Comments (3)
I don't think there is any erros in your code. And since I update the evaluation code, all the miou of my experiment drops a little. And I just test my model using my new evaluation code, the final miou is also about 48%. So I just think there is a little error in my old evaluation code. Sorry to confuse you.
And for improving the the performance, I think the poly learning policy and using tag to clean all the probability of not-existing labels may do help. I just plan to do some more experiment to check my thought in a few days.
from sec-tensorflow.
One more thing, if you use fixed input_size for testing, you may get a better score.
from sec-tensorflow.
Thank you. I will also do some try. Waiting for your good news.
from sec-tensorflow.
Related Issues (11)
- Have you tried to generate the localization cues by yourself HOT 6
- Error while loading localisation_cues.pickle HOT 7
- Trained Model, Please HOT 5
- Tensorflow version HOT 3
- Segmentation fault with pydensecrf HOT 9
- Test Code HOT 1
- Segmentation fault (core dumped) on self.sess.run(self.net["accum_gradient_accum"], feed_dict=params) HOT 1
- How to produce my own localization_cues.pickle? HOT 1
- "model_path":"./20180622-3-4/final-0", HOT 3
- the Training Net work and the Test Network HOT 2
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from sec-tensorflow.