def text(imgs):
#On charge le modèle VGG
encode = ei.model_gen()
#on charge le modèle RNN
sd = SceneDesc.scenedesc()
model = sd.create_model(ret_model=True)
#On charge les poids qui vont avec
weight = 'RNN_Train_weights/Weights.h5'
model.load_weights(weight)
#Où se situent nos images
path = "Data/Images/"
if isinstance(imgs, list): #si nous avons une liste d'imagess
encoded_images = [(img, ei.encodings(encode, path + img))
for img in imgs]
image_captions = [(img,
tm.generate_captions(sd,
model,
encoding,
beam_size=3))
for img, encoding in encoded_images]
else: #Si nous avons une image unique
image_path = path + imgs
encoded_image = ei.encodings(encode, image_path)
image_captions = (imgs,
tm.generate_captions(sd,
model,
encoded_image,
beam_size=3))
print(image_captions)
def test_generate_captions():
'''
Wherein we test test_mod.generate_captions. Since you may
use pre-computed weights from any source only print the
generated sentence to stdout and check that it is nonempty
'''
encoded_img=ei.encodings(ei.model_gen(),test_img)
caption=generate_captions(sd,model,encoded_img,beam_size=3)
def report():
print('The model generated the caption: '+caption)
atexit.register(report)
assert(len(caption)>0)
def text(img): t1= time.time() encode = ei.model_gen() weight = 'Output/Weights.h5' sd = SceneDesc.scenedesc() model = sd.create_model(ret_model = True) model.load_weights(weight) image_path = img encoded_images = ei.encodings(encode, image_path) image_captions = tm.generate_captions(sd, model, encoded_images, beam_size=3) engine = pyttsx.init() print (image_captions) engine.say( str(image_captions)) engine.runAndWait()
def text(img):
t1 = time.time()
encode = ei.model_gen()
weight = 'Output/Weights.h5'
sd = SceneDesc.scenedesc()
model = sd.create_model(ret_model=True)
model.load_weights(weight)
image_path = img
encoded_images = ei.encodings(encode, image_path)
image_captions = tm.generate_captions(sd,
model,
encoded_images,
beam_size=3)
engine = pyttsx.init()
print '\nCaption Generated for the above Image is=\n', image_captions