def procOutput(opt, out, *_):
load = out['load']
node0 = Node(dict(op='toFloat'), load)
bitDepthOut = out['bitDepth']
node1 = newNode(opt, dict(op='toOutput', bits=bitDepthOut), load)
fOutput = node1.bindFunc(toOutput(bitDepthOut))
fs = [NonNullWrap(node0.bindFunc(toFloat)), NonNullWrap(fOutput)]
ns = [node0, node1]
if out['source']:
fPreview[0] = restrictSize(2048)
fs1 = [node0.bindFunc(toFloat), fOutput]
if previewFormat:
def o(im):
res = reduce(applyNonNull, fs1, im)
funcPreview(im)
return [res]
else:
o = lambda im: [reduce(applyNonNull, fs1, im)]
fs = [o]
if out['channel']:
fPreview[4] = BGR2RGB
else:
fPreview[4] = identity
ns.append(
appendFuncs(BGR2RGB, Node(dict(op='Channel')), fs1, False))
out['channel'] = 1
ns.append(
appendFuncs(toBuffer(bitDepthOut),
Node(dict(op='toBuffer', bits=bitDepthOut), load), fs1,
False))
return fs, ns, out
def procInput(source, bitDepth, fs, out):
out['load'] = 1
node = Node({'op': 'toTorch', 'bits': bitDepth})
fs.append(
NonNullWrap(
node.bindFunc(toTorch(bitDepth, config.dtype(), config.device()))))
return fs, [node], out
def procDN(opt, out, *_):
DNopt = opt['opt']
node = Node(dict(op='DN', model=opt['model']), out['load'])
if 'name' in opt:
node.name = opt['name']
return [NonNullWrap(node.bindFunc(lambda im: runDN.dn(im, DNopt)))
], [node], out
def genProcess(steps, root=True, outType=None):
funcs=[]
nodes=[]
last = identity
rf = lambda im: reduce(apply, funcs, im)
if root:
for i, opt in enumerate(steps):
opt['name'] = i + (0 if steps[0]['op'] == 'file' else 2)
for opt in filter((lambda opt: opt['op'] == 'SR'), steps):
toInt(opt, ['scale', 'ensemble'])
opt['opt'] = runSR.getOpt(opt)
for opt in filter((lambda opt: opt['op'] == 'resize'), steps):
toInt(opt, ['width', 'height'])
if 'scaleW' in opt:
opt['scaleW'] = float(opt['scaleW'])
if 'scaleH' in opt:
opt['scaleH'] = float(opt['scaleH'])
for opt in filter((lambda opt: opt['op'] == 'DN'), steps):
opt['opt'] = runDN.getOpt(opt)
for opt in filter((lambda opt: opt['op'] == 'dehaze'), steps):
opt['opt'] = dehaze.getOpt(opt)
slomos = [*filter((lambda opt: opt['op'] == 'slomo'), steps)]
for opt in slomos:
toInt(opt, ['sf'])
opt['opt'] = runSlomo.getOpt(opt)
if len(slomos):
slomos[-1]['opt'].notLast = 0
if steps[-1]['op'] != 'output':
steps.append(dict(op='output'))
config.getFreeMem(True)
process = lambda im, name=None: last(rf(im), name, context)
else:
process = rf
for i, opt in enumerate(steps):
op = opt['op']
fs, ns, outType = procs[op](opt, outType, nodes)
funcs.extend(fs)
nodes.extend(ns)
if op == 'slomo':
if i + 1 < len(steps):
f, nodesAfter = genProcess(steps[i + 1:], False, outType)
else:
f = identity
nodesAfter = []
slomoOpt = opt['opt']
slomo = funcs[-1](f, nodes[-1], slomoOpt)
funcs[-1] = windowWrap(slomo, slomoOpt, 2)
nodeAfter = Node({}, total=opt['sf'], learn=0)
for node in nodesAfter:
nodeAfter.append(node)
nodes.append(nodeAfter)
break
if root and steps[0]['op'] == 'file':
n = Node({'op': 'write'}, outType['load'])
nodes.append(n)
last = n.bindFunc(writeFile)
else:
context.imageMode = 'RGB'
return process, nodes
def genProcess(steps, root=True, outType=None):
funcs = []
nodes = []
last = identity
rf = lambda im: reduce(apply, funcs, im)
if root:
stepOffset = 0 if steps[0]['op'] == 'file' else 2
for i, opt in enumerate(steps):
opt['name'] = i + stepOffset
if opt['op'] == 'resize':
if 'scaleW' in opt:
opt['scaleW'] = float(opt['scaleW'])
if 'scaleH' in opt:
opt['scaleH'] = float(opt['scaleH'])
if opt['op'] in stepOpts:
stepOpt = stepOpts[opt['op']]
toInt(opt, stepOpt.get('toInt', []))
if 'getOpt' in stepOpt:
opt['opt'] = stepOpt['getOpt'].getOpt(opt)
if steps[-1]['op'] != 'output':
steps.append(dict(op='output'))
config.getFreeMem(True)
process = lambda im, name=None: last(rf(im), name, context)
else:
process = rf
for i, opt in enumerate(steps):
op = opt['op']
fs, ns, outType = procs[op](opt, outType, nodes)
funcs.extend(fs)
nodes.extend(ns)
if op in videoOps:
if i + 1 < len(steps):
f, nodesAfter = genProcess(steps[i + 1:], False, outType)
else:
f = identity
nodesAfter = []
videoOpt = opt['opt']
func = funcs[-1](f, nodes[-1], videoOpt)
funcs[-1] = windowWrap(func, videoOpt,
videoOps[op]) if videoOps[op] > 1 else func
nodeAfter = Node({}, total=opt.get('sf', 1), learn=0)
for node in nodesAfter:
nodeAfter.append(node)
nodes.append(nodeAfter)
break
if root and steps[0]['op'] == 'file':
n = Node({'op': 'write'}, outType['load'])
nodes.append(n)
last = n.bindFunc(writeFile)
else:
context.imageMode = 'RGB'
return process, nodes
def genProcess(steps, root=True, outType=None):
funcs=[]
nodes=[]
last = identity
rf = lambda im: reduce(apply, funcs, im)
if root:
for opt in filter((lambda opt: opt['op'] == 'SR'), steps):
opt['scale'] = int(opt['scale'])
opt['opt'] = runSR.getOpt(opt['scale'], opt['model'], config.ensembleSR)
for opt in filter((lambda opt: opt['op'] == 'resize'), steps):
opt['scale'] = int(opt['scale'])
for opt in filter((lambda opt: opt['op'] == 'DN'), steps):
opt['opt'] = runDN.getOpt(opt['model'])
for opt in filter((lambda opt: opt['op'] == 'dehaze'), steps):
opt['opt'] = dehaze.getOpt()
slomos = [*filter((lambda opt: opt['op'] == 'slomo'), steps)]
for opt in slomos:
opt['sf'] = int(opt['sf'])
opt['opt'] = runSlomo.getOpt(opt)
if len(slomos):
slomos[-1]['opt'].notLast = 0
steps.append(dict(op='output'))
config.getFreeMem(True)
process = lambda im, name=None: last(rf(im), name)
else:
process = rf
for i, opt in enumerate(steps):
op = opt['op']
fs, ns, outType = procs[op](opt, outType, nodes)
funcs.extend(fs)
nodes.extend(ns)
if op == 'slomo':
if i + 1 < len(steps):
f, nodesAfter = genProcess(steps[i + 1:], False, outType)
else:
f = identity
nodesAfter = []
slomoOpt = opt['opt']
slomo = funcs[-1](f, nodes[-1])
funcs[-1] = windowWrap(lambda data: slomo(data, slomoOpt), 2, runSlomo.getBatchSize(opt))
nodeAfter = Node({}, total=opt['sf'], learn=0)
for node in nodesAfter:
nodeAfter.append(node)
nodes.append(nodeAfter)
break
if root and steps[0]['op'] == 'file':
n = Node({'op': 'write'}, outType['load'])
nodes.append(n)
last = n.bindFunc(writeFile)
return process, nodes
def procOutput(opt, out, *_):
load = out['load']
node0 = Node(dict(op='toFloat'), load)
bitDepthOut = out['bitDepth']
node1 = Node(dict(op='toOutput', bits=bitDepthOut), load, name=opt['name'] if 'name' in opt else None)
fOutput = node1.bindFunc(toOutput(bitDepthOut))
fs = [NonNullWrap(node0.bindFunc(toFloat)), NonNullWrap(fOutput)]
ns = [node0, node1]
if out['source']:
fs1 = [fOutput]
def o(im):
res = reduce(applyNonNull, fs1, im)
funcPreview(im)
return [res]
fs[1] = o
if out['channel']:
fPreview[2] = BGR2RGB
else:
fPreview[2] = identity
ns.append(appendFuncs(BGR2RGB, Node(dict(op='Channel')), fs1, False))
out['channel'] = 1
ns.append(appendFuncs(toBuffer(bitDepthOut), Node(dict(op='toBuffer', bits=bitDepthOut), load), fs1, False))
return fs, ns, out
def procResize(opt, out, nodes):
node = Node(dict(op='resize', mode=opt['method']),
1,
name=opt['name'] if 'name' in opt else None)
return [node.bindFunc(NonNullWrap(resize(opt, out, len(nodes),
nodes)))], [node], out
