TimoSaemann / ENet

ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
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slow using GTX 980M #35

Open jjzhu opened 6 years ago

jjzhu commented 6 years ago

I am running the script from the instruction:

python test_segmentation.py --model ../prototxts/enet_deploy_final.prototxt --weights ../enet_weights_zoo/cityscapes_weights.caffemodel --colours ../scripts/cityscapes19.png --input_image ../example_image/munich_000000_000019_leftImg8bit.png --out_dir ../example_image/

by only timing the forward function

t1 = time.time()
out = net.forward_all(**{net.inputs[0]: input_image})
t2 = time.time()
print 'forward time:', (t2-t1) * 1000

forward time: 1605.10015488

am I doing sth. wrong? my GTX 980M should be as good as 30% of a titanic X. So I am expecting at least close to realtime performance?

Thank you