def startupParameters():
numpy.set_printoptions(threshold=numpy.nan)
# argv: outputPath, occluder, occLevel, numIterations
ind = sys.argv.index('--')
args = sys.argv[ind+1:]
outputPath = str('/om/user/janner/mit/urop/picture/centos/' + args[0])
print('\nOutput Path: ', outputPath)
hideAll_inference()
occluder = args[1]
occLevel = 0 if occluder == 'None' else int(args[2])
if occLevel != 0:
parameterize(occluder, outputPath, 0, 0, occLevel)
print('Occlusion: ', occluder, str(occLevel))
if len(args) >= 4:
numIterations = int(args[3])
else:
numIterations = 20
print('numIterations: ', numIterations, '\n')
if len(args) >= 5:
batchNumber = int(args[4])
print('batchNumber: ', batchNumber, '\n')
if len(args) >= 6:
sweep = int(args[5])
print('sweep: ', sweep, '\n')
gpu = int(args[6])
print('gpu: ', gpu)
if gpu:
setToGPU()
return outputPath, occluder, occLevel, numIterations, batchNumber, sweep
end = int(args[1])
if len(args) > 2:
gpu = eval(args[2])
else:
gpu = False
if gpu:
switchToGPU()
outputBase = '/om/user/janner/mit/urop/picture/centos/dDiff-dOccl/'
# identity, name, outputPath = startupParameters(outputBase)
shapeMU, shapePC, shapeEV, texMU, texPC, texEV, segMM, segMB, tl = loadModel()
#### [identity, name, path, (occluder, occLevel)]
renderArray = numpy.load(outputBase + 'render.npy')
for [identity, name, tempPath, (occluder, occlusionLevel)] in renderArray[start:end]:
hideAll_inference()
print(len(identity))
if len(identity) == 1:
identity = identity.tolist()[0]
print('Converted to list of length ', len(identity), sep='')
# print(identity)
print(str(outputBase + tempPath + name))
alpha = identity[:200]
beta = identity[200:]
# print('alpha: ', alpha)
# print('beta: ', beta)
print('Received coefs:', len(alpha), len(beta))
print('tempPath: ', '/om' in tempPath, tempPath)
parameterize(occluder, outputBase + tempPath, 0, 0, occlusionLevel)
newFace(alpha, beta)
write(outputBase + tempPath if '/om/' not in tempPath else tempPath, name)
