help="1=Yes|0=No",
choices=[1, 0])
parser.add_argument("--image_path",
type=str,
help="Path to the Image for Generation of Captions")
parser.add_argument("--validation_data",
type=str,
help="Path to the Validation Data for evaluation")
args = parser.parse_args()
config = Configuration(vars(args))
if config.mode == "train":
caption_file = 'Data/training.txt'
feature_file = 'Data/training_features.npy'
vocab, wtoidx, training_data = generate_captions(config.word_threshold,
config.max_len,
caption_file,
feature_file)
features, captions = training_data[:, 0], training_data[:, 1]
features = np.array([feat.astype(float) for feat in features])
data = (vocab.tolist(), wtoidx.tolist(), features, captions)
model = Caption_Generator(config, data=data)
loss, inp_dict = model.build_train_graph()
model.train(loss, inp_dict)
elif config.mode == "test":
if os.path.exists(args.image_path):
model = Caption_Generator(config)
model.decode(args.image_path)
else:
print "Please provide a valid image path.\n Usage:\n python main.py --mode test --image_path VALID_PATH"
help="If mode is test then, Path to the Image for Generation of Captions")
parser.add_argument(
"--load_image",
help=
"If mode is test then, displays and stores image with generated caption",
action="store_true")
parser.add_argument(
"--validation_data",
type=str,
help="If mode is eval then, Path to the Validation Data for evaluation")
args = parser.parse_args()
config = Configuration(vars(args))
if config.mode == "train":
vocab, wtoidx, training_data = generate_captions(
config.word_threshold, config.max_len, args.coco_caption_path,
args.flickr_caption_path, args.feature_path, config.data_is_coco)
features, captions = training_data[:, 0], training_data[:, 1]
features = np.array([feat.astype(float) for feat in features])
data = (vocab.tolist(), wtoidx.tolist(), features, captions)
model = Caption_Generator(config, data=data)
loss, inp_dict = model.build_train_graph()
model.train(loss, inp_dict)
elif config.mode == "test":
if os.path.exists(args.image_path):
model = Caption_Generator(config)
model.decode(args.image_path)
else:
print "Please provide a valid image path.\n Usage:\n python main.py --mode test --image_path VALID_PATH"