def buttonPushed():
data = None
word_thresh=0.01
objects = []
verb_forms = {}
spec_post = False
with_preps = True
print "success"
newhognew(file1)
svminput.svminputfn()
svmfile.svmfilefn()
#classi()
#print file1
#txt.insert(END, file1)
data = yaml.load(file('C:/meenuneenu/project/libsvm-3.17/python/detail.txt', 'r'))
pickle.dump(data, open("C:/meenuneenu/project/libsvm-3.17/python/pickled_files/data.pk", "wb"))
learn_obj = learn(objects, word_thresh)
gen_obj = Generator(learn_obj, data, spec_post, with_preps)
final_sentence=gen_obj.run()
for post_id in sorted(final_sentence):
print "***", post_id
for s_num in final_sentence[post_id]:
for sentence in final_sentence[post_id][s_num]:
#print sentence + '.'+ '\n'
txt.insert(END, sentence)
txt.insert(END, '.\n')
deletefiles()
def get_detections(self, data={}):
label = ""
if data == {}:
data = self.data
for a in data:
last_label = label
try:
label = self.learn_obj.label_hash[a['label']]
except KeyError:
label = a['label']
except:
txt.insert(END, 'No sentence')
deletefiles()
id_n = str(a['id'])
post_id = a['post_id']
# Generating for just a single image.
if self.spec_post and post_id != self.spec_post:
continue
try:
self.label_id_hash[post_id][id_n] = label
except KeyError:
self.label_id_hash[post_id] = {id_n:label}
try:
if a['preps'] == {}:
self.prep_detections[post_id] = {}
for id_set in a['preps']:
ids = id_set.split(",")
id1 = ids[0].strip("'")
id2 = ids[1].strip("'")
try:
self.prep_detections[post_id][(id1, id2)] = a['preps'][id_set]
except KeyError:
self.prep_detections[post_id] = {(id1, id2): a['preps'][id_set]}
except KeyError:
pass
try:
self.mod_detections[post_id][id_n] = {}
except KeyError:
self.mod_detections[post_id] = {id_n:{}}
try:
for mod in a['attrs']:
self.mod_detections[post_id][id_n][mod] = a['attrs'][mod]
except KeyError:
self.mod_detections[post_id][id_n] = {}
