def procSR(opt, out, *_):
load = out['load']
scale = opt['scale']
mode = opt['model']
SRopt = opt['opt']
es = SRopt.ensemble + 1
if not scale > 1:
raise TypeError('Invalid scale setting for SR.')
out['load'] = load * scale * scale
fs, ns = convertChannel(out) if out['channel'] and mode == 'gan' else ([], [])
ns.append(appendFuncs(runSR.sr(SRopt), newNode(opt, dict(op='SR', model=mode, scale=scale), load * es), fs))
return fs, ns, out
def procSR(opt, out, *_):
load = out['load']
scale = opt['scale']
mode = opt['model']
SRopt = opt['opt']
if not scale > 1:
raise TypeError('Invalid scale setting for SR.')
out['load'] = load * scale * scale
fs, ns = convertChannel(out) if out['channel'] and mode == 'gan' else ([], [])
ns.append(appendFuncs(lambda im: runSR.sr(im, SRopt), Node(dict(op='SR', model=mode), load), fs))
if 'name' in opt:
ns[-1].name = opt['name']
return fs, ns, out
def genProcess(scale=1,
mode='a',
dnmodel='no',
dnseq='before',
source='image',
bitDepthIn=8,
bitDepthOut=0):
SRopt = runSR.getOpt(scale, mode, config.ensembleSR)
DNopt = runDN.getOpt(dnmodel)
config.getFreeMem(True)
if not bitDepthOut:
bitDepthOut = bitDepthIn
quant = 1 << bitDepthIn
funcs = []
last = lambda im, _: im
if source == 'file':
funcs.append(readFile)
elif source == 'buffer':
funcs.append(toNumPy(bitDepthIn))
funcs.append(toTorch(quant, config.dtype(), config.device()))
if (dnseq == 'before') and (dnmodel != 'no'):
funcs.append(lambda im: runDN.dn(im, DNopt))
if (scale > 1):
funcs.append(lambda im: runSR.sr(im, SRopt))
if (dnseq == 'after') and (dnmodel != 'no'):
funcs.append(lambda im: runDN.dn(im, DNopt))
funcs.append(toOutput(bitDepthOut))
if source == 'file':
last = writeFile
elif source == 'buffer':
funcs.append(toBuffer(bitDepthOut))
def process(im, name=None):
im = reduce(apply, funcs, im)
return last(im, name)
return process