lc82111 / keras_hed Goto Github PK
View Code? Open in Web Editor NEWHolistically-Nested Edge Detection in Keras
Holistically-Nested Edge Detection in Keras
Hello, I tried your code with the HED dataset. When i run main_segmentation.py, It shows Epoch1/4096
and "while True:" for a long time. I think maybe there is somrthing wrong with the generate_minibatches().
Do you have the same problem?
Hi! Can you Provide pre trained weights for your Model? That would be a Great Advantage as Starting Point. Thanks.
I have trained the HED-BSDS
and , how can I test the dataset?
I can't find the code about testing.
thx
Hi,
thanks for your work.
have you tested the model accuracy ODS, OIS ?
and how many epoch does it need?
Regards
What is the necessary configuration needed?
Hi~ I have tested this well. I think this is very good example and I will try to enhance this model.
But, I have a question.
Why are the correction values of 103.939, 116.779, and 123.68 to BGR channels used in HED_data_parser.py file?
Why did you specify these values?
Hello~
I have trained and tested this HED model.
In conclusion, I have confirmed this model works fine and very good.
I saved the model as .h5 format using model.save('hed.h5').
Then, I have tried to load the saved model again using keras.models.load_model('hed.h5').
But the error occurred like:
ValueError: Unknown loss function:cross_entropy_balanced
How can I get over this?
(detailed error message)
Traceback (most recent call last):
File "", line 1, in
model0 = keras.models.load_model('hed.h5')
File "C:\Anaconda3\lib\site-packages\keras-2.3.0-py3.6.egg\keras\engine\saving.py", line 492, in load_wrapper
return load_function(*args, **kwargs)
File "C:\Anaconda3\lib\site-packages\keras-2.3.0-py3.6.egg\keras\engine\saving.py", line 584, in load_model
model = _deserialize_model(h5dict, custom_objects, compile)
File "C:\Anaconda3\lib\site-packages\keras-2.3.0-py3.6.egg\keras\engine\saving.py", line 369, in _deserialize_model
sample_weight_mode=sample_weight_mode)
File "C:\Anaconda3\lib\site-packages\keras-2.3.0-py3.6.egg\keras\engine\training.py", line 119, in compile
self.loss, self.output_names)
File "C:\Anaconda3\lib\site-packages\keras-2.3.0-py3.6.egg\keras\engine\training_utils.py", line 820, in prepare_loss_functions
loss_functions.append(get_loss_function(loss.get(name, None)))
File "C:\Anaconda3\lib\site-packages\keras-2.3.0-py3.6.egg\keras\engine\training_utils.py", line 705, in get_loss_function
loss_fn = losses.get(loss)
File "C:\Anaconda3\lib\site-packages\keras-2.3.0-py3.6.egg\keras\losses.py", line 795, in get
return deserialize(identifier)
File "C:\Anaconda3\lib\site-packages\keras-2.3.0-py3.6.egg\keras\losses.py", line 776, in deserialize
printable_module_name='loss function')
File "C:\Anaconda3\lib\site-packages\keras-2.3.0-py3.6.egg\keras\utils\generic_utils.py", line 167, in deserialize_keras_object
':' + function_name)
ValueError: Unknown loss function:cross_entropy_balanced
A declarative, efficient, and flexible JavaScript library for building user interfaces.
๐ Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. ๐๐๐
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google โค๏ธ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.