def split_file(path, folders):
""" Create the set of splits for a single file.
Parameters:
-----------
path: string
path to the input Decompressed file
folders: dict
dictionary containing the id of the split as key
and the path to the folder where the split is
saved as value.
"""
filerels = fh.DecompressedFile(path)
idx2rels = {}
with filerels as frels:
fname_in = frels.filename
for idfr, arr in frels.iterate_frames():
idx2rels[idfr] = arr
for split in sorted(folders):
perc = int(len(idx2rels)*split/100)
logger.info('Creating split with {}%: {}*0.{} = {} observations'.format(split, len(idx2rels), split, perc))
indexes = list(idx2rels.keys())
sampling = random.choices(indexes, k=perc)
fileoutput = join(folders[split], fname_in)
save_file(fileoutput, sampling, idx2rels)
def compress_relations(file_input,
output=None,
file_types='types.pddl',
class_file='classes.cfg',
rels_file='relations.cfg',
keep_names=False):
if not output:
fname, _ = splitext(basename(file_input))
output = join(dirname(file_input), fname + '_predicates.txt')
# Load classes for objects from dict {0: 'rel0', 1: 'rel1'}
do = fh.ConfigFile(class_file).load_classes(cnames=True)
logger.info('Loaded dictionary with {} objects.'.format(len(do)))
dr = fh.ConfigFile(rels_file).load_classes(cnames=True)
logger.info('Loaded dictionary with {} relations.'.format(len(dr)))
dp = fh.PddlTypes(file_types)
df = fh.DecompressedFile(file_input)
rels = df.list_relations()
relations = []
for s, r, o in rels:
s = s.replace('_', '-')
o = o.replace('_', '-')
relations.append((r, dp[s], dp[o]))
relations.append((r, (s, dp[s][1]), (o, dp[o][1])))
with open(output, 'w') as fout:
fout.write('(:predicates\n')
for r, s, o in sorted(set(relations)):
# (on ?f - food ?o - object)
fout.write(' (%s ?%s - %s ?%s - %s)\n' %
(r, s[1], s[0], o[1], o[0]))
fout.write(')')
logger.info('File saved at: %s' % output)
def sanitize_relations(file_relations, config_file):
""" Check whether a file containing relations is according with the possible relations
described in the `config_file` file.
"""
logger.info('Checking file: {}'.format(file_relations))
verify_sequence_frames(file_relations)
drels = load_possible_relations(config_file)
# Load groups of relations for frame
errors = 0
recorded = {}
frls = fh.DecompressedFile(file_relations)
with frls as frels:
for arr in frels:
fr, o1, r, o2 = arr[0], arr[1], arr[2], arr[3]
pathimg = str(fr)+'.jpg'
if not drels.has_key((o1, r, o2)) and not recorded.has_key((o1, r, o2)):
logger.error('There is not possible relation: [{}, {}, {}]'.format(o1, r, o2))
recorded[(o1, r, o2)] = ''
errors += 1
if errors:
logger.info('Finished WITH {} errors!'.format(errors))
else:
logger.info('Finished without errors!')
def show_relations(file_input,
output=None,
class_file='classes.cfg',
rels_file='relations.cfg',
keep_names=False):
if not output:
fname, _ = splitext(basename(file_input))
output = join(dirname(file_input), fname + '_list.txt')
# Load classes for objects from dict {0: 'rel0', 1: 'rel1'}
do = fh.ConfigFile(class_file).load_classes(cnames=True)
logger.info('Loaded dictionary with {} objects.'.format(len(do)))
dr = fh.ConfigFile(rels_file).load_classes(cnames=True)
logger.info('Loaded dictionary with {} relations.'.format(len(dr)))
# Check whether the file contains names or ids
with open(file_input) as fin:
for line in fin:
if line[0].isdigit():
break
arr = line.strip().split('-')
if len(arr) == 5:
#0-15-o1-r-o2
handler = fh.CompressedFile(file_input)
else:
#0-o1,r,o2
handler = fh.DecompressedFile(file_input)
list_rels = handler.list_relations(as_set=True)
with open(output, 'w') as fout:
for o1, r, o2 in sorted(list_rels):
fout.write('{} {} {}\n'.format(o1, r, o2))
logger.info('File saved at: %s' % output)
def load_relations(file_relations, do, dr, dmap=None, home=None):
""" Returns a dictionary containing the form
drels[path_img] = [(idsub1, idrel1, idobj1), (idsub2, idrel2, idobj2),...]
Parameters:
-----------
file_relations: string
path to the Decompressed file containing relations
do: dict
dictionary in the form {'object_1': idobj1, 'object_2': idobj2...}
dr: dict
dictionary in the form {'relation1': idrel1, 'relation2': idrel2...}
dmap: dict
dictionary with maps from KSCGR to VOC dataset {'kscgr_path1': voc_path1,...}
home: string
path to the files in the server, such as '/usr/share/datasets/VOC/'
"""
dic_rels = defaultdict(list) # relations for each image
logger.info('Loading information from file: {}'.format(file_relations))
filerls = fh.DecompressedFile(file_relations)
pb = pbar.ProgressBar(filerls.nb_lines())
with filerls as frels:
for fr, o1, r, o2, path in frels:
#print fr, o1, r, o2, path
idsub = do[o1]
idrel = dr[r]
idobj = do[o2]
pathimg = join(path, str(fr) + '.jpg')
if dmap:
pathimg = dmap[join(home, pathimg)]
dic_rels[pathimg].append((idsub, idrel, idobj))
pb.update()
return dic_rels
def _extract_relations(self, folder_input):
""" Extract relations (sub, rel, obj) from multiple files. """
relations = []
logger.info('Generating dictionary...')
relfiles = fh.FolderHandler(folder_input)
for file_input in relfiles:
with fh.DecompressedFile(file_input) as cf:
relations.extend(cf.list_relations())
return relations
def cohen_kappa_relations(fanno_1, fanno_2):
dic = {}
annotator1 = []
annotator2 = []
fd1 = fh.DecompressedFile(fanno_1)
fd2 = fh.DecompressedFile(fanno_2)
for arr1, arr2 in zip(fd1.iterate_frames(), fd2.iterate_frames()):
idf1, vec1 = arr1
idf2, vec2 = arr2
convert_list(dic, vec1)
convert_list(dic, vec2)
if idf1 != idf2:
logger.error(
'Files do not contain the same sequence of frames: {}/{}'.
format(idf1, idf2))
sys.exit()
v1, v2 = align_lists(vec1, vec2)
annotator1.extend(v1)
annotator2.extend(v2)
kappa = cohen_kappa_score(annotator1, annotator2)
print(kappa)
print('Finished')
def main(inputfile,
output=None,
class_file='classes.cfg',
rels_file='relations.cfg'):
"""
Create a `so_prior.pkl` file containing the relationship between objects.
"""
if not output:
output = join(dirname(inputfile), 'so_prior.pkl')
# Load classes for objects from dict {0: 'rel0', 1: 'rel1'}
# DO NOT LOAD `__background__`, thus id_person=0
do = fh.ConfigFile(class_file, background=False).load_classes(cnames=True)
logger.info('Loaded dictionary with {} objects.'.format(len(do)))
dr = fh.ConfigFile(rels_file).load_classes(cnames=True)
logger.info('Loaded dictionary with {} relations.'.format(len(dr)))
so_prior = np.zeros((len(do), len(do), len(dr)), dtype='float64')
objsub = np.zeros((len(do), len(do)), dtype='float64')
logger.info('Matrix of objects and relations with shape: {}'.format(
so_prior.shape))
logger.info('Matrix of only objects with shape: {}'.format(objsub.shape))
filerels = fh.DecompressedFile(inputfile)
logger.info('Loading information from file: {}'.format(inputfile))
nb_lines = filerels.nb_lines()
pb = pbar.ProgressBar(nb_lines)
logger.info('Processing {} lines...'.format(nb_lines))
with filerels as frels:
for arr in frels:
fr, o1, r, o2 = arr[0], arr[1], arr[2], arr[3]
idsub = do[o1]
idrel = dr[r]
idobj = do[o2]
so_prior[idsub][idobj][idrel] += 1
objsub[idsub][idobj] += 1
pb.update()
print
for i in range(so_prior.shape[2]):
so_prior[:, :, i] = np.divide(so_prior[:, :, i],
objsub,
out=np.zeros_like(so_prior[:, :, i]),
where=objsub != 0)
fout = open(output, 'wb')
cPickle.dump(so_prior, fout)
fout.close()
logger.info('Saved content in file: {}'.format(output))
def goal_state_from_file(fileinput, output=None):
""" Extract the goal state for a single file.
In case of having `output`, the goal state is saved into a file.
Parameters:
-----------
fileinput: string
path to the DecompressedFile containing relations
output: string (optional)
path to the output file
"""
fd = fh.DecompressedFile(fileinput)
rels = fd.relations_at_frame(fd.nb_frames() - 1)
rels = check_group(rels)
if output:
save_goal(rels)
return rels
def preconditions_effects_pair(file_input, srep, dprec):
last_state = []
current_state = []
logger.info('Processing file: {}'.format(file_input))
config = fh.PDDLInit()
dinit = config.dic_initial_states()
last_state = State(srep, dinit)
with fh.DecompressedFile(file_input) as cf:
for idfr, relations in cf.iterate_frames():
#print idfr, State(srep, relations).state
current_state = State(srep, relations)
if current_state != last_state:
effect = last_state.XORe(current_state)
nb = len(dprec)
dprec[nb] = (last_state, effect)
last_state = current_state
return dprec
def preconditions_effects(file_input, srep, dprec, dinit):
""" Generate the preconditions and effects of each action """
last_state = []
current_state = []
logger.info('Processing file: {}'.format(file_input))
last_state = State(srep, dinit)
with fh.DecompressedFile(file_input) as cf:
for idfr, relations in cf.iterate_frames():
#print idfr, State(srep, relations).state
current_state = State(srep, relations)
if current_state != last_state:
effect = last_state.XORe(current_state)
if effect in dprec:
dprec[effect].append(last_state)
else:
dprec[effect] = [last_state]
last_state = current_state
return dprec
def preconditions_effects_solo(file_input, srep, dprec):
last_state = []
current_state = []
logger.info('Processing file: {}'.format(file_input))
nb = 0
with fh.DecompressedFile(file_input) as cf:
for idfr, relations in cf.iterate_frames():
#print idfr, State(srep, relations).state
if idfr == 0:
last_state = State(srep, relations)
else:
current_state = State(srep, relations)
if current_state != last_state:
effect = last_state.XORe(current_state)
if effect in dprec:
dprec[effect].append(last_state)
else:
dprec[effect] = [last_state]
nb += 1
last_state = current_state
return dprec
def compress_relations(file_input,
output=None,
class_file='classes.cfg',
rels_file='relations.cfg',
keep_names=False):
if not output:
fname, _ = splitext(basename(file_input))
output = join(dirname(file_input), fname + '_compressed.txt')
# Load classes for objects from dict {0: 'rel0', 1: 'rel1'}
do = fh.ConfigFile(class_file).load_classes(cnames=True)
logger.info('Loaded dictionary with {} objects.'.format(len(do)))
dr = fh.ConfigFile(rels_file).load_classes(cnames=True)
logger.info('Loaded dictionary with {} relations.'.format(len(dr)))
df = fh.DecompressedFile(file_input)
dcomp = df.group_relations()
logger.info(
'Found {} relations spread on {} lines of the input file.'.format(
len(df.start_frames), df.nb_line - 1))
logger.info('Compressed to {} lines in output file.'.format(
len(df.start_frames)))
logger.info('Saving output file...')
with open(output, 'w') as fout:
if keep_names:
fout.write('Initial_frame-Final_frame Subject Relation Object\n')
else:
fout.write('Initial_frame-Final_frame-Subject-Relation-Object\n')
for _, key in sorted(df.start_frames):
start, end = dcomp[key]['contiguous'].pop(0)
subj, rel, obj = key
if keep_names:
fout.write('%d-%d %s %s %s\n' % (start, end, subj, rel, obj))
else:
fout.write('%d-%d-%d-%d-%d\n' %
(start, end, do[subj], dr[rel], do[obj]))
logger.info('File saved at: %s' % output)
def sanitize_for_bounding_boxes(file_objects, file_relations, output=None):
""" Check whether a file of relations is according with the bouding boxes
described in the `file_objects` file.
"""
if not output:
fname, ext = splitext(basename(file_relations))
output = join(dirname(file_relations), fname+'_sanity'+ext)
verify_sequence_frames(file_objects)
verify_sequence_frames(file_relations)
drels = defaultdict(list)
# Load groups of relations for frame
frls = fh.DecompressedFile(file_relations)
with frls as frels:
for arr in frels:
fr, o1, r, o2 = arr[0], arr[1], arr[2], arr[3]
pathimg = str(fr)+'.jpg'
drels[pathimg].append((fr, o1, r, o2))
logger.info('Loaded relations for {} frames.'.format(len(drels)))
errors = 0
filelis = fh.LisFile(file_objects)
with open(output, 'w') as fout, filelis as flis:
fout.write('Frame\tSubject\tRelation\tObject\tPath: {}\n'.format(frls.path))
for pathimg, arr in flis.iterate_frames():
objects = [bbox[0] for bbox in arr]
relations = drels[pathimg]
for fr, o1, r, o2 in relations:
if check_error(objects, o1, pathimg) and check_error(objects, o2, pathimg):
fout.write('{}\t{}\t{}\t{}\n'.format(fr, o1, r, o2))
else:
errors += 1
if errors:
logger.info('Finished WITH {} errors!'.format(errors))
else:
os.remove(output)
logger.info('Finished without errors!')
def merge_annotation(folder_input, output=None, class_file='classes.cfg', rels_file='relations.cfg'):
if not output:
output = join(folder_input, 'merged_relations.txt')
# Load classes for objects from dict {0: 'rel0', 1: 'rel1'}
do = fh.ConfigFile(class_file).load_classes(cnames=True)
logger.info('Loaded dictionary with {} objects.'.format(len(do)))
dr = fh.ConfigFile(rels_file).load_classes(cnames=True)
logger.info('Loaded dictionary with {} relations.'.format(len(dr)))
files = fh.FolderHandler(folder_input)
with open(output, 'w') as fout:
fout.write('Frame\tSubject\tRelation\tObject\tPath\n')
for path in files:
logger.info('Processing file: %s' % path)
filerels = fh.DecompressedFile(path)
with filerels as frels:
for fr, o1, r, o2 in frels:
check_error(do, o1, frels.nb_lines)
check_error(do, o2, frels.nb_lines)
check_error(dr, r, frels.nb_lines)
fout.write('%d\t%s\t%s\t%s\t%s\n' % (fr, o1, r, o2, filerels.path))
logger.info('Saved relations in file: %s' % output)
def main(fileobj,
filerel,
output=None,
class_file='classes.cfg',
rels_file='relations.cfg',
map_paths='map_paths.txt'):
"""
Create a `train.pkl` or 'test.pkl` file containing the relationship between objects.
TODO: Implement relations for two objects of the same class in the same image
"""
if not output:
output = join(dirname(fileobj), 'train.pkl')
fdicobj = join(dirname(output), 'obj.txt')
fdicrel = join(dirname(output), 'rel.txt')
if map_paths:
fmap = fh.MapFile(map_paths)
dmap = fmap.load_dictionary(key='kscgr')
logger.info('Loaded map file containing {} entries.'.format(len(dmap)))
home = fmap.path
# Load classes for objects from dict {0: 'rel0', 1: 'rel1'}
# DO NOT LOAD `__background__`. Thus, id_person=0
do = fh.ConfigFile(class_file, background=False).load_classes(cnames=True)
logger.info('Loaded dictionary with {} objects.'.format(len(do)))
dr = fh.ConfigFile(rels_file).load_classes(cnames=True)
logger.info('Loaded dictionary with {} relations.'.format(len(dr)))
dic_rels = defaultdict(list) # relations for each image
logger.info('Loading information from file: {}'.format(filerel))
filerls = fh.DecompressedFile(filerel)
pb = pbar.ProgressBar(filerls.nb_lines())
with filerls as frels:
for fr, o1, r, o2, path in frels:
idsub = do[o1]
idrel = dr[r]
idobj = do[o2]
pathimg = join(path, str(fr) + '.jpg')
if map_paths:
pathimg = dmap[join(home, pathimg)]
dic_rels[pathimg].append((idsub, idrel, idobj))
pb.update()
print
info = []
# Load objects
logger.info('Loading information from file: {}'.format(fileobj))
flis = fh.LisFile(fileobj)
nb_frames = filerls.nb_frames()
pb = pbar.ProgressBar(nb_frames)
logger.info('Processing {} frames.'.format(nb_frames))
with flis as fin:
for imgname, arr in flis.iterate_frames():
filepath = dmap[join(home, imgname)]
classes, boxes = [], []
vsub, vobj, vrel = [], [], []
dor = {}
for i in range(len(arr)):
obj, x, y, w, h = arr[i]
iobj = do[obj]
dor[iobj] = i
classes.append(iobj)
boxes.append([x, y, x + w, y + w]) # [xmin,ymin,xmax,ymax]
for idsub, idrel, idobj in dic_rels[filepath]:
vsub.append(dor[idsub])
vobj.append(dor[idobj])
vrel.append([idrel])
info.append({
'img_path': filepath,
'classes': np.array(classes),
'boxes': np.array(boxes),
'ix1': np.array(vsub),
'ix2': np.array(vobj),
'rel_classes': vrel
})
pb.update()
logger.info('Saving pickle file...')
fout = open(output, 'wb')
cPickle.dump(info, fout)
fout.close()
logger.info('Saved content in file: {}'.format(output))
save_dictionary(fdicobj, do)
save_dictionary(fdicrel, dr)