def Load_Aligned_Data():
'''Function that read already downloaded files.
Returns a mmdatasdk class with speech and text
multimodal data features'''
dataset_set = {"glove_vectors.csd", "COVAREP.csd", "Sentiment Labels.csd"}
dataset_dictionary = {}
BASE_PATH = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
path = os.path.join(BASE_PATH, 'dataloaders/mosei_aligned')
if os.path.isdir(path) is False:
print("Folder does not exist ...")
exit(-1)
csdfiles = [
f for f in listdir(path)
if isfile(join(path, f)) and f[-4:] == '.csd' and (f in dataset_set)
]
if len(csdfiles) == 0:
print("No csd files in the given folder")
exit(-2)
print("%d csd files found" % len(csdfiles))
for csdfile in csdfiles:
dataset_dictionary[csdfile] = os.path.join(path, csdfile)
dataset = mmdatasdk.mmdataset(dataset_dictionary)
print("List of the computational sequences")
print(dataset.computational_sequences.keys())
return (dataset)
def ReadDlData(name_dict, path):
'''Function that read already downloaded files
from specified given path which is given as
input argument. Returns a mmdatasdk class with
all available multimodal data features'''
url_dictionary = InverseMap(name_dict)
dataset_dictionary={}
if os.path.isdir(path) is False:
print ("Folder does not exist ...")
exit(-1)
csdfiles = [f for f in listdir(path) if isfile(join(path, f)) and f[-4:]=='.csd']
if len(csdfiles)==0:
print("No csd files in the given folder")
exit(-2)
highlevel_names = SearchDictKeys(url_dictionary, csdfiles)
print("%d csd files found"%len(csdfiles))
for csdfile in csdfiles:
dataset_dictionary[highlevel_names[csdfile]]=os.path.join(path,csdfile)
dataset=mmdatasdk.mmdataset(dataset_dictionary)
print ("List of the computational sequences")
print (dataset.computational_sequences.keys())
return(dataset)
def add_labels(cmumosi_higlevel):
cmumosi_highlevel.add_computational_sequences(mmdatasdk.cmu_mosi.labels,
'cmumosi/')
cmumosi_highlevel.align('Opinion Segment Labels')
deploy_files = {
x: x
for x in cmumosi_highlevel.computational_sequences.keys()
}
cmumosi_highlevel.deploy('aligned/', deploy_files)
aligned_cmumosi_highlevel = mmdatasdk.mmdataset('aligned/')
return (cmumosi_higlevel)
return np.average(features, axis=0)
def directory_check(dirName):
exists = True
if os.path.exists(dirName) and os.path.isdir(dirName):
if not os.listdir(dirName):
print("MOSEI Directory is empty")
exists = False
else:
print("MOSEI Directory is not empty")
else:
print("MOSEI Directory doesn't exist")
exists = False
return exists
cmumosei_path = '/ssd/speech_data/cmumosei/'
if directory_check(cmumosei_path):
# aling CMU-MOSEI
cmumosei_highlevel = ReadDlData(mmdatasdk.cmu_mosei.highlevel, cmumosei_path)
cmumosei_highlevel.align('glove_vectors', collapse_functions=[average])
cmumosei_highlevel.add_computational_sequences(mmdatasdk.cmu_mosei.labels, 'cmumosei/')
cmumosei_highlevel.align('Sentiment Labels') # 'Emotion Labels' available as well
deploy_files = {x:x for x in cmumosei_highlevel.computational_sequences.keys()}
cmumosei_highlevel.deploy('mosei_aligned/', deploy_files)
aligned_cmumosei_highlevel = mmdatasdk.mmdataset('mosei_aligned/')
print("MOSI Directory is not empty")
else:
print("MOSI Directory doesn't exist")
exists = False
return (exists)
BASE_PATH = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
cmumosi_path = os.path.join(BASE_PATH, 'cmumosi')
aligned_path = os.path.join(BASE_PATH, 'aligned')
print("preaparing CMU MOSI download")
if not directory_check(cmumosi_path):
## execute the following command only once
print(".....mosi is being downloaded")
cmumosi_highlevel = mmdatasdk.mmdataset(mmdatasdk.cmu_mosi.highlevel,
'cmumosi/')
else:
print("mosi is already downloaded")
cmumosi_highlevel = ReadDlData(mmdatasdk.cmu_mosi.highlevel, cmumosi_path)
cmumosi_highlevel.align('glove_vectors', collapse_functions=[myavg])
cmumosi_highlevel.add_computational_sequences(mmdatasdk.cmu_mosi.labels,
'cmumosi/')
size_list = [9216, 74, 47, 300, 1585]
cmumosi_highlevel.align('Opinion Segment Labels')
deploy_files = {x: x for x in cmumosi_highlevel.computational_sequences.keys()}
cmumosi_highlevel.deploy('aligned/', deploy_files)
aligned_cmumosi_highlevel = mmdatasdk.mmdataset('aligned/')
#cmumosi_highlevel = add_labels(cmumosi_highlev)