gdirpath):
    os.mkdir(gdirpath)

for k in range(dataset.testSet().numLights()):
    xmlAddGradientSliceRendering(testset.gradientRenderables[k],
                                 slices=len(testset.parameterList()))

for i in range(dataset.testSet().numBSDFIterations()):

예제 #5

파일: render-indirect-current.py 프로젝트: cmu-ci-lab/multibounce_reflectometry

                  type="int")
parser.add_option("-v",
                  "--verbose",
                  dest="verbose",
                  action="store_true",
                  default=False)
parser.add_option("--direct-only",
                  dest="directOnly",
                  action="store_true",
                  default=False)

(options, args) = parser.parse_args()

directory = args[0]

dataset = Dataset(directory)
testset = dataset.testSet()

if not options.directOnly:
    idirpath = directory + "/renders/indirect"
else:
    idirpath = directory + "/renders/direct"

if not os.path.exists(idirpath):
    os.mkdir(idirpath)

for i in range(dataset.testSet().numIterations() +
               dataset.testSet().numBSDFIterations()):
    if i >= dataset.testSet().numIterations():
        ii = 0
        bi = i - dataset.testSet().numIterations()

예제 #6

            wts.append(1.0)
        else:
            wts.append(1.0)
    return np.array(wts)


# from dataset_reader import Dataset (Alternative temporary fix)
#execfile(os.path.dirname(__file__) + "/../tools/dataset_reader.py")

parser = optparse.OptionParser()

(options, args) = parser.parse_args()

directory = args[0]

dataset = Dataset(directory)

profiles = [{
    "name":
    "invAlpha",
    "sampleWeights":
    invAlpha(dataset.testSet().bsdfDictionary).tolist(),
    "type":
    "bsdf-adaptive"
}, {
    "name":
    "uniform",
    "sampleWeights": [1.0] * len(dataset.testSet().bsdfDictionary["elements"]),
    "type":
    "bsdf-adaptive"
}, {

예제 #7

파일: raw-viewer.py 프로젝트: cmu-ci-lab/multibounce_reflectometry

import splitpolarity
import rendernormals

parser = optparse.OptionParser()
parser.add_option("--layout-columns", dest="layoutColumns", default=5, type="int")
parser.add_option("--layout-rows", dest="layoutRows", default=5, type="int")
parser.add_option("-i","--iteration", dest="iteration", default=0, type="int")
parser.add_option("-s","--super-iteration", dest="superiteration", default=0, type="int")
parser.add_option("-l","--lindex", dest="lindex", default=0, type="int")


(options, args) = parser.parse_args()

directory = args[0]

dataset = Dataset(directory)
testset = dataset.testSet()

gdirpath = directory + "/images/raw-bsdf-gradients"

lr = options.layoutRows
lc = options.layoutColumns


gradientSlices = np.load(gdirpath + "/" + format(options.superiteration).zfill(2) + "/" + format(options.iteration).zfill(4) + "-" + format(options.lindex).zfill(2) + ".npy")
fig = plt.figure(figsize=(lr, lc))
for k in range(gradientSlices.shape[0]):
    if k >= (lr * lc):
        print "Not enough spots to display all slices. Slices remaining: ", (gradientSlices.shape[0] - k) + 1
        break
    ax = fig.add_subplot(lr, lc, k+1)

예제 #8

파일: single-bounce-gradients.py 프로젝트: cmu-ci-lab/multibounce_reflectometry

import rendernormals

import merl_io

parser = optparse.OptionParser()
parser.add_option("-l", "--linear", dest="linear", action="store_true", default=False)
parser.add_option("-c", "--distribution", dest="distribution", default=None, type="string")
parser.add_option("-r", "--samples", dest="samples", default=128, type="int")
parser.add_option("-i", "--iteration", dest="iteration", default=None, type="int")
parser.add_option("-s", "--super-iteration", dest="superiteration", default=0, type="int")

(options, args) = parser.parse_args()

directory = args[0]

dataset = Dataset(directory)
testset = dataset.testSet()

gdirpath = directory + "/meshes/single-bounce-gradients"
idirpath = directory + "/images/single-bounce-currents"
gidirpath = directory + "/renders/single-bounce-gradients"
if not os.path.exists(gdirpath):
    os.mkdir(gdirpath)
if not os.path.exists(idirpath):
    os.mkdir(idirpath)
if not os.path.exists(gidirpath):
    os.mkdir(gidirpath)

print(dataset.testSet().numIterations() + dataset.testSet().numBSDFIterations())
print("")
print("")

예제 #9

parser.add_option("-m", "--compare", 
                  dest="compare", default=None)
parser.add_option("-e", "--envmaps", dest="envmaps", default="uffizi;doge;field")
parser.add_option("-r", "--resolution", dest="resolution", default=64, type="int")
parser.add_option("--samples", dest="sampleCount", default=1024, type="int")
parser.add_option("-c", "--distribution", dest="distribution", default=None)
parser.add_option("-o", "--output", dest="output", default=None)
parser.add_option("-g", "--coverage", dest="coverage", default=None)
parser.add_option("--source-mesh", dest="sourceMesh", action="store_true", default=False)

(options, args) = parser.parse_args()


directory = args[0]

dataset = Dataset(directory)
testset = dataset.testSet()

envmaps = [envmap for envmap in options.envmaps.split(";") if envmap != ""]

if options.compare is None:
    print("Provide a comparison BRDF as -m <merl-binary>")

# Prep sphere renderables by embedding the BSDF format onto the sphere scene.
sphereXML = os.path.dirname(__file__) + "/data/sphere-embeddable.xml"
sphereXMLP = os.path.dirname(__file__) + "/data/sphere-postprocessed.xml"
testset.embedOnto(sphereXML, sphereXMLP)

renderable = testset.renderables[0]
renderable.setEmbeddedParameter("meshSlot", 0)

예제 #10

파일: first-order-gradient.py 프로젝트: cmu-ci-lab/multibounce_reflectometry

parser.add_option("-s",
                  "--jump-size",
                  dest="jumpSize",
                  default=None,
                  type="string")
parser.add_option("-k",
                  "--resolution",
                  dest="resolution",
                  default=256,
                  type="int")

(options, args) = parser.parse_args()

directory = args[0]

dataset = Dataset(directory)

pt = np.array(dataset.lastAvailableBSDF())

if not dataset.testSet().bsdfAdaptiveSampled:
    print("BSDF Adaptive Sampling should be enabled for variance testing")
    sys.exit(1)

adaptiveParamList = dataset.bsdfAdaptiveSamplingParameterList
paramList = dataset.testSet().parameterList()
testset = dataset.testSet()

###
# Monte Carlo gradient
###

예제 #11

파일: compute-rendered-error.py 프로젝트: cmu-ci-lab/multibounce_reflectometry

from shutil import copyfile
from dataset_reader import Dataset, Testset
import merl_io

parser = optparse.OptionParser()
parser.add_option("-s", "--samples", dest="sampleCount", default=1024, type="int")
parser.add_option("-e", "--envmaps", dest="envmaps", default="uffizi;doge;field")
parser.add_option("-i", "--iteration", dest="iteration", default=None, type="int")
parser.add_option("-c", "--distribution", dest="distribution", default=None, type="string")
parser.add_option("-k", "--skip", dest="skip", default=1, type="int")

(options, args) = parser.parse_args()

envmaps = [envmap for envmap in options.envmaps.split(";")]

dataset = Dataset(args[0])

directory = args[0]

testset = dataset.testSet()

sphereXML = os.path.dirname(__file__) + "/data/sphere-embeddable.xml"
sphereXMLP = os.path.dirname(__file__) + "/data/sphere-postprocessed.xml"
testset.embedOnto(sphereXML, sphereXMLP)

renderable = testset.renderables[0]
renderable.setEmbeddedParameter("meshSlot", 0)
renderable.setFile(sphereXMLP)

renderable.setEmbeddedParameter("width", 64)
renderable.setEmbeddedParameter("height", 64)

예제 #12

parser.add_option("-c", "--distribution", dest="distribution", default=None)
parser.add_option("-u",
                  "--use-actual-reductor",
                  action="store_true",
                  dest="useActualReductor",
                  default=False)
parser.add_option("-p",
                  "--use-plain-reductor",
                  action="store_true",
                  dest="usePlainReductor",
                  default=False)
(options, args) = parser.parse_args()

directory = args[0]

dataset = Dataset(directory)

if options.sampleFile is None:
    print("Using default sample profile filename")
    options.sampleFile = directory + "/spatial_sample_profiles.json"

sampleProfiles = json.load(open(options.sampleFile, "r"))

pt = np.array(dataset.lastAvailableBSDF())

if not dataset.testSet().bsdfAdaptiveSampled:
    print("BSDF Adaptive Sampling should be enabled for variance testing")
    sys.exit(1)

adaptiveParamList = dataset.bsdfAdaptiveSamplingParameterList
paramList = dataset.testSet().parameterList()