else:
im_file = fuse_radio_ir_4_pred(args.radio_fits,
args.ir_png,
model=args.model)
vis_file = args.ir_png
#print("im_file", im_file)
if (im_file is None):
print("Error in generating contours")
sys.exit(1)
hard_code_cfg()
net = get_network('rgz_test')
iter_num = 80000
if ('D3' == args.model):
iter_num = 60000
model_weight = osp.join(
get_rgz_root(), 'data/pretrained_model/rgz/%s/VGGnet_fast_rcnn-%d' %
(args.model, iter_num))
if (not osp.exists(model_weight + '.index')):
print(
"Fail to load rgz model, have you done \'python download_data.py\' already?"
)
sys.exit(1)
saver = tf.train.Saver()
sess = tf.Session(config=tf.ConfigProto(allow_soft_placement=True))
sys.stdout.write('Loading RGZ model from {:s}... '.format(model_weight))
sys.stdout.flush()
stt = time.time()
saver.restore(sess, model_weight)
print(("Done in %.3f seconds" % (time.time() - stt)))
sys.stdout.write("Detecting radio sources... ")
if ('D1' == args.model):
im_file = args.radio_png
vis_file = args.radio_png
else:
im_file = fuse_radio_ir_4_pred(args.radio_fits, args.ir_png, model=args.model)
vis_file = args.ir_png
#print("im_file", im_file)
if (im_file is None):
print("Error in generating contours")
sys.exit(1)
hard_code_cfg()
net = get_network('rgz_test')
iter_num = 80000
if ('D3' == args.model):
iter_num = 60000
model_weight = osp.join(get_rgz_root(), 'data/pretrained_model/rgz/%s/VGGnet_fast_rcnn-%d' % (args.model, iter_num))
if (not osp.exists(model_weight + '.index')):
print("Fail to load rgz model, have you done \'python download_data.py\' already?")
sys.exit(1)
saver = tf.train.Saver()
sess = tf.Session(config=tf.ConfigProto(allow_soft_placement=True))
sys.stdout.write('Loading RGZ model from {:s}... '.format(model_weight))
sys.stdout.flush()
stt = time.time()
saver.restore(sess, model_weight)
print("Done in %.3f seconds" % (time.time() - stt))
sys.stdout.write("Detecting radio sources... ")
sys.stdout.flush()
ret = demo(sess, net, im_file, vis_file, args.radio_fits, conf_thresh=args.conf_thresh,
eval_class=(not args.eval_eoi))