def roidbToFeatures(roidb,
pyloader=roidbSampleHOG,
calcHog=False,
roidbSizes=None):
pyroidb = RoidbDataset(roidb, [0, 1, 2, 3, 4, 5, 6, 7],
loader=pyloader,
transform=None)
if roidbSizes is not None:
pyroidb.roidbSizes = np.arange(len(roidb)) + 1
l_feat,l_idx,y = extract_pyroidb_features(pyroidb, 'hog', cfg.clsToSet, calc_feat = calcHog, \
spatial_size=(32, 32),hist_bins=32, \
orient=9, pix_per_cell=8, cell_per_block=2, \
hog_channel=0)
return l_feat, l_idx, y
for size in datasetSizes:
# create a file for each dataset size
idlist_filename = createFilenameID(setID, str(r),
str(size))
repo_roidbs, roidbs_anno_counts = createMixtureDataset(
setID, size)
assert len(repo_roidbs) == setID.count('1')
# write pickle file of the roidb
allRoidb = combined_roidb(repo_roidbs)
onlyNewRoidb = combineOnlyNew(repo_roidbs, pc)
appendHOGtoRoidb(onlyNewRoidb)
pklName = idlist_filename + ".pkl"
print(pklName, roidbs_anno_counts, size)
pyroidb = RoidbDataset(allRoidb, [0, 1, 2, 3, 4, 5, 6, 7],
loader=roidbSampleBox,
transform=None)
printPyroidbSetCounts(pyroidb)
pyroidb = RoidbDataset(onlyNewRoidb,
[0, 1, 2, 3, 4, 5, 6, 7],
loader=roidbSampleBox,
transform=None)
printPyroidbSetCounts(pyroidb)
saveInfo = {
"allRoidb": onlyNewRoidb,
"annoCounts": roidbs_anno_counts
}
if osp.exists(pklName) is False:
with open(pklName, "wb") as f:
print("size: {}".format(size))
print_each_size(sizedRoidb)
print("-="*50)
# issue: we are getting zeros area for 5343 of bboxes for pascal_voc_2007
path = osp.join(prefix_path,"areas.dat")
np.savetxt(path,areas,fmt='%.18e',delimiter=' ')
path = osp.join(prefix_path,"widths.dat")
np.savetxt(path,widths,fmt='%.18e',delimiter=' ')
path = osp.join(prefix_path,"heights.dat")
np.savetxt(path,heights,fmt='%.18e',delimiter=' ')
pyroidb = RoidbDataset(roidb,[0,1,2,3,4,5,6,7],
loader=roidbSampleImageAndBox,
transform=pyroidbTransform_cropImageToBox)
if args.save:
index = imdb._get_roidb_index_at_size(30)
print("saving 30 imdb annotations to output folder...")
print(prefix_path)
for i in range(index):
boxes = roidb[i]['boxes']
if len(boxes) == 0: continue
im = cv2.imread(roidb[i]['image'])
if roidb[i]['flipped']:
im = im[:, ::-1, :]
cls = roidb[i]['gt_classes']
fn = osp.join(prefix_path,"{}_{}.png".format(imdb.name,i))
print(fn)
path = osp.join(prefix_path, "areas.dat")
np.savetxt(path, areas, fmt='%.18e', delimiter=' ')
path = osp.join(prefix_path, "widths.dat")
np.savetxt(path, widths, fmt='%.18e', delimiter=' ')
path = osp.join(prefix_path, "heights.dat")
np.savetxt(path, heights, fmt='%.18e', delimiter=' ')
print("-=-=-=-=-=-")
clsToSet = loadDatasetIndexDict()
print("as pytorch friendly ")
pyroidb = RoidbDataset(roidb, [1, 2, 3, 4, 5, 6, 7, 8],
loader=cv2.imread,
transform=cropImageToAnnoRegion)
if args.save:
print("save 30 cropped annos in output folder.")
saveDir = "./output/mixedDataReport/"
if not osp.exists(saveDir):
print("making directory: {}".format(saveDir))
os.makedirs(saveDir)
for i in range(30):
cls = roidb[i]['set']
ds = clsToSet[cls]
fn = osp.join(saveDir, "{}_{}.jpg".format(i, ds))
print(fn)
cv2.imwrite(fn, pyroidb[i][0])
path = osp.join(prefix_path, "heights.dat")
np.savetxt(path, heights, fmt='%.18e', delimiter=' ')
print("-=" * 50)
clsToSet = loadDatasetIndexDict()
print("as pytorch friendly ")
train_size = 500
test_size = 500
#cropped hog image input
pyroidb = RoidbDataset(roidb, [0, 1, 2, 3, 4, 5, 6, 7],
loader=roidbSampleHOG,
transform=None)
print('this is the annocount', annoCount)
l_feat,l_idx,y = extract_pyroidb_features(pyroidb, 'hog', clsToSet, calc_feat = False, \
spatial_size=(32, 32),hist_bins=32, \
orient=9, pix_per_cell=8, cell_per_block=2, \
hog_channel=0)
X_train, X_test, y_train, y_test, X_idx = split_data(train_size, test_size, \
l_feat,l_idx, y,\
clsToSet)
print(X_train.shape)
print(y_train.shape)
X_train, X_test = scale_data(X_train, X_test)
if args.size != -1:
datasetSizes = [args.size]
repeatRange = range(10)
if args.repeat != -1:
repeatRange = [args.repeat]
## load svm
for size in datasetSizes:
for repeat in range(repeatRange):
roidb,annoCount = load_mixture_set(setID,repeat,size)
print(annoCount)
numAnnos = computeTotalAnnosFromAnnoCount(annoCount)
clsToSet = loadDatasetIndexDict()
pyroidb = RoidbDataset(roidb,[0,1,2,3,4,5,6,7],
loader=roidbSampleBox,
transform=pyroidbTransform_normalizeBox)
annoMaps = annotationDensityPlot(pyroidb)
for idx,annoMap in enumerate(annoMaps):
print(" -=-=-=- dataset {} -=-=-=-=- ".format(clsToSet[idx]))
print("M1: {}".format(metric_1(annoMap,10)))
fnPrefix = "{}_{}_{}".format(clsToSet[idx],size,repeat)
plotDensityPlot(annoMap,fnPrefix)
saveRawAnnoPlot(annoMap,fnPrefix)
fnPrefix = "{}_{}_{}_hog_a".format(clsToSet[idx],size,repeat)
hogFts = HOGFromImage(annoMap.astype(np.float32))
saveHogFeatures(hogFts,fnPrefix)
fnPrefix = "{}_{}_{}_hog_b".format(clsToSet[idx],size,repeat)
path = osp.join(prefix_path, "areas.dat")
np.savetxt(path, areas, fmt='%.18e', delimiter=' ')
path = osp.join(prefix_path, "widths.dat")
np.savetxt(path, widths, fmt='%.18e', delimiter=' ')
path = osp.join(prefix_path, "heights.dat")
np.savetxt(path, heights, fmt='%.18e', delimiter=' ')
print("-=-=-=-=-=-")
clsToSet = loadDatasetIndexDict()
print("as pytorch friendly ")
pyroidb = RoidbDataset(roidb, [0, 1, 2, 3, 4, 5, 6, 7],
loader=cv2.imread,
transform=cropImageToAnnoRegion,
returnBox=False)
print(annoCount)
# printPyroidbSetCounts(pyroidb)
# print_each_size(roidb)
if args.save:
print("save 30 cropped annos in output folder.")
saveDir = "./output/mixedDataReport/"
if not osp.exists(saveDir):
print("making directory: {}".format(saveDir))
os.makedirs(saveDir)
print("pyroidb length: {}".format(len(pyroidb)))
randIdx = npr.permutation(len(pyroidb))
print_report(roidbTr, annoCountTr, roidbTe, annoCountTe, setID, repeat,
size)
print("-=" * 50)
clsToSet = loadDatasetIndexDict()
# add the "HOG" field to pyroidb
if args.appendHog:
resaveWithHog(setID, repeat)
print("as pytorch friendly ")
if args.pyroidb_type == "mixture":
pyroidb = RoidbDataset(roidbTr, [0, 1, 2, 3, 4, 5, 6, 7],
loader=roidbSampleImageAndBox,
transform=pyroidbTransform_cropImageToBox)
elif args.pyroidb_type == "hog":
pyroidb = RoidbDataset(roidbTr, [0, 1, 2, 3, 4, 5, 6, 7],
loader=roidbSampleHOG,
transform=None)
if args.save:
print("save 30 cropped annos in output folder.")
saveDir = "./output/mixedDataReport/"
if not osp.exists(saveDir):
print("making directory: {}".format(saveDir))
os.makedirs(saveDir)
print("pyroidb length: {}".format(len(pyroidb)))
# randIdx = npr.permutation(len(pyroidb))
randIdx = np.arange(len(pyroidb))
# create the repeat folder
path_repeat = createPathRepeat(setID,str(r))
if osp.isdir(path_repeat) == False:
os.makedirs(path_repeat)
# shuffle imdbs
shuffle_imdbs()
# reset previuos counters
zeroPreviousCounts()
for size in datasetSizes:
# create a file for each dataset size
idlist_filename = createFilenameID(setID,str(r),str(size))
repo_roidbs,roidbs_anno_counts = createMixtureDataset(setID,size)
assert len(repo_roidbs) == setID.count('1')
# write pickle file of the roidb
allRoidb = combined_roidb(repo_roidbs)
onlyNewRoidb = combineOnlyNew(repo_roidbs)
pklName = idlist_filename + ".pkl"
print(pklName,roidbs_anno_counts,size)
pyroidb = RoidbDataset(allRoidb,[0,1,2,3,4,5,6,7],loader=None,transform=None,returnBox=True)
printPyroidbSetCounts(pyroidb)
pyroidb = RoidbDataset(onlyNewRoidb,[0,1,2,3,4,5,6,7],loader=None,transform=None,returnBox=True)
printPyroidbSetCounts(pyroidb)
saveInfo = {"allRoidb":onlyNewRoidb,"annoCounts":roidbs_anno_counts}
if osp.exists(pklName) is False:
with open(pklName,"wb") as f:
pickle.dump(saveInfo,f)
else:
print("{} exists".format(pklName))
updatePreviousCounts(repo_roidbs)