def testref(self, iter, definition=None, vars={}, num_iter=-1):
modelFile, iter = self.getModelFile(iter)
vars['output'] = True
vars['prefix'] = 'ref_%d' % iter
vars['lowres'] = True
self.makeScratchDir()
if definition is None: definition = 'test'
proto = self.findProto(definition)
outPath = '%s/output_%d_%s' % (self._path, iter, vars['dataset'])
if os.path.isdir(outPath):
if self._unattended or tb.queryYesNo(
'Output folder %s exists, do you want to delete it first?'
% os.path.basename(outPath)):
os.system('rm -rf %s' % outPath)
finalProto = self.makeScratchPrototxt(proto, vars)
solverProto = self.makeScratchPrototxt(self._solverProto, vars)
self.notice(
'testing snapshot iteration %d for %d iterations...' %
(iter, num_iter), 'notice')
os.chdir(self._path)
self._backend.test(caffemodelFilename=modelFile,
protoFilename=finalProto,
iterations=num_iter,
logFile=self._scratchLogFile)
def testFiles(self, filelist, iter, output=False, definition=None, vars={}):
modelFile, iter = self.getModelFile(iter)
assert(output)
vars['output'] = True
vars['prefix'] = iter
vars['dataset'] = os.path.splitext(os.path.basename(filelist))[0]
self.makeScratchDir()
if definition is None: definition = 'testsingle'
proto = self.findProto(definition)
if output and 'dataset' in vars:
outPath = '%s/output_%d_%s' % (self._path, iter, vars['dataset'])
if os.path.isdir(outPath):
if self._unattended or tb.queryYesNo('Output folder %s exists, do you want to delete it first?' % os.path.basename(outPath)):
os.system('rm -rf %s' % outPath)
data_list = IO.readTupleList(filelist)
print data_list
# Run a new net for every sample:
for idx, line in enumerate(data_list):
num_blobs = len(line)
input_data = []
for blob_idx in range(num_blobs):
img = IO.readImage(line[blob_idx])
#print(img.shape)
input_data.append(img[np.newaxis, :, :, :].transpose(0, 3, 1, 2)[:,[2,1,0],:,:])
#print(input_data[-1].shape)
vars['width'] = input_data[0].shape[3]
vars['height'] = input_data[0].shape[2]
vars['basename'] = 'b%03d' % idx
finalProto = self.makeScratchPrototxt(proto, vars)
caffe.set_logging_disabled()
caffe.set_mode_gpu()
net = caffe.Net(finalProto, modelFile,caffe.TEST)
print 'Network forward pass (%d of %d). %d inputs of shapes:' % (idx+1, len(data_list), num_blobs)
for blob_idx in range(num_blobs):
print(" " + str(input_data[blob_idx].shape))
if not len(net.inputs) == len(line):
raise Exception('Net has %d inputs and in file list there are %d' % (len(net.inputs), len(line)))
input_dict = {}
for blob_idx in range(num_blobs):
input_dict[net.inputs[blob_idx]] = input_data[blob_idx]
net.forward(**input_dict)
print 'Iteration was %d' %iter
def test(self,
iter,
output=False,
definition=None,
vars={},
num_iter=-1,
discard=False):
modelFile, iter = self.getModelFile(iter)
if output:
vars['output'] = True
vars['prefix'] = iter
self.makeScratchDir()
if definition is None: definition = 'test'
proto = self.findProto(definition)
if output and 'dataset' in vars:
outPath = '%s/output_%d_%s' % (self._path, iter, vars['dataset'])
if os.path.isdir(outPath):
if self._unattended or tb.queryYesNo(
'Output folder %s exists, do you want to delete it first?'
% os.path.basename(outPath)):
os.system('rm -rf %s' % outPath)
finalProto = self.makeScratchPrototxt(proto, vars)
solverProto = self.makeScratchPrototxt(self._solverProto, vars)
self.notice(
'testing snapshot iteration %d for %d iterations...' %
(iter, num_iter), 'notice')
os.chdir(self._path)
self._backend.test(caffemodelFilename=modelFile,
protoFilename=finalProto,
iterations=num_iter,
logFile=self._scratchLogFile)
if output and 'dataset' in vars and num_iter == -1:
outPath = '%s/output_%d_%s' % (self._path, iter, vars['dataset'])
if os.path.isdir(outPath):
logFile = '%s/log.txt' % outPath
print 'saving log to %s', logFile
os.system('cp %s %s' % (self._scratchLogFile, logFile))
if 'dataset' in vars:
self._saveTestResults(iter, vars['dataset'], not discard)
print 'Iteration was %d' % iter
def resume(self, iter=-1):
if not len(self._stateFiles):
raise Exception('no .solverstate files to continue from')
stateFile, iter = self.getStateFile(iter)
if self.existingData(iter) and not self._unattended:
if not tb.queryYesNo(
'Existing data beyond iteration %d found. Do you want to delete it and continue?' % iter):
return
self.clean(iter)
solverFilename = self.prepareTraining()
self.notice('continuing from iteration %d ...' % iter, 'notice')
os.chdir(self._trainDir)
self._backend.resume(solverFilename=solverFilename, solverstateFilename=stateFile, logFile=self._logFile)
def train(self, weights=None, blobSummary=False):
if self.existingData() and not self._unattended:
if not tb.queryYesNo('Existing data found. Do you want to delete it and start from scratch?'):
return
self.clean()
solverFilename = self.prepareTraining()
self.notice('training...')
os.chdir(self._trainDir)
if weights != '':
self._backend.train(solverFilename=solverFilename, logFile=self._logFile, weights=weights)
else:
self._backend.train(solverFilename=solverFilename, logFile=self._logFile)
if blobSummary:
self.displayBlobSummary(self._logFile)
def resume(self, iter=-1):
if not len(self._stateFiles):
raise Exception('no .solverstate files to continue from')
stateFile, iter = self.getStateFile(iter)
if self.existingData(iter) and not self._unattended:
if not tb.queryYesNo(
'Existing data beyond iteration %d found. Do you want to delete it and continue?'
% iter):
return
self.clean(iter)
solverFilename = self.prepareTraining()
self.notice('continuing from iteration %d ...' % iter, 'notice')
os.chdir(self._trainDir)
self._backend.resume(solverFilename=solverFilename,
solverstateFilename=stateFile,
logFile=self._logFile)
def train(self, weights=None, blobSummary=False):
if self.existingData() and not self._unattended:
if not tb.queryYesNo(
'Existing data found. Do you want to delete it and start from scratch?'
):
return
self.clean()
solverFilename = self.prepareTraining()
self.notice('training...')
os.chdir(self._trainDir)
if weights != '':
self._backend.train(solverFilename=solverFilename,
logFile=self._logFile,
weights=weights)
else:
self._backend.train(solverFilename=solverFilename,
logFile=self._logFile)
if blobSummary:
self.displayBlobSummary(self._logFile)
def testref(self, iter, definition=None, vars={}, num_iter=-1):
modelFile, iter = self.getModelFile(iter)
vars['output'] = True
vars['prefix'] = 'ref_%d' % iter
vars['lowres'] = True
self.makeScratchDir()
if definition is None: definition = 'test'
proto = self.findProto(definition)
outPath = '%s/output_%d_%s' % (self._path, iter, vars['dataset'])
if os.path.isdir(outPath):
if self._unattended or tb.queryYesNo('Output folder %s exists, do you want to delete it first?' % os.path.basename(outPath)):
os.system('rm -rf %s' % outPath)
finalProto = self.makeScratchPrototxt(proto, vars)
solverProto = self.makeScratchPrototxt(self._solverProto, vars)
self.notice('testing snapshot iteration %d for %d iterations...' % (iter, num_iter), 'notice')
os.chdir(self._path)
self._backend.test(caffemodelFilename=modelFile, protoFilename=finalProto, iterations=num_iter, logFile=self._scratchLogFile)
def test(self, iter, output=False, definition=None, vars={}, num_iter=-1, discard=False):
modelFile, iter = self.getModelFile(iter)
if output:
vars['output'] = True
vars['prefix'] = iter
self.makeScratchDir()
if definition is None: definition = 'test'
proto = self.findProto(definition)
if output and 'dataset' in vars:
outPath = '%s/output_%d_%s' % (self._path, iter, vars['dataset'])
if os.path.isdir(outPath):
if self._unattended or tb.queryYesNo('Output folder %s exists, do you want to delete it first?' % os.path.basename(outPath)):
os.system('rm -rf %s' % outPath)
finalProto = self.makeScratchPrototxt(proto, vars)
solverProto = self.makeScratchPrototxt(self._solverProto, vars)
self.notice('testing snapshot iteration %d for %d iterations...' % (iter, num_iter), 'notice')
os.chdir(self._path)
self._backend.test(caffemodelFilename=modelFile, protoFilename=finalProto, iterations=num_iter, logFile=self._scratchLogFile)
if output and 'dataset' in vars and num_iter==-1:
outPath = '%s/output_%d_%s' % (self._path, iter, vars['dataset'])
if os.path.isdir(outPath):
logFile = '%s/log.txt' % outPath
print 'saving log to %s', logFile
os.system('cp %s %s' % (self._scratchLogFile, logFile))
if 'dataset' in vars:
self._saveTestResults(iter,vars['dataset'], not discard)
print 'Iteration was %d' %iter
def testFiles(self,
filelist,
iter,
output=False,
definition=None,
vars={}):
modelFile, iter = self.getModelFile(iter)
assert (output)
vars['output'] = True
vars['prefix'] = iter
vars['dataset'] = os.path.splitext(os.path.basename(filelist))[0]
self.makeScratchDir()
if definition is None: definition = 'testsingle'
proto = self.findProto(definition)
if output and 'dataset' in vars:
outPath = '%s/output_%d_%s' % (self._path, iter, vars['dataset'])
if os.path.isdir(outPath):
if self._unattended or tb.queryYesNo(
'Output folder %s exists, do you want to delete it first?'
% os.path.basename(outPath)):
os.system('rm -rf %s' % outPath)
data_list = IO.readTupleList(filelist)
print data_list
# Run a new net for every sample:
for idx, line in enumerate(data_list):
num_blobs = len(line)
input_data = []
for blob_idx in range(num_blobs):
img = IO.readImage(line[blob_idx])
#print(img.shape)
input_data.append(img[np.newaxis, :, :, :].transpose(
0, 3, 1, 2)[:, [2, 1, 0], :, :])
#print(input_data[-1].shape)
vars['width'] = input_data[0].shape[3]
vars['height'] = input_data[0].shape[2]
vars['basename'] = 'b%03d' % idx
finalProto = self.makeScratchPrototxt(proto, vars)
caffe.set_logging_disabled()
caffe.set_mode_gpu()
net = caffe.Net(finalProto, modelFile, caffe.TEST)
print 'Network forward pass (%d of %d). %d inputs of shapes:' % (
idx + 1, len(data_list), num_blobs)
for blob_idx in range(num_blobs):
print(" " + str(input_data[blob_idx].shape))
if not len(net.inputs) == len(line):
raise Exception(
'Net has %d inputs and in file list there are %d' %
(len(net.inputs), len(line)))
input_dict = {}
for blob_idx in range(num_blobs):
input_dict[net.inputs[blob_idx]] = input_data[blob_idx]
net.forward(**input_dict)
print 'Iteration was %d' % iter
def createBinDB(resolution, subpath, collectionName, clips, entryTypes=None, downsample=1, skipIfExists=False, overwrite=True):
if entryTypes is None:
entryTypes = ['cleanImageL', 'finalImageL', 'cleanImageR', 'finalImageR', 'forwardFlowL', 'forwardFlowR', 'backwardFlowL', 'backwardFlowR', 'dispL', 'dispR', 'forwardDispChangeL', 'forwardDispChangeR', 'backwardDispChangeL', 'backwardDispChangeR']
def entryProto(name, type, channels):
txt = ''
txt += ' entry_format: {\n'
txt += ' name: "%s"\n' % name
txt += ' data_encoding: %s \n' % type
txt += ' width: %d\n' % width
txt += ' height: %d\n' % height
txt += ' channels: %d\n' % channels
txt += ' }\n'
return txt
def fileProto(filename, entries):
txt = ''
txt += 'file {\n'
txt += ' filename: "%s"\n' % filename
txt += ' content: {\n'
for entry in entries:
txt += entry
txt += ' }\n'
txt += '}\n'
txt += '\n'
return txt
def writeCleanImage(path):
if path is 0 or path is None:
np.array([0], dtype=np.int32).tofile(fCleanImage)
np.zeros((3,height,width)).astype(np.uint8).tofile(fCleanImage)
else:
np.array([1], dtype=np.int32).tofile(fCleanImage)
Entry('image',path=path).data(downsample=downsample).tofile(fCleanImage)
def writeFinalImage(path):
if path is 0 or path is None:
np.array([0], dtype=np.int32).tofile(fFinalImage)
np.zeros((3,height,width)).astype(np.uint8).tofile(fFinalImage)
else:
np.array([1], dtype=np.int32).tofile(fFinalImage)
Entry('image',path=path).data(downsample=downsample).tofile(fFinalImage)
def writeFlow(path):
if path is 0 or path is None:
np.array([0], dtype=np.int32).tofile(fFlow)
np.zeros((2,height,width)).astype(np.uint16).tofile(fFlow)
else:
np.array([1], dtype=np.int32).tofile(fFlow)
Entry('flow',path=path).data(downsample=downsample).tofile(fFlow)
def writeDispL(path):
if path is 0 or path is None:
np.array([0], dtype=np.int32).tofile(fDisp)
np.zeros((1,height,width)).astype(np.uint16).tofile(fDisp)
else:
np.array([1], dtype=np.int32).tofile(fDisp)
Entry('leftdisparity',path=path).data(downsample=downsample).tofile(fDisp)
def writeDispR(path):
if path is 0 or path is None:
np.array([0], dtype=np.int32).tofile(fDisp)
np.zeros((1,height,width)).astype(np.uint16).tofile(fDisp)
else:
np.array([1], dtype=np.int32).tofile(fDisp)
Entry('rightdisparity',path=path).data(downsample=downsample).tofile(fDisp)
def writeDispChangeL(path):
if path is 0 or path is None:
np.array([0], dtype=np.int32).tofile(fDispChange)
np.zeros((1,height,width)).astype(np.uint16).tofile(fDispChange)
else:
np.array([1], dtype=np.int32).tofile(fDispChange)
Entry('leftdisparitychange',path=path).data(downsample=downsample).tofile(fDispChange)
def writeDispChangeR(path):
if path is 0 or path is None:
np.array([0], dtype=np.int32).tofile(fDispChange)
np.zeros((1,height,width)).astype(np.uint16).tofile(fDispChange)
else:
np.array([1], dtype=np.int32).tofile(fDispChange)
Entry('rightdisparitychange',path=path).data(downsample=downsample).tofile(fDispChange)
dataPath = '/misc/lmbraid17/sceneflownet/common/data/4_bin-db'
path = '%s/%s/%s/%s' % (dataPath, resolution, subpath, collectionName)
if os.path.exists(path):
if not overwrite and (skipIfExists or not tb.queryYesNo('The collection %s already exists. Do you want to delete it and create a new one?' % collectionName)):
return
else:
os.system('rm -rf %s' % path)
print path
os.system('mkdir -p %s' % path)
num = 0
width = -1
height = -1
slice_points = []
print 'collection', collectionName, path
for clip in clips:
frame = clip.frame(clip.startFrame())
if frame.hasCleanImageL():
image = misc.imread(frame.cleanImageL())
else:
image = misc.imread(frame.finalImageL())
if width==-1 and height==-1:
width = image.shape[1]
height = image.shape[0]
if width!= image.shape[1] or height!=image.shape[0]:
raise Exception('clips in collection %s have different resolutions' % collection)
length = clip.endFrame() - clip.startFrame() + 1
print 'adding clip %d %d (%d)' % (clip.startFrame(), clip.endFrame(), length)
num += length
print 'slice_point %d' % num
slice_points.append(num)
txt = ''
txt += 'num: %d\n' % num
for point in slice_points[:-1]:
txt += 'slice_before: %d\n' % point
txt += '\n'
cleanImageDefs = []
if 'cleanImageL' in entryTypes: cleanImageDefs.append(entryProto('cleanImageL','UINT8',3))
if 'cleanImageR' in entryTypes: cleanImageDefs.append(entryProto('cleanImageR','UINT8',3))
if len(cleanImageDefs): txt += fileProto('image_clean.bin', cleanImageDefs)
finalImageDefs = []
if 'finalImageL' in entryTypes: finalImageDefs.append(entryProto('finalImageL','UINT8',3))
if 'finalImageR' in entryTypes: finalImageDefs.append(entryProto('finalImageR','UINT8',3))
if len(finalImageDefs): txt += fileProto('image_final.bin', finalImageDefs)
flowDefs = []
if 'forwardFlowL' in entryTypes: flowDefs.append(entryProto('forwardFlowL', 'FIXED16DIV32', 2))
if 'forwardFlowR' in entryTypes: flowDefs.append(entryProto('forwardFlowR', 'FIXED16DIV32', 2))
if 'backwardFlowL' in entryTypes: flowDefs.append(entryProto('backwardFlowL', 'FIXED16DIV32', 2))
if 'backwardFlowR' in entryTypes: flowDefs.append(entryProto('backwardFlowR', 'FIXED16DIV32', 2))
if len(flowDefs): txt += fileProto('flow.bin', flowDefs)
disparityDefs = []
if 'dispL' in entryTypes: disparityDefs.append(entryProto('dispL', 'FIXED16DIV32', 1))
if 'dispR' in entryTypes: disparityDefs.append(entryProto('dispR', 'FIXED16DIV32', 1))
if len(disparityDefs): txt += fileProto('disparity.bin', disparityDefs)
disparityChangeDefs = []
if 'forwardDispChangeL' in entryTypes: disparityChangeDefs.append(entryProto('forwardDispChangeL', 'FIXED16DIV32', 1))
if 'forwardDispChangeR' in entryTypes: disparityChangeDefs.append(entryProto('forwardDispChangeR', 'FIXED16DIV32', 1))
if 'backwardDispChangeL' in entryTypes: disparityChangeDefs.append(entryProto('backwardDispChangeL', 'FIXED16DIV32', 1))
if 'backwardDispChangeR' in entryTypes: disparityChangeDefs.append(entryProto('backwardDispChangeR', 'FIXED16DIV32', 1))
if len(disparityChangeDefs): txt += fileProto('disparity_change.bin', disparityChangeDefs)
txt += '\n'
open('%s/index.prototxt' % path, 'w').write(txt)
if len(cleanImageDefs): fCleanImage = open('%s/image_clean.bin' % path, 'w')
if len(finalImageDefs): fFinalImage = open('%s/image_final.bin' % path, 'w')
if len(flowDefs): fFlow = open('%s/flow.bin' % path, 'w')
if len(disparityDefs): fDisp = open('%s/disparity.bin' % path, 'w')
if len(disparityChangeDefs): fDispChange = open('%s/disparity_change.bin' % path, 'w')
for clip in clips:
for i in range(clip.startFrame(), clip.endFrame()+1):
frame = clip.frame(i)
print '%d:' % i
if 'cleanImageL' in entryTypes:
print 'cleanImageL:', frame.cleanImageL()
writeCleanImage(frame.cleanImageL())
if 'cleanImageR' in entryTypes:
print 'cleanImageR:', frame.cleanImageR()
writeCleanImage(frame.cleanImageR())
if 'finalImageL' in entryTypes:
print 'finalImageL:', frame.finalImageL()
writeFinalImage(frame.finalImageL())
if 'finalImageR' in entryTypes:
print 'finalImageR:', frame.finalImageR()
writeFinalImage(frame.finalImageR())
if not frame.last():
if 'forwardFlowL' in entryTypes:
print 'forwardFlowL:', frame.forwardFlowL()
writeFlow(frame.forwardFlowL())
if 'forwardFlowR' in entryTypes:
print 'forwardFlowR:', frame.forwardFlowR()
writeFlow(frame.forwardFlowR())
if 'forwardDispChangeL' in entryTypes:
print 'forwardDispChangeL', frame.forwardDispChangeL()
writeDispChangeL(frame.forwardDispChangeL())
if 'forwardDispChangeR' in entryTypes:
print 'forwardDispChangeR', frame.forwardDispChangeR()
writeDispChangeR(frame.forwardDispChangeR())
else:
if 'forwardFlowL' in entryTypes:
print 'forwardFlowL:', 0
writeFlow(0)
if 'forwardFlowR' in entryTypes:
print 'forwardFlowR:', 0
writeFlow(0)
if 'forwardDispChangeL' in entryTypes:
print 'forwardDispChangeL', 0
writeDispChangeL(0)
if 'forwardDispChangeL' in entryTypes:
print 'forwardDispChangeL', 0
writeDispChangeR(0)
if not frame.first():
if 'backwardFlowL' in entryTypes:
print 'backwardFlowL:', frame.backwardFlowL()
writeFlow(frame.backwardFlowL())
if 'backwardFlowR' in entryTypes:
print 'backwardFlowR:', frame.backwardFlowR()
writeFlow(frame.backwardFlowR())
if 'backwardDispChangeL' in entryTypes:
print 'backwardDispChangeL', frame.backwardDispChangeL()
writeDispChangeL(frame.backwardDispChangeL())
if 'backwardDispChangeR' in entryTypes:
print 'backwardDispChangeR', frame.backwardDispChangeR()
writeDispChangeR(frame.backwardDispChangeR())
else:
if 'backwardFlowL' in entryTypes:
print 'backwardFlowL:', 0
writeFlow(0)
if 'backwardFlowR' in entryTypes:
print 'backwardFlowR:', 0
writeFlow(0)
if 'backwardDispChangeL' in entryTypes:
print 'backwardDispChangeL', 0
writeDispChangeL(0)
if 'backwardDispChangeL' in entryTypes:
print 'backwardDispChangeL', 0
writeDispChangeR(0)
if 'dispL' in entryTypes:
print 'dispL:', frame.dispL()
writeDispL(frame.dispL())
if 'dispR' in entryTypes:
print 'dispR:', frame.dispR()
writeDispR(frame.dispR())
