def window_file_ptch_gt_euler_5():
prms, cPrms = mev2.ptch_pose_euler_smallnet_v5_fc5_exp1_lossl1()
wTest = prms.paths['windowFile']['test']
wFid = mpio.GenericWindowReader(wTest)
oName = 'ptch_test_euler-gt5.txt'
readFlag = True
count = 0
imDat, lbDat = [], []
while readFlag:
ims, lb = wFid.read_next()
if lb is None:
readFlag = False
continue
poseLb = lb[0][0:2]
mxTheta = 30 * max(np.abs(poseLb))
if mxTheta < 5 and not (lb[0][3] == 0):
continue
count += 1
imDat.append(ims)
lbDat.append([lb[0][3]])
if wFid.is_eof():
readFlag = False
wFid.close()
#Outside id
oFid = mpio.GenericWindowWriter(oName, count, 2, 1)
for c in range(count):
oFid.write(lbDat[c], *imDat[c])
oFid.close()
def make_pascal3d_generic_window():
srcFile = '/data1/pulkitag/data_sets/pascal_3d/my/window_file_%s.txt'
outFile = '/data1/pulkitag/data_sets/pascal_3d/my/generic_window_file_%s.txt'
setNames = ['train', 'val']
for s in setNames:
iFile = srcFile % s
oFile = outFile % s
with open(iFile) as fi:
lines = fi.readlines()
N = len(lines)
oFid = mpio.GenericWindowWriter(oFile, N, 1, 3)
for i, l in enumerate(lines[0:100]):
if np.mod(i, 1000) == 1:
print(i)
print l
fName, y1, y2, x1, x2, az, el, cl = l.strip().split()
im = cv2.imread(fName)
h, w, ch = im.shape
fSplit = fName.split('/')
assert fSplit[-3] == 'Images'
fName = fSplit[-2] + '/' + fSplit[-1]
y1, y2, x1, x2 = float(y1), float(y2), float(x1), float(x2)
az, el = float(az), float(el)
cl = int(cl)
imLine = [[fName, [ch, h, w], [x1, y1, x2, y2]]]
oFid.write([az, el, cl], *imLine)
def convert_pose_ptch_2_ptch(inFile, outFile):
inFid = mpio.GenericWindowReader(inFile)
outFid = mpio.GenericWindowWriter(outFile, inFid.num_, 2, 1)
while not inFid.is_eof():
imData, lb = inFid.read_next()
lbls = [[lb[0][2]]]
outFid.write(lbls[0], *imData)
inFid.close()
outFid.close()
def reform_window_file(fName='test-files/vegas_ptch_test.txt'):
fid = mpio.GenericWindowReader(fName)
oid = mpio.GenericWindowWriter('vegas.txt', fid.num_, 2, 1)
readFlag = True
while readFlag:
ims, lbs = fid.read_next()
lb = [lbs[0][0]]
oid.write(lb, *ims)
if fid.is_eof():
readFlag = False
def make_window_file(prms, setNames=['test', 'train']):
oldState = np.random.get_state()
seqCounts = ku.get_num_images()
for sNum, setName in enumerate(setNames):
seqNums = ku.get_train_test_seqnum(prms, setName)
setSeqCount = np.array([seqCounts[se]
for se in seqNums]).astype(np.float32)
sampleProb = setSeqCount / sum(setSeqCount)
im1, im2, ps = [], [], []
imSz1, imSz2 = [], []
totalSamples = 0
for ii, seq in enumerate(seqNums):
randSeed = (101 * sNum) + 2 * seq + 1
numSamples = int(
round(prms['numSamples'][setName] * sampleProb[ii]))
print "Storing %d samples for %d seq in set %s" % (numSamples, seq,
setName)
randState = np.random.RandomState(randSeed)
imT1, imT2, imSzT1, imSzT2, psT = get_imnames_and_pose(
prms, seq, numSamples, randState)
im1 = im1 + imT1
im2 = im2 + imT2
imSz1 = imSz1 + imSzT1
imSz2 = imSz2 + imSzT2
ps = ps + psT
totalSamples = totalSamples + len(imT1)
#Permute all the sequences togther
perm = randState.permutation(totalSamples)
im1 = [im1[p] for p in perm]
im2 = [im2[p] for p in perm]
imSz1 = [imSz1[p] for p in perm]
imSz2 = [imSz2[p] for p in perm]
ps = [ps[p] for p in perm]
#Save in the file
gen = mpio.GenericWindowWriter(prms['paths']['windowFile'][setName],
len(im1), 2, prms['labelSz'])
for i in range(len(im1)):
h, w, ch = imSz1[i]
l1 = [im1[i], [ch, h, w], [0, 0, w, h]]
h, w, ch = imSz2[i]
l2 = [im2[i], [ch, h, w], [0, 0, w, h]]
gen.write(ps[i], l1, l2)
gen.close()
np.random.set_state(oldState)
def make_window_file_by_folderid(prms, folderId, maxGroups=None):
if len(prms.labelNames) == 1 and prms.labelNames[0] == 'nrml':
numImPerExample = 1
else:
numImPerExample = 2
#Assuming the size of images
h, w, ch = prms.rawImSz, prms.rawImSz, 3
hCenter, wCenter = int(h / 2), int(w / 2)
cr = int(prms.crpSz / 2)
minH = max(0, hCenter - cr)
maxH = min(h, hCenter + cr)
minW = max(0, wCenter - cr)
maxW = min(w, wCenter + cr)
#Get the im-label data
lb, prefix = sls.get_label_by_folderid(prms, folderId, maxGroups=maxGroups)
#For the imNames
imNames1 = []
print('Window file for %s' % folderId)
imKeys = pickle.load(
open(prms.paths.proc.im.folder.keyFile % folderId, 'r'))
imKeys = imKeys['imKeys']
for pref in prefix:
tmpNames = []
_, p1, _, p2 = pref
tmpNames.append(osp.join(folderId, imKeys[p1]))
if p2 is not None:
tmpNames.append(osp.join(folderId, imKeys[p2]))
imNames1.append(tmpNames)
#Randomly permute the data
N = len(imNames1)
randState = np.random.RandomState(19)
perm = randState.permutation(N)
#The output file
wFile = prms.paths.exp.window.folderFile % folderId
wDir, _ = osp.split(wFile)
sp._mkdir(wDir)
gen = mpio.GenericWindowWriter(wFile, len(imNames1), numImPerExample,
prms['labelSz'])
for i in perm:
line = []
for n in range(numImPerExample):
line.append([imNames1[i][n], [ch, h, w], [minW, minH, maxW, maxH]])
gen.write(lb[i], *line)
gen.close()
def make_window_file():
prms = get_prms()
posDat = pickle.load(open(prms.paths.jpgPosKey, 'r'))['imNames']
negDat = pickle.load(open(prms.paths.jpgNegKey, 'r'))['imNames']
allDat = posDat + negDat
labels = np.ones((len(allDat), ))
labels[len(posDat):] = 0
perm = np.random.permutation(len(allDat))
allDat = [allDat[p] for p in perm]
labels = [labels[p] for p in perm]
N = len(allDat)
wFid = mpio.GenericWindowWriter(prms.paths.wFile, N, 2, 1)
for dat, lb in zip(allDat, labels):
line = []
line.append([dat[0], [3, 64, 64], [0, 0, 64, 64]])
line.append([dat[1], [3, 64, 64], [0, 0, 64, 64]])
wFid.write([lb], *line)
wFid.close()
def create_window_file():
setName = ['test', 'train']
for i,s in enumerate(setName):
inName = 'pose-files/annotations_master_%s_pascal3d.txt' % s
oName = 'pose-files/euler_%s_pascal3d.txt' % s
inFid = mpio.GenericWindowReader(inName)
imDat, lbls = [], []
N = inFid.num_
for i in range(inFid.num_):
im, lb = inFid.read_next()
imDat.append(im)
lbls.append(lb)
inFid.close()
randSeed = 3 + (2 * i)
randState = np.random.RandomState(randSeed)
perm = randState.permutation(N)
if s == 'train':
numBad = 2
else:
numBad = 0
oFid = mpio.GenericWindowWriter(oName, N-numBad, 1, 3)
for p in perm:
im, lb = imDat[p], lbls[p]
fName, ch, h, w, x1, y1, x2, y2 = im[0].strip().split()
x1, y1, x2, y2 = int(x1), int(y1), int(x2), int(y2)
if x2 <= x1 or y2 <= y1:
print ('Size is weird', x1,x2,y1,y2)
print ('Skipping', s, im)
continue
if x1 <0 or y1<0:
print ('Too small', x1, y1)
if x2 > w or y2 > h:
print ('Too big', x2, w, y2, h)
rots = []
for theta in lb[0]:
rots.append(su.rot_range(theta)/30.0)
rots.append(1.0)
oFid.write(rots, *im)
oFid.close()
def make_window_file(prms):
oldState = np.random.get_state()
for sNum, setName in enumerate(['test', 'train']):
im1, im2, label = get_names_and_label(prms, setName)
N = len(im1)
randSeed = 2 * sNum + 1
randState = np.random.RandomState(randSeed)
#Permute all the sequences togther
perm = randState.permutation(N)
im1 = [im1[p] for p in perm]
im2 = [im2[p] for p in perm]
ps = [label[p] for p in perm]
#Save in the file
gen = mpio.GenericWindowWriter(prms['paths']['windowFile'][setName],
len(im1), 2, prms['labelSz'])
h, w, ch = 320, 480, 3
for i in range(len(im1)):
l1 = [im1[i], [ch, h, w], [0, 0, w, h]]
l2 = [im2[i], [ch, h, w], [0, 0, w, h]]
gen.write(ps[i], l1, l2)
gen.close()
np.random.set_state(oldState)
def make_combined_window_file(prms, setName='train'):
keys = sp.get_train_test_defs(prms.geoFence, setName=setName)
wObjs, wNum = [], []
numIm = None
for i, k in enumerate(keys):
wFile = prms.paths.exp.window.folderFile % k
wObj = mpio.GenericWindowReader(wFile)
wNum.append(wObj.num_)
wObjs.append(wObj)
if i == 0:
numIm = wObj.numIm_
else:
assert numIm == wObj.numIm_, '%d, %d' % (numIm, wObj.num_)
nExamples = sum(wNum)
N = min(nExamples, int(prms.splits.num[setName]))
mainWFile = mpio.GenericWindowWriter(prms['paths']['windowFile'][setName],
N, numIm, prms['labelSz'])
print('Total examples to chose from: %d' % sum(wNum))
wCount = copy.deepcopy(np.array(wNum))
wNum = np.array(wNum).astype(float)
wNum = wNum / sum(wNum)
pCum = np.cumsum(wNum)
print(pCum)
assert pCum[-1] == 1, 'Something is wrong'
randState = np.random.RandomState(31)
ignoreCount = 0
nrmlPrune = False
if 'nrml' in prms.labelNames and len(prms.labelNames) == 1:
if prms.nrmlMakeUni is not None:
idx = prms.labelNames.index('nrml')
lbInfo = prms.labels[idx]
nrmlPrune = True
if lbInfo.loss_ in ['l2', 'l1']:
nrmlBins = np.linspace(-180, 180, 101)
binCounts = np.zeros((2, 101))
elif lbInfo.loss_ == 'classify':
nrmlBins = np.array(range(lbInfo.numBins_ + 1))
binCounts = np.zeros((2, lbInfo.numBins_))
mxBinCount = int(prms.nrmlMakeUni * np.sum(wCount))
print('mxBinCount :%d' % mxBinCount)
#Get the normalization data if required
if prms['lbNrmlz'] is not None:
nrmlzDat = get_label_stats(prms)
writeCount = 0
for i in range(N):
sampleFlag = True
idx = None
while sampleFlag:
rand = randState.rand()
idx = su.find_first_false(rand >= pCum)
if not wObjs[idx].is_eof():
sampleFlag = False
else:
ignoreCount += 1
if ignoreCount > 2000:
print(ignoreCount, 'Resetting prob distribution')
pCum = np.cumsum(wCount / float(sum(wCount)))
print pCum
ignoreCount = 0
wCount[idx] -= 1
imNames, lbls = wObjs[idx].read_next()
if prms['lbNrmlz'] is not None:
if prms['lbNrmlz'] == 'zscore':
mu, sd = nrmlzDat
else:
raise Exception('lbNrmlz %s not recognized' % prms['lbNrmlz'])
assert len(prms.labels
) == 1, 'This needs to be generalized for multi-labels'
for lbIdx in range(prms.labels[0].lbSz_):
lbls[0][lbIdx] = (lbls[0][lbIdx] - mu[lbIdx]) / sd[lbIdx]
if nrmlPrune:
nrmlIdx = randState.permutation(2)[0]
binIdx = find_bin_index(nrmlBins, lbls[0][nrmlIdx])
if binCounts[nrmlIdx][binIdx] < mxBinCount:
binCounts[nrmlIdx][binIdx] += 1
else:
continue
try:
mainWFile.write(lbls[0], *imNames)
except:
print 'Error'
pdb.set_trace()
writeCount += 1
mainWFile.close()
#Only if nrml labels are being considered
#Get the count correct for nrmlPrune scenarios
if nrmlPrune:
imNames, lbls = [], []
mainWFile = mpio.GenericWindowReader(prms.paths.windowFile[setName])
readFlag = True
readCount = 0
while readFlag:
name, lb = mainWFile.read_next()
imNames.append(name)
lbls.append(lb)
readCount += 1
if readCount == writeCount:
readFlag = False
mainWFile.close()
#Write the corrected version
mainWFile = mpio.GenericWindowWriter(
prms['paths']['windowFile'][setName], writeCount, numIm,
prms['labelSz'])
for n in range(writeCount):
mainWFile.write(lbls[n][0], *imNames[n])
mainWFile.close()
def create_window_file_v2(imSz=256, padSz=24, debugMode=False):
dName = '/data0/pulkitag/data_sets/pascal_3d/imCrop'
dName = osp.join(dName, 'imSz%d_pad%d_hash') % (imSz, padSz)
svFile = 'f%s/im%s.jpg' % ('%d', '%d')
srcDir = '/data0/pulkitag/pascal3d/Images'
setName = ['train', 'test']
count, fCount = 0, 0
fStore = edict()
for si, s in enumerate(setName):
inName = 'pose-files/annotations_master_%s_pascal3d.txt' % s
oName = 'pose-files/euler_%s_pascal3d_imSz%d_pdSz%d.txt' % (s, imSz, padSz)
oFile = 'pose-files/pascal3d_dict_%s_imSz%d_pdSz%d.pkl' % (s, imSz, padSz)
inFid = mpio.GenericWindowReader(inName)
imDat, lbls = [], []
N = inFid.num_
for i in range(inFid.num_):
im, lb = inFid.read_next()
imDat.append(im)
lbls.append(lb)
inFid.close()
randSeed = 7
randState = np.random.RandomState(randSeed)
perm = randState.permutation(N)
if s == 'train':
numBad = 2
else:
numBad = 0
print (len(perm))
imList = []
lbList = []
for rep, p in enumerate(perm):
if np.mod(rep,1000)==1:
print (rep, fCount, count)
im, lb = imDat[p], lbls[p]
lb = lb[0]
srcImName, ch, h, w, x1, y1, x2, y2 = im[0].strip().split()
x1, y1, x2, y2, h, w = int(x1), int(y1), int(x2), int(y2), int(h), int(w)
if x2 <= x1 or y2 <= y1:
print ('Size is weird', x1,x2,y1,y2)
print ('Skipping', s, im)
continue
if x1 <0 or y1<0:
print ('Too small', x1, y1)
continue
if x2 > w or y2 > h:
print ('Too big', x2, w, y2, h)
continue
srcImPrefix = srcImName[0:-4]
svImName = svFile % (fCount, np.mod(count,1000))
if srcImPrefix not in fStore.keys():
fStore[srcImPrefix] = edict()
fStore[srcImPrefix].name = [svImName]
fStore[srcImPrefix].coords = [(x1,y1,x2,y2)]
else:
fStore[srcImPrefix].name.append(svImName)
fStore[srcImPrefix].coords.append((x1,y1,x2,y2))
count += 1
if np.mod(count,1000) == 0:
fCount += 1
#Read and crop the image
xOg1, yOg1, xOg2, yOg2 = x1, y1, x2, y2
x1, y1, x2, y2 , xPad, yPad= crop_for_imsize((h, w, x1, y1, x2, y2), imSz, padSz)
im = scm.imread(osp.join(srcDir, srcImName))
if im.ndim == 2:
im = color.gray2rgb(im)
hIm, wIm, chIm = im.shape
assert hIm==h and wIm==w and chIm==3,(hIm, wIm, chIm, h, w)
im = cv2.resize(im[y1:y2, x1:x2,:], (imSz, imSz), interpolation=cv2.INTER_LINEAR)
#get filestr
fStr = get_filename(svImName)
fMirrorStr = get_filename(svImName, isMirror=True)
svName = osp.join(dName, fStr)
ou.mkdir(osp.dirname(svName))
scm.imsave(svName, im)
#print (svName)
#pdb.set_trace()
if debugMode:
imList.append([fStr, fName, (xOg1, yOg1, xOg2, yOg2), chIm,
imSz, imSz, 0, 0, imSz, imSz, xPad, yPad])
else:
imList.append([fStr, (chIm, imSz, imSz), (0, 0, imSz, imSz)])
lbList.append(format_raw_label(lb))
#Mirror the image
im = im[:,::-1,:]
lbMirror = copy.deepcopy(lb)
#For pascal images, azimuth becomes negative, but elevation doesnot change
lbMirror[0] = -lb[0]
svName = osp.join(dName, fMirrorStr)
scm.imsave(svName, im)
if debugMode:
imList.append([fMirrorStr, fName, (xOg1, yOg1, xOg2, yOg2), chIm,
imSz, imSz, 0, 0, imSz, imSz, xPad, yPad])
else:
imList.append([fMirrorStr, (chIm, imSz, imSz), (0, 0, imSz, imSz)])
lbList.append(format_raw_label(lbMirror))
#Write to window file
N = len(imList)
perm = randState.permutation(N)
oFid = mpio.GenericWindowWriter(oName, N, 1, 2)
for p in perm:
oFid.write(lbList[p], imList[p])
oFid.close()
if debugMode:
return imList, lbList