H-DenseUNet
TMI 2018. H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation from CT Volumes
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- H-DenseUNet.iml
- misc.xml
- modules.xml
- vcs.xml
- webServers.xml
- faq.md
- functional-api-guide.md
- sequential-model-guide.md
- about-keras-layers.md
- writing-your-own-keras-layers.md
- about-keras-models.md
- model.md
- sequential.md
- image.md
- sequence.md
- text.md
- activations.md
- applications.md
- backend.md
- callbacks.md
- constraints.md
- datasets.md
- index.md
- initializers.md
- losses.md
- metrics.md
- optimizers.md
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- scikit-learn-api.md
- visualization.md
- autogen.py
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- imdb_lstm.py
- lstm_benchmark.py
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- mnist_acgan.py
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- mnist_hierarchical_rnn.py
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- mnist_mlp.py
- mnist_net2net.py
- mnist_siamese_graph.py
- mnist_sklearn_wrapper.py
- mnist_swwae.py
- mnist_tfrecord.py
- mnist_transfer_cnn.py
- mymodel.h5
- neural_doodle.py
- neural_style_transfer.py
- pretrained_word_embeddings.py
- README.md
- reuters_mlp.py
- reuters_mlp_relu_vs_selu.py
- stateful_lstm.py
- variational_autoencoder.py
- variational_autoencoder_deconv.py
- __init__.cpython-35.pyc
- __init__.cpython-36.pyc
- __init__.cpython-37.pyc
- activations.cpython-36.pyc
- __init__.py
- __init__.pyc
- imagenet_utils.py
- imagenet_utils.pyc
- inception_v3.py
- inception_v3.pyc
- mobilenet.py
- mobilenet.pyc
- resnet50.py
- resnet50.pyc
- vgg16.py
- vgg16.pyc
- vgg19.py
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- xception.py
- xception.pyc
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- tensorflow_backend.cpython-35.pyc
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- __init__.py
- __init__.pyc
- cntk_backend.py
- common.py
- common.pyc
- tensorflow_backend.py
- tensorflow_backend.pyc
- theano_backend.py
- __init__.py
- __init__.pyc
- boston_housing.py
- boston_housing.pyc
- cifar.py
- cifar.pyc
- cifar10.py
- cifar10.pyc
- cifar100.py
- cifar100.pyc
- imdb.py
- imdb.pyc
- mnist.py
- mnist.pyc
- reuters.py
- reuters.pyc
- __init__.cpython-36.pyc
- topology.cpython-36.pyc
- __init__.py
- __init__.pyc
- topology.py
- topology.pyc
- training.py
- training.pyc
- __init__.py
- __init__.pyc
- advanced_activations.py
- advanced_activations.pyc
- convolutional.py
- convolutional.pyc
- convolutional_recurrent.py
- convolutional_recurrent.pyc
- core.py
- core.pyc
- embeddings.py
- embeddings.pyc
- local.py
- local.pyc
- merge.py
- merge.pyc
- noise.py
- noise.pyc
- normalization.py
- normalization.pyc
- pooling.py
- pooling.pyc
- recurrent.py
- recurrent.pyc
- wrappers.py
- wrappers.pyc
- __init__.py
- __init__.pyc
- interfaces.py
- interfaces.pyc
- layers.py
- layers.pyc
- models.py
- models.pyc
- __init__.py
- __init__.pyc
- image.py
- sequence.py
- sequence.pyc
- text.py
- __init__.cpython-35.pyc
- __init__.cpython-36.pyc
- __init__.cpython-37.pyc
- conv_utils.cpython-35.pyc
- conv_utils.cpython-36.pyc
- conv_utils.cpython-37.pyc
- data_utils.cpython-35.pyc
- data_utils.cpython-36.pyc
- data_utils.cpython-37.pyc
- generic_utils.cpython-35.pyc
- generic_utils.cpython-36.pyc
- generic_utils.cpython-37.pyc
- io_utils.cpython-35.pyc
- io_utils.cpython-36.pyc
- io_utils.cpython-37.pyc
- layer_utils.cpython-36.pyc
- np_utils.cpython-35.pyc
- np_utils.cpython-36.pyc
- np_utils.cpython-37.pyc
- vis_utils.cpython-36.pyc
- __init__.py
- __init__.pyc
- conv_utils.py
- conv_utils.pyc
- data_utils.py
- data_utils.pyc
- generic_utils.py
- generic_utils.pyc
- io_utils.py
- io_utils.pyc
- layer_utils.py
- layer_utils.pyc
- np_utils.py
- np_utils.pyc
- test_utils.py
- vis_utils.py
- vis_utils.pyc
- __init__.py
- __init__.pyc
- multi_gpu.py
- multi_gpu.pyc
- __init__.py
- __init__.pyc
- scikit_learn.py
- __init__.py
- __init__.pyc
- activations.py
- activations.pyc
- callbacks.py
- callbacks.pyc
- constraints.py
- constraints.pyc
- initializers.py
- initializers.pyc
- losses.py
- losses.pyc
- metrics.py
- metrics.pyc
- models.py
- models.pyc
- objectives.py
- optimizers.py
- optimizers.pyc
- regularizers.py
- regularizers.pyc
- dependency_links.txt
- PKG-INFO
- requires.txt
- SOURCES.txt
- top_level.txt
- test_image_data_tasks.py
- test_temporal_data_tasks.py
- test_vector_data_tasks.py
- applications_test.py
- imagenet_utils_test.py
- backend_test.py
- test_datasets.py
- test_topology.py
- test_training.py
- advanced_activations_test.py
- convolutional_recurrent_test.py
- convolutional_test.py
- core_test.py
- embeddings_test.py
- local_test.py
- merge_test.py
- noise_test.py
- normalization_test.py
- recurrent_test.py
- wrappers_test.py
- interface_test.py
- layers_test.py
- models_test.py
- image_test.py
- sequence_test.py
- text_test.py
- data_utils_test.py
- generic_utils_test.py
- io_utils_test.py
- layer_utils_test.py
- vis_utils_test.py
- scikit_learn_test.py
- activations_test.py
- constraints_test.py
- initializers_test.py
- losses_test.py
- metrics_test.py
- optimizers_test.py
- regularizers_test.py
- test_callbacks.py
- test_sequential_model.py
- test_documentation.py
- test_dynamic_trainability.py
- test_loss_masking.py
- test_loss_weighting.py
- test_model_saving.py
- test_multiprocessing.py
- __init__.cpython-36.pyc
- __init__.py
- __init__.pyc
- composer.py
- composer.pyc
- constructor.py
- constructor.pyc
- cyaml.py
- cyaml.pyc
- dumper.py
- dumper.pyc
- emitter.py
- emitter.pyc
- error.py
- error.pyc
- events.py
- events.pyc
- loader.py
- loader.pyc
- nodes.py
- nodes.pyc
- parser.py
- parser.pyc
- reader.py
- reader.pyc
- representer.py
- representer.pyc
- resolver.py
- resolver.pyc
- scanner.py
- scanner.pyc
- serializer.py
- serializer.pyc
- tokens.py
- tokens.pyc
- LICENSE
- MANIFEST.in
- PKG-INFO
- README.md
- setup.cfg
- setup.py
- misc.xml
- modules.xml
- mylib.iml
- workspace.xml
- __init__.py
- __init__.pyc
- custom_layers.py
- custom_layers.pyc
- funcs.py
- funcs.pyc
- .gitignore
- bash_train.sh
- densenet.py
- denseunet.py
- denseunet3d.py
- hybridnet.py
- loss.py
- preprocessing.py
- README.md
- requirements.txt
- test.py
- train_2ddense.py
- train_hybrid.py
# Installation Guide
1. Get the code
git clone https://github.com/xmengli/H-DenseUNet
Downloads the entire project code from GitHub to your computer.
cd H-DenseUNet
Moves into the project folder you just downloaded.
2. Python
Easy RecommendedPrerequisites
pip install -r requirements.txt
Installs the Python libraries listed in requirements.txt (or similar).
python <μ€νν νμΌλͺ
>.py # READMEμμ μ νν μ€ν νμΌλͺ
μ νμΈνμΈμ
Runs the Python script (or module).
If it runs without errors and prints output in the terminal, it worked.
// repository documentation
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