diff --git a/recognition/.DS_Store b/recognition/.DS_Store
index ae199051c1..f0314aa5f2 100644
Binary files a/recognition/.DS_Store and b/recognition/.DS_Store differ
diff --git a/recognition/45375325_VQVAE_for_image_creation/.gitignore b/recognition/45375325_VQVAE_for_image_creation/.gitignore
new file mode 100644
index 0000000000..7680612ff0
--- /dev/null
+++ b/recognition/45375325_VQVAE_for_image_creation/.gitignore
@@ -0,0 +1,147 @@
+### Python template
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+# Usually these files are written by a python script from a template
+# before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+# For a library or package, you might want to ignore these files since the code is
+# intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+# However, in case of collaboration, if having platform-specific dependencies or dependencies
+# having no cross-platform support, pipenv may install dependencies that don't work, or not
+# install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# data
+/data
+/data.zip
+
+# mac things
+/.DS_Store
+
diff --git a/recognition/45375325_VQVAE_for_image_creation/.idea/.gitignore b/recognition/45375325_VQVAE_for_image_creation/.idea/.gitignore
new file mode 100644
index 0000000000..13566b81b0
--- /dev/null
+++ b/recognition/45375325_VQVAE_for_image_creation/.idea/.gitignore
@@ -0,0 +1,8 @@
+# Default ignored files
+/shelf/
+/workspace.xml
+# Editor-based HTTP Client requests
+/httpRequests/
+# Datasource local storage ignored files
+/dataSources/
+/dataSources.local.xml
diff --git a/recognition/45375325_VQVAE_for_image_creation/.idea/45375325_VQVAE_for_image_creation.iml b/recognition/45375325_VQVAE_for_image_creation/.idea/45375325_VQVAE_for_image_creation.iml
new file mode 100644
index 0000000000..32cb803dbc
--- /dev/null
+++ b/recognition/45375325_VQVAE_for_image_creation/.idea/45375325_VQVAE_for_image_creation.iml
@@ -0,0 +1,11 @@
+
+
+
+
+
+
+
+
+
+
+
\ No newline at end of file
diff --git a/recognition/45375325_VQVAE_for_image_creation/.idea/codeStyles/codeStyleConfig.xml b/recognition/45375325_VQVAE_for_image_creation/.idea/codeStyles/codeStyleConfig.xml
new file mode 100644
index 0000000000..a55e7a179b
--- /dev/null
+++ b/recognition/45375325_VQVAE_for_image_creation/.idea/codeStyles/codeStyleConfig.xml
@@ -0,0 +1,5 @@
+
+
+
+
+
\ No newline at end of file
diff --git a/recognition/45375325_VQVAE_for_image_creation/.idea/inspectionProfiles/Project_Default.xml b/recognition/45375325_VQVAE_for_image_creation/.idea/inspectionProfiles/Project_Default.xml
new file mode 100644
index 0000000000..2ace6d0c3e
--- /dev/null
+++ b/recognition/45375325_VQVAE_for_image_creation/.idea/inspectionProfiles/Project_Default.xml
@@ -0,0 +1,6 @@
+
+
+
+
+
+
\ No newline at end of file
diff --git a/recognition/45375325_VQVAE_for_image_creation/.idea/inspectionProfiles/profiles_settings.xml b/recognition/45375325_VQVAE_for_image_creation/.idea/inspectionProfiles/profiles_settings.xml
new file mode 100644
index 0000000000..105ce2da2d
--- /dev/null
+++ b/recognition/45375325_VQVAE_for_image_creation/.idea/inspectionProfiles/profiles_settings.xml
@@ -0,0 +1,6 @@
+
+
+
+
+
+
\ No newline at end of file
diff --git a/recognition/45375325_VQVAE_for_image_creation/.idea/misc.xml b/recognition/45375325_VQVAE_for_image_creation/.idea/misc.xml
new file mode 100644
index 0000000000..9dcb1bfdcf
--- /dev/null
+++ b/recognition/45375325_VQVAE_for_image_creation/.idea/misc.xml
@@ -0,0 +1,4 @@
+
+
+
+
\ No newline at end of file
diff --git a/recognition/45375325_VQVAE_for_image_creation/.idea/modules.xml b/recognition/45375325_VQVAE_for_image_creation/.idea/modules.xml
new file mode 100644
index 0000000000..3e8096629f
--- /dev/null
+++ b/recognition/45375325_VQVAE_for_image_creation/.idea/modules.xml
@@ -0,0 +1,8 @@
+
+
+
+
+
+
+
+
\ No newline at end of file
diff --git a/recognition/45375325_VQVAE_for_image_creation/.idea/other.xml b/recognition/45375325_VQVAE_for_image_creation/.idea/other.xml
new file mode 100644
index 0000000000..640fd80b82
--- /dev/null
+++ b/recognition/45375325_VQVAE_for_image_creation/.idea/other.xml
@@ -0,0 +1,7 @@
+
+
+
+
+
+
+
\ No newline at end of file
diff --git a/recognition/45375325_VQVAE_for_image_creation/.idea/vcs.xml b/recognition/45375325_VQVAE_for_image_creation/.idea/vcs.xml
new file mode 100644
index 0000000000..b2bdec2d71
--- /dev/null
+++ b/recognition/45375325_VQVAE_for_image_creation/.idea/vcs.xml
@@ -0,0 +1,6 @@
+
+
+
+
+
+
\ No newline at end of file
diff --git a/recognition/45375325_VQVAE_for_image_creation/README.MD b/recognition/45375325_VQVAE_for_image_creation/README.MD
new file mode 100644
index 0000000000..3d664f6569
--- /dev/null
+++ b/recognition/45375325_VQVAE_for_image_creation/README.MD
@@ -0,0 +1,116 @@
+# VQ-VAE for creation of images using the OASIS Brain Dataset
+
+***
+
+This is our implementation of the vector quantised variable auto encoder as depicted in the paper by members of DeepMind (1).
+
+We used [this implementation](https://github.com/MishaLaskin/vqvae) by [MishaLaskin](https://github.com/MishaLaskin/) as inspiration to gain an understanding of how the code works.
+
+***
+
+## Usage
+
+***
+
+### Dependencies
+
+- torch == 1.13.0.dev20220901
+- torchvision == 0.14.0.dev20220901
+- matplotlib == 3.6.0
+- pillow == 9.2.0
+- numpy == 1.23.3
+- tqdm == 4.64.1
+- scikit-learn == 1.1.2
+
+Can also create a conda environment from the provided environment.yml with command (WARNING: This environment is one that I use for general work and as such is bloated with libraries not necassary for this module)
+
+```console
+conda env create -f environment.yml
+```
+
+or you can update the environment file with
+
+```console
+conda env export > environment.yml
+```
+
+Main difference for this environment is that this script was created using the nightly version of pytorch so that I could make use of the Apple Silicon gpu and mps acceleration. If you wanted to use the normal version of pytorch prior to them making mps acceleration available then for every definition of `DEVICE` delete the `'mps' if torch.has_mps else`. This should allow for the code to function normally on a cuda gpu.
+
+### Reproducibility
+
+To use this model for other datasets, place your data inside the data folder following pytorch documentation for producing a dataset using [ImageFolder](https://pytorch.org/vision/stable/generated/torchvision.datasets.ImageFolder.html#torchvision.datasets.ImageFolder).
+
+If you want to make use of the current model seen in this readme skip the training and saving cells and simply load the model. After that run all the cells in order to see results. If you wish to maintain the saved model and save a new one for your other datasets then adjust the name that the model is saved under and run the save model cell.
+
+***
+
+## Training
+
+***
+
+### VQ-VAE
+
+The Vector Quantized - Variational Autoencoder (VQVAE) is a network that makes use of the concept of an autoencoder. A model composed of two separate models, an encoder and a decoder. The encoder takes in an image and compresses the information down to a smaller vector known as the latent space. The decoder then takes the information from the latent space and generates the original image again. This comes with some information loss but that is often negligible when both the encoder and decoder have been trained properly.
+
+The vector quantisation component is the ability to then take this latent space and turn what were all continuous values into discrete values creating a codebook in place of the latent space and training the decoder on this instead. This has been found to produce clearer images, reducing the information loss.
+
+
+
+Above describes the encoding process to a latent space as well as the quantisation step and then the decoding process.
+
+The quantisation step makes use of L2 norm with the full equation defined below where $|| ... ||_2$ is defined as L2 norm
+
+
+
+This gives us a quantized representation of all the features of an image. This idea has been extended to 3d/environments, as well as sounds in (1)
+
+The Models used for encoder and decoder as well as all other models can be found in the `modules` directory
+
+#### Pixel CNN
+
+Once an embedding space or codebook has been trained, we use a Pixel CNN to generate a codebook these generated codebooks are then parsed to the decoder to generate unique images. Typically the better trained the Pixel CNN the more unique items within the image are created.
+
+The Pixel CNN model is defined as
+
+
+
+This involves 15 layers of the MaskedGatedConv2d
+
+Please find the implementations in the modules module:
+
+- `modules.decoder.py`
+- `modules.encoder.py`
+- `modules.quantizer.py`
+- `modules.stack.py`
+- `modules.vqvae.py`
+- `modules.pixelcnn.py`
+
+***
+
+## Results (using OASIS brain dataset)
+
+### VQ-VAE - results
+
+The VQVAE was trained for 2 epochs and produced quite similar images, as can be seen below
+
+
+
+There is some loss of quality and finer details visible in the reconstruction but the overall idea of the image remains.
+
+### Pixel CNN - results
+
+Unfortunately we were unable to get the pixel cnn working in time and as such don't have any results to show. You can however see the progress made as well as the errors found.
+
+***
+
+## Future improvements
+
+Obviously it would be great if there were a working pixel cnn for generating new images to truly test the VQ-VAE and see its limitations.
+
+The VQ-VAE could possible by trained for longer to see an increase in quality of reconstructions possibly giving the higher details.
+
+There are certainly further optimisations possible throughout this project including supplying a less bloated environment file to work with.
+
+## Sources
+
+[1] van den Oord, A., Vinyals, O., & Kavukcuoglu, K. (2017). Neural Discrete Representation Learning. CoRR, abs/1711.00937. Opgehaal van
diff --git a/recognition/45375325_VQVAE_for_image_creation/dataset.py b/recognition/45375325_VQVAE_for_image_creation/dataset.py
new file mode 100644
index 0000000000..ecb6e13c29
--- /dev/null
+++ b/recognition/45375325_VQVAE_for_image_creation/dataset.py
@@ -0,0 +1,60 @@
+import torch
+import torchvision.transforms as tf
+import numpy as np
+import os
+from torch.utils.data import Dataset, DataLoader
+from torchvision import datasets
+from PIL import Image
+
+# defining constants
+root = os.getcwd() + "/data/"
+TRAIN_PATH = root + "train/"
+TEST_PATH = root + "test/"
+VALIDATE_PATH = root + "validate/"
+batch_size = 32
+DEVICE = "mps" if torch.has_mps else "cuda" if torch.cuda.is_available() else "cpu"
+TRANSFORM = tf.Compose([
+ tf.ToTensor()
+])
+
+
+# define dataset
+class PixelCNNData(Dataset):
+ def __init__(self, model, transforms, train):
+ if train:
+ self.PATH = TRAIN_PATH + 'images/'
+ else:
+ self.PATH = TEST_PATH + 'images/'
+ self.model = model
+ self.images = os.listdir(self.PATH)
+ self.tfs = transforms
+
+ def __len__(self):
+ return len(self.images)
+
+ def __getitem__(self, x):
+ # print(len(self.images))
+ img_path = self.PATH + self.images[x]
+ image = Image.open(img_path).convert('RGB')
+ image = self.tfs(image)
+ image = image.unsqueeze(dim=0)
+ image = image.to(DEVICE)
+ encoded_output = self.model.encoder(image)
+ z = self.model.pre_quantization_conv(encoded_output)
+ _,_,_,z = self.model.vector_quantizer(z)
+ z = z.float().to(DEVICE)
+ z = z.view(64,64)
+ z = torch.stack((z,z,z),0) # GAN uses 3 channel inputs
+ return z,z
+
+# create datasets and dataloaders
+train_set = datasets.ImageFolder(root=root, transform=TRANSFORM)
+test_set = datasets.ImageFolder(root=root, transform=TRANSFORM)
+validate_set = datasets.ImageFolder(root=root, transform=TRANSFORM)
+
+train_dl = DataLoader(train_set, batch_size=batch_size)
+test_dl = DataLoader(test_set, batch_size=batch_size)
+validate_dl = DataLoader(validate_set, batch_size=batch_size)
+
+
+
diff --git a/recognition/45375325_VQVAE_for_image_creation/environment.yml b/recognition/45375325_VQVAE_for_image_creation/environment.yml
new file mode 100644
index 0000000000..38d28e0dfa
--- /dev/null
+++ b/recognition/45375325_VQVAE_for_image_creation/environment.yml
@@ -0,0 +1,294 @@
+name: comp3710
+channels:
+ - pytorch-nightly
+ - conda-forge
+dependencies:
+ - abseil-cpp=20210324.2=hbdafb3b_0
+ - absl-py=1.2.0=pyhd8ed1ab_0
+ - aiohttp=3.8.3=py39h02fc5c5_0
+ - aiosignal=1.2.0=pyhd8ed1ab_0
+ - aom=3.4.0=hbe31e94_1
+ - appnope=0.1.3=pyhd8ed1ab_0
+ - argon2-cffi=21.3.0=pyhd8ed1ab_0
+ - argon2-cffi-bindings=21.2.0=py39hb18efdd_2
+ - asttokens=2.0.8=pyhd8ed1ab_0
+ - astunparse=1.6.3=pyhd8ed1ab_0
+ - async-timeout=4.0.2=pyhd8ed1ab_0
+ - attrs=22.1.0=pyh71513ae_1
+ - backcall=0.2.0=pyh9f0ad1d_0
+ - backports=1.0=py_2
+ - backports.functools_lru_cache=1.6.4=pyhd8ed1ab_0
+ - beautifulsoup4=4.11.1=pyha770c72_0
+ - bleach=5.0.1=pyhd8ed1ab_0
+ - blinker=1.5=pyhd8ed1ab_0
+ - blosc=1.21.1=hd414afc_3
+ - brotli=1.0.9=h1c322ee_7
+ - brotli-bin=1.0.9=h1c322ee_7
+ - brotlipy=0.7.0=py39hb18efdd_1004
+ - brunsli=0.1=h9f76cd9_0
+ - bzip2=1.0.8=h3422bc3_4
+ - c-ares=1.18.1=h3422bc3_0
+ - c-blosc2=2.4.2=h303ed30_0
+ - ca-certificates=2022.9.24=h4653dfc_0
+ - cached-property=1.5.2=hd8ed1ab_1
+ - cached_property=1.5.2=pyha770c72_1
+ - cachetools=5.2.0=pyhd8ed1ab_0
+ - certifi=2022.9.24=pyhd8ed1ab_0
+ - cffi=1.15.1=py39h04d3946_0
+ - cfitsio=4.1.0=hd4f5c17_0
+ - charls=2.3.4=hbdafb3b_0
+ - charset-normalizer=2.1.1=pyhd8ed1ab_0
+ - click=8.1.3=py39h2804cbe_0
+ - cloudpickle=2.2.0=pyhd8ed1ab_0
+ - contourpy=1.0.5=py39haaf3ac1_0
+ - cryptography=38.0.1=py39haa0b8cc_0
+ - cycler=0.11.0=pyhd8ed1ab_0
+ - cytoolz=0.12.0=py39h9eb174b_0
+ - dask-core=2022.10.0=pyhd8ed1ab_1
+ - dav1d=1.0.0=he4db4b2_1
+ - debugpy=1.6.3=py39h3c22d25_0
+ - decorator=5.1.1=pyhd8ed1ab_0
+ - defusedxml=0.7.1=pyhd8ed1ab_0
+ - entrypoints=0.4=pyhd8ed1ab_0
+ - executing=1.1.1=pyhd8ed1ab_0
+ - expat=2.4.9=hb7217d7_0
+ - ffmpeg=5.1.1=gpl_hfdc7bce_101
+ - flit-core=3.7.1=pyhd8ed1ab_0
+ - font-ttf-dejavu-sans-mono=2.37=hab24e00_0
+ - font-ttf-inconsolata=3.000=h77eed37_0
+ - font-ttf-source-code-pro=2.038=h77eed37_0
+ - font-ttf-ubuntu=0.83=hab24e00_0
+ - fontconfig=2.14.0=h82840c6_1
+ - fonts-conda-ecosystem=1=0
+ - fonts-conda-forge=1=0
+ - fonttools=4.37.4=py39h02fc5c5_0
+ - freetype=2.12.1=hd633e50_0
+ - frozenlist=1.3.1=py39h4eb3d34_0
+ - fsspec=2022.10.0=pyhd8ed1ab_0
+ - gast=0.5.3=pyhd8ed1ab_0
+ - gettext=0.19.8.1=h0186832_1009
+ - giflib=5.2.1=h27ca646_2
+ - gmp=6.2.1=h9f76cd9_0
+ - gnutls=3.7.8=h9f1a10d_0
+ - google-auth=2.12.0=pyh1a96a4e_0
+ - google-auth-oauthlib=0.4.6=pyhd8ed1ab_0
+ - google-pasta=0.2.0=pyh8c360ce_0
+ - grpc-cpp=1.45.2=h5b4c0ed_5
+ - grpcio=1.45.0=py39hcf421d0_0
+ - h5py=3.7.0=nompi_py39h6b51346_101
+ - hdf5=1.12.2=nompi_h8968d4b_100
+ - icu=70.1=h6b3803e_0
+ - idna=3.4=pyhd8ed1ab_0
+ - imagecodecs=2022.9.26=py39h6bc43d6_0
+ - imageio=2.22.0=pyhfa7a67d_0
+ - importlib-metadata=4.11.4=py39h2804cbe_0
+ - importlib_resources=5.10.0=pyhd8ed1ab_0
+ - ipykernel=6.16.0=pyh736e0ef_0
+ - ipython=8.5.0=pyhd1c38e8_1
+ - ipython_genutils=0.2.0=py_1
+ - jedi=0.18.1=pyhd8ed1ab_2
+ - jinja2=3.1.2=pyhd8ed1ab_1
+ - jpeg=9e=he4db4b2_2
+ - jsonschema=4.16.0=pyhd8ed1ab_0
+ - jupyter_client=7.3.5=pyhd8ed1ab_0
+ - jupyter_core=4.11.1=py39h2804cbe_0
+ - jupyterlab_pygments=0.2.2=pyhd8ed1ab_0
+ - jxrlib=1.1=h27ca646_2
+ - keras=2.8.0=pyhd8ed1ab_0
+ - keras-preprocessing=1.1.2=pyhd8ed1ab_0
+ - kiwisolver=1.4.4=py39hab5e169_0
+ - krb5=1.19.3=hf9b2bbe_0
+ - lame=3.100=h1a8c8d9_1003
+ - lcms2=2.12=had6a04f_0
+ - lerc=4.0.0=h9a09cb3_0
+ - libaec=1.0.6=hbdafb3b_0
+ - libavif=0.10.1=he4db4b2_1
+ - libblas=3.9.0=16_osxarm64_openblas
+ - libbrotlicommon=1.0.9=h1c322ee_7
+ - libbrotlidec=1.0.9=h1c322ee_7
+ - libbrotlienc=1.0.9=h1c322ee_7
+ - libcblas=3.9.0=16_osxarm64_openblas
+ - libcurl=7.85.0=hd538317_0
+ - libcxx=14.0.6=h04bba0f_0
+ - libdeflate=1.14=h1a8c8d9_0
+ - libedit=3.1.20191231=hc8eb9b7_2
+ - libev=4.33=h642e427_1
+ - libffi=3.4.2=h3422bc3_5
+ - libgfortran=5.0.0=11_3_0_hd922786_25
+ - libgfortran5=11.3.0=hdaf2cc0_25
+ - libiconv=1.17=he4db4b2_0
+ - libidn2=2.3.3=he4db4b2_0
+ - liblapack=3.9.0=16_osxarm64_openblas
+ - libnghttp2=1.47.0=h232270b_1
+ - libopenblas=0.3.21=openmp_hc731615_3
+ - libpng=1.6.38=h76d750c_0
+ - libprotobuf=3.20.1=hb5ab8b9_4
+ - libsodium=1.0.18=h27ca646_1
+ - libsqlite=3.39.4=h76d750c_0
+ - libssh2=1.10.0=hb80f160_3
+ - libtasn1=4.19.0=h1a8c8d9_0
+ - libtiff=4.4.0=hfa0b094_4
+ - libunistring=0.9.10=h3422bc3_0
+ - libvpx=1.11.0=hc470f4d_3
+ - libwebp=1.2.4=h328b37c_0
+ - libwebp-base=1.2.4=h57fd34a_0
+ - libxcb=1.13=h9b22ae9_1004
+ - libxml2=2.10.2=ha9542bf_1
+ - libzlib=1.2.12=h03a7124_4
+ - libzopfli=1.0.3=h9f76cd9_0
+ - llvm-openmp=14.0.4=hd125106_0
+ - locket=1.0.0=pyhd8ed1ab_0
+ - lz4-c=1.9.3=hbdafb3b_1
+ - markdown=3.4.1=pyhd8ed1ab_0
+ - markupsafe=2.1.1=py39hb18efdd_1
+ - matplotlib=3.6.0=py39hdf13c20_0
+ - matplotlib-base=3.6.0=py39h35e9e80_0
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+ - mistune=0.8.4=py39h5161555_1005
+ - multidict=6.0.2=py39hb18efdd_1
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+ - ncurses=6.3=h07bb92c_1
+ - nest-asyncio=1.5.6=pyhd8ed1ab_0
+ - nettle=3.8.1=h63371fa_1
+ - ninja=1.11.0=hf86a087_0
+ - notebook=6.4.12=pyha770c72_0
+ - numpy=1.23.3=py39hcb4b507_0
+ - oauthlib=3.2.1=pyhd8ed1ab_0
+ - openh264=2.3.0=h9a09cb3_0
+ - openjpeg=2.5.0=h5d4e404_1
+ - openssl=1.1.1q=ha287fd2_0
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+ - p11-kit=0.24.1=h29577a5_0
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+ - python_abi=3.9=2_cp39
+ - pytorch=1.13.0.dev20220901=py3.9_0
+ - pyu2f=0.1.5=pyhd8ed1ab_0
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+ - setuptools=65.4.1=pyhd8ed1ab_0
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+ - sqlite=3.39.4=h2229b38_0
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+ - svt-av1=1.2.1=he23bcac_0
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+ - tensorboard-data-server=0.6.0=py39hbe5e4b8_2
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+ - torchvision=0.14.0.dev20220901=py39_cpu
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+ - werkzeug=2.2.2=pyhd8ed1ab_0
+ - wheel=0.37.1=pyhd8ed1ab_0
+ - wrapt=1.14.1=py39h9eb174b_0
+ - x264=1!164.3095=h57fd34a_2
+ - x265=3.5=hbc6ce65_3
+ - xorg-libxau=1.0.9=h27ca646_0
+ - xorg-libxdmcp=1.1.3=h27ca646_0
+ - xz=5.2.6=h57fd34a_0
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+ - yarl=1.7.2=py39hb18efdd_2
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+ - zlib-ng=2.0.6=he4db4b2_0
+ - zstd=1.5.2=h8128057_4
+ - pip:
+ - appdirs==1.4.4
+ - dill==0.3.5.1
+ - etils==0.7.1
+ - googleapis-common-protos==1.56.4
+ - htmlmin==0.1.12
+ - imagehash==4.3.0
+ - ipywidgets==8.0.2
+ - joblib==1.1.0
+ - jupyterlab-widgets==3.0.3
+ - jupyterthemes==0.20.0
+ - lesscpy==0.15.0
+ - missingno==0.5.1
+ - multimethod==1.8
+ - networkx==2.8.6
+ - opencv-python==4.6.0.66
+ - pandas==1.4.4
+ - pandas-profiling==3.3.0
+ - patsy==0.5.2
+ - phik==0.12.2
+ - ply==3.11
+ - promise==2.3
+ - pydantic==1.9.2
+ - pyee==8.2.2
+ - pyppeteer==1.0.2
+ - pytz==2022.2.1
+ - scikit-learn==1.1.2
+ - seaborn==0.11.2
+ - sklearn==0.0
+ - statsmodels==0.13.2
+ - tangled-up-in-unicode==0.2.0
+ - tensorflow-datasets==4.6.0
+ - tensorflow-metadata==1.10.0
+ - threadpoolctl==3.1.0
+ - toml==0.10.2
+ - tqdm==4.64.1
+ - visions==0.7.5
+ - websockets==10.3
+ - widgetsnbextension==4.0.3
+prefix: /opt/homebrew/Caskroom/mambaforge/base/envs/comp3710
diff --git a/recognition/45375325_VQVAE_for_image_creation/images/.DS_Store b/recognition/45375325_VQVAE_for_image_creation/images/.DS_Store
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diff --git a/recognition/45375325_VQVAE_for_image_creation/interface.ipynb b/recognition/45375325_VQVAE_for_image_creation/interface.ipynb
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+++ b/recognition/45375325_VQVAE_for_image_creation/interface.ipynb
@@ -0,0 +1,697 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 23,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from train import train_vqvae, DEVICE, train_pixel_cnn, test_pixel_cnn\n",
+ "from predict import generate_samples\n",
+ "from modules.vqvae import VQVAE\n",
+ "from modules.pixelcnn import PixelCNN\n",
+ "from dataset import train_dl, test_dl, batch_size, test_set, PixelCNNData\n",
+ "from torch.utils.data import DataLoader\n",
+ "import torch\n",
+ "import torchvision\n",
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "import tqdm\n",
+ "\n",
+ "def show(img):\n",
+ " \"\"\"\n",
+ " Plotting func\n",
+ " \"\"\"\n",
+ " np_img = img.numpy()\n",
+ " fig = plt.imshow(np.transpose(np_img, (1, 2, 0)), interpolation='nearest')\n",
+ " fig.axes.get_xaxis().set_visible(False)\n",
+ " fig.axes.get_yaxis().set_visible(False)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 24,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "model = VQVAE(latent_dim=128, res_h_dim=32, num_embeddings=512, embedding_dim=64, beta=0.25)\n",
+ "model.to(DEVICE)\n",
+ "EPOCHS = 2\n",
+ "\n",
+ "optim = torch.optim.Adam(model.parameters(), lr=1e-3)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 23,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "=======================EPOCH = 1======================\n",
+ "batch 0/354 \t |current loss: 0.807003\n",
+ "batch 25/354 \t |current loss: 0.532948\n",
+ "batch 50/354 \t |current loss: 0.308322\n",
+ "batch 75/354 \t |current loss: 0.336627\n",
+ "batch 100/354 \t |current loss: 0.248623\n",
+ "batch 125/354 \t |current loss: 0.203222\n",
+ "batch 150/354 \t |current loss: 0.121747\n",
+ "batch 175/354 \t |current loss: 0.166472\n",
+ "batch 200/354 \t |current loss: 0.176555\n",
+ "batch 225/354 \t |current loss: 0.138061\n",
+ "batch 250/354 \t |current loss: 0.189433\n",
+ "batch 275/354 \t |current loss: 0.237457\n",
+ "batch 300/354 \t |current loss: 0.125128\n",
+ "batch 325/354 \t |current loss: 0.108246\n",
+ "batch 350/354 \t |current loss: 0.150739\n",
+ "Reconstruction loss: 0.23556041077705425\n",
+ "=======================EPOCH = 2======================\n",
+ "batch 0/354 \t |current loss: 0.103885\n",
+ "batch 25/354 \t |current loss: 12.274344\n",
+ "batch 50/354 \t |current loss: 0.583294\n",
+ "batch 75/354 \t |current loss: 0.172976\n",
+ "batch 100/354 \t |current loss: 0.148386\n",
+ "batch 125/354 \t |current loss: 0.118308\n",
+ "batch 150/354 \t |current loss: 0.075305\n",
+ "batch 175/354 \t |current loss: 0.087421\n",
+ "batch 200/354 \t |current loss: 0.107263\n",
+ "batch 225/354 \t |current loss: 0.081158\n",
+ "batch 250/354 \t |current loss: 0.127829\n",
+ "batch 275/354 \t |current loss: 0.117017\n",
+ "batch 300/354 \t |current loss: 0.107976\n",
+ "batch 325/354 \t |current loss: 0.342758\n",
+ "batch 350/354 \t |current loss: 0.168653\n",
+ "Reconstruction loss: 0.24887285507836585\n"
+ ]
+ }
+ ],
+ "source": [
+ "training_reconstruction_loss = []\n",
+ "for i in range(EPOCHS):\n",
+ " print(f\"=======================EPOCH = {i + 1}======================\")\n",
+ " loss = train_vqvae(dl=train_dl, model=model, optim=optim)\n",
+ " training_reconstruction_loss.append(loss)\n",
+ " print(f\"Reconstruction loss: {loss}\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 29,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# save the model\n",
+ "torch.save(model, './results/vqvae.pth')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 25,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# load model\n",
+ "model = torch.load('./results/vqvae.pth')\n",
+ "model = model.to(DEVICE)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 26,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "test_real = next(iter(test_dl)) # load some from test dl\n",
+ "test_real = test_real[0]\n",
+ "test_real = test_real.to(DEVICE)\n",
+ "pre_conv = model.pre_quantization_conv(model.encoder(test_real)) # encoder, reshape\n",
+ "_, test_quantized, _, _ = model.vector_quantizer(pre_conv)\n",
+ "test_reconstructions = model.decoder(test_quantized)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# show reconstructed images\n",
+ "show(torchvision.utils.make_grid(test_reconstructions.cpu()))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# show original images\n",
+ "show(torchvision.utils.make_grid(test_real.cpu()))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 40,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 40,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "fig, (ax1, ax2) = plt.subplots(1, 2)\n",
+ "fig.suptitle('Reconstruction vs Original')\n",
+ "ax1.imshow(test_reconstructions.cpu().detach().numpy()[0][1])\n",
+ "ax2.imshow(test_real.cpu().detach().numpy()[0][1])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "torch.Size([1, 3, 256, 256])\n",
+ "tensor([113, 149, 430, 461])\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 7,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "test_input = next(iter(test_dl))\n",
+ "test_input = test_input[0][0]\n",
+ "test_input = test_input.unsqueeze(0)\n",
+ "print(test_input.shape)\n",
+ "test_input = test_input.to(DEVICE)\n",
+ "test_encoded = model.encoder(test_input)\n",
+ "test_encoded = model.pre_quantization_conv(test_encoded)\n",
+ "_, test_encoded, encodings, indices = model.vector_quantizer(test_encoded)\n",
+ "decoded = model.decoder(test_encoded)\n",
+ "# Plot codebook index\n",
+ "plot_image = indices.view(64, 64)\n",
+ "print(torch.unique(indices.to('cpu')))\n",
+ "plot_image = plot_image.to('cpu')\n",
+ "detached_image = plot_image.detach().numpy()\n",
+ "\n",
+ "test_input = test_input[0][0].cpu().detach().numpy()\n",
+ "fig, (ax1, ax2) = plt.subplots(1, 2)\n",
+ "fig.suptitle('Real vs Codebook index')\n",
+ "ax1.imshow(test_input)\n",
+ "ax2.imshow(detached_image)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 8,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# Convert Codebook index to quantized\n",
+ "fig, (ax1, ax2) = plt.subplots(1, 2)\n",
+ "fig.suptitle('Codebook indice vs quantized')\n",
+ "indices_quantized = model.vector_quantizer.get_quantized(indices)\n",
+ "decoded_quantized_indices = model.decoder(indices_quantized)\n",
+ "immi = decoded_quantized_indices[0]\n",
+ "immi = immi.to('cpu')\n",
+ "immi = immi.detach().numpy()\n",
+ "ax2.imshow(immi[1])\n",
+ "ax1.imshow(indices.cpu().view(64, 64).detach().numpy())"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Skipping initialisation of MaskedGatedConv2d\n",
+ "Skipping initialisation of MaskedGatedConv2d\n",
+ "Skipping initialisation of MaskedGatedConv2d\n",
+ "Skipping initialisation of MaskedGatedConv2d\n",
+ "Skipping initialisation of MaskedGatedConv2d\n",
+ "Skipping initialisation of MaskedGatedConv2d\n",
+ "Skipping initialisation of MaskedGatedConv2d\n",
+ "Skipping initialisation of MaskedGatedConv2d\n",
+ "Skipping initialisation of MaskedGatedConv2d\n",
+ "Skipping initialisation of MaskedGatedConv2d\n",
+ "Skipping initialisation of MaskedGatedConv2d\n",
+ "Skipping initialisation of MaskedGatedConv2d\n",
+ "Skipping initialisation of MaskedGatedConv2d\n",
+ "Skipping initialisation of MaskedGatedConv2d\n",
+ "Skipping initialisation of MaskedGatedConv2d\n"
+ ]
+ }
+ ],
+ "source": [
+ "pixel_cnn = PixelCNN()\n",
+ "pixel_cnn = pixel_cnn.to(DEVICE)\n",
+ "criterion = torch.nn.CrossEntropyLoss().to(DEVICE)\n",
+ "opt = torch.optim.Adam(model.parameters(), lr=0.01)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "pixel_cnn_train_ds = PixelCNNData(model=model, transforms=torchvision.transforms.ToTensor(), train=True)\n",
+ "pixel_cnn_train_dl = DataLoader(pixel_cnn_train_ds, batch_size=32)\n",
+ "\n",
+ "pixel_cnn_test_ds = PixelCNNData(model=model, transforms=torchvision.transforms.ToTensor(), train=False)\n",
+ "pixel_cnn_test_dl = DataLoader(pixel_cnn_test_ds, batch_size=32)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 12,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ " 0%| | 0/4 [00:00, ?it/s]"
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "\n",
+ "Epoch 1:\n"
+ ]
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ " 0%| | 0/4 [00:00, ?it/s]"
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "before\n",
+ "torch.Size([32, 64, 64, -1])\n"
+ ]
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "\n"
+ ]
+ },
+ {
+ "ename": "RuntimeError",
+ "evalue": "view size is not compatible with input tensor's size and stride (at least one dimension spans across two contiguous subspaces). Use .reshape(...) instead.",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mRuntimeError\u001b[0m Traceback (most recent call last)",
+ "Cell \u001b[0;32mIn [12], line 7\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m epoch \u001b[38;5;129;01min\u001b[39;00m tqdm\u001b[38;5;241m.\u001b[39mtqdm(\u001b[38;5;28mrange\u001b[39m(\u001b[38;5;241m1\u001b[39m, cnn_epochs)):\n\u001b[1;32m 6\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124mEpoch \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m:\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat(epoch))\n\u001b[0;32m----> 7\u001b[0m \u001b[43mtrain_pixel_cnn\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpixel_cnn\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpixel_cnn_train_dl\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcriterion\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m512\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mopt\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 8\u001b[0m cur_loss \u001b[38;5;241m=\u001b[39m test_pixel_cnn(pixel_cnn, pixel_cnn_test_dl, criterion, \u001b[38;5;241m512\u001b[39m)\n\u001b[1;32m 10\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m cur_loss \u001b[38;5;241m<\u001b[39m\u001b[38;5;241m=\u001b[39m BEST_LOSS:\n",
+ "File \u001b[0;32m~/Documents/GitHub/PatternFlow/recognition/45375325_VQVAE_for_image_creation/train.py:36\u001b[0m, in \u001b[0;36mtrain_pixel_cnn\u001b[0;34m(model, dl, criterion, n_embeddings, optimiser)\u001b[0m\n\u001b[1;32m 34\u001b[0m \u001b[39m# Train PixelCNN with images\u001b[39;00m\n\u001b[1;32m 35\u001b[0m \u001b[39mprint\u001b[39m(\u001b[39m'\u001b[39m\u001b[39mbefore\u001b[39m\u001b[39m'\u001b[39m)\n\u001b[0;32m---> 36\u001b[0m logits \u001b[39m=\u001b[39m model(x, x)\n\u001b[1;32m 37\u001b[0m \u001b[39mprint\u001b[39m(\u001b[39m'\u001b[39m\u001b[39mafter\u001b[39m\u001b[39m'\u001b[39m)\n\u001b[1;32m 38\u001b[0m logits \u001b[39m=\u001b[39m logits\u001b[39m.\u001b[39mpermute(\u001b[39m0\u001b[39m, \u001b[39m2\u001b[39m, \u001b[39m3\u001b[39m, \u001b[39m1\u001b[39m)\u001b[39m.\u001b[39mcontiguous()\n",
+ "File \u001b[0;32m/opt/homebrew/Caskroom/mambaforge/base/envs/comp3710/lib/python3.9/site-packages/torch/nn/modules/module.py:1190\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *input, **kwargs)\u001b[0m\n\u001b[1;32m 1186\u001b[0m \u001b[39m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m 1187\u001b[0m \u001b[39m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m 1188\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m (\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_pre_hooks \u001b[39mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m 1189\u001b[0m \u001b[39mor\u001b[39;00m _global_forward_hooks \u001b[39mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1190\u001b[0m \u001b[39mreturn\u001b[39;00m forward_call(\u001b[39m*\u001b[39;49m\u001b[39minput\u001b[39;49m, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m 1191\u001b[0m \u001b[39m# Do not call functions when jit is used\u001b[39;00m\n\u001b[1;32m 1192\u001b[0m full_backward_hooks, non_full_backward_hooks \u001b[39m=\u001b[39m [], []\n",
+ "File \u001b[0;32m~/Documents/GitHub/PatternFlow/recognition/45375325_VQVAE_for_image_creation/modules/pixelcnn.py:106\u001b[0m, in \u001b[0;36mPixelCNN.forward\u001b[0;34m(self, x, label)\u001b[0m\n\u001b[1;32m 104\u001b[0m shape \u001b[39m=\u001b[39m x\u001b[39m.\u001b[39msize() \u001b[39m+\u001b[39m (\u001b[39m-\u001b[39m\u001b[39m1\u001b[39m, )\n\u001b[1;32m 105\u001b[0m \u001b[39mprint\u001b[39m(shape)\n\u001b[0;32m--> 106\u001b[0m x \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39membedding(x\u001b[39m.\u001b[39;49mview(\u001b[39m-\u001b[39;49m\u001b[39m1\u001b[39;49m))\u001b[39m.\u001b[39mview(shape)\n\u001b[1;32m 107\u001b[0m \u001b[39mprint\u001b[39m(\u001b[39m'\u001b[39m\u001b[39mhello_world\u001b[39m\u001b[39m'\u001b[39m)\n\u001b[1;32m 108\u001b[0m x \u001b[39m=\u001b[39m x\u001b[39m.\u001b[39mpermute(\u001b[39m0\u001b[39m, \u001b[39m3\u001b[39m, \u001b[39m1\u001b[39m, \u001b[39m2\u001b[39m)\n",
+ "\u001b[0;31mRuntimeError\u001b[0m: view size is not compatible with input tensor's size and stride (at least one dimension spans across two contiguous subspaces). Use .reshape(...) instead."
+ ]
+ }
+ ],
+ "source": [
+ "BEST_LOSS = 999\n",
+ "LAST_SAVED = -1\n",
+ "cnn_epochs = 5\n",
+ "generated = []\n",
+ "for epoch in tqdm.tqdm(range(1, cnn_epochs)):\n",
+ " print(\"\\nEpoch {}:\".format(epoch))\n",
+ " train_pixel_cnn(pixel_cnn, pixel_cnn_train_dl, criterion, 512, opt)\n",
+ " cur_loss = test_pixel_cnn(pixel_cnn, pixel_cnn_test_dl, criterion, 512)\n",
+ "\n",
+ " if cur_loss <= BEST_LOSS:\n",
+ " BEST_LOSS = cur_loss\n",
+ " LAST_SAVED = epoch\n",
+ "\n",
+ " print(\"Saving model!\")\n",
+ " torch.save(model.state_dict(), 'results/{}_pixelcnn.pt'.format(pixel_cnn_train_dl))\n",
+ "\n",
+ " generated.append(generate_samples(pixel_cnn, 256))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "IndexError",
+ "evalue": "list index out of range",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mIndexError\u001b[0m Traceback (most recent call last)",
+ "Cell \u001b[0;32mIn [13], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m f1 \u001b[38;5;241m=\u001b[39m \u001b[43mgenerated\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m]\u001b[49m\n\u001b[1;32m 3\u001b[0m \u001b[38;5;66;03m# Visualise generated code\u001b[39;00m\n\u001b[1;32m 4\u001b[0m generated_code_indice \u001b[38;5;241m=\u001b[39m f1[\u001b[38;5;241m0\u001b[39m][\u001b[38;5;241m0\u001b[39m]\n",
+ "\u001b[0;31mIndexError\u001b[0m: list index out of range"
+ ]
+ }
+ ],
+ "source": [
+ "f1 = generated[-1]\n",
+ "\n",
+ "# Visualise generated code\n",
+ "generated_code_indice = f1[0][0]\n",
+ "generated_code_indice = generated_code_indice.to('cpu')\n",
+ "generated_code_indice = generated_code_indice.detach().numpy()\n",
+ "plt.imshow(generated_code_indice)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "NameError",
+ "evalue": "name 'f1' is not defined",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
+ "Cell \u001b[0;32mIn [14], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m generated_code_indice \u001b[38;5;241m=\u001b[39m \u001b[43mf1\u001b[49m[\u001b[38;5;241m0\u001b[39m][\u001b[38;5;241m0\u001b[39m]\n\u001b[1;32m 2\u001b[0m generated_code_indice \u001b[38;5;241m=\u001b[39m torch\u001b[38;5;241m.\u001b[39mflatten(generated_code_indice)\n",
+ "\u001b[0;31mNameError\u001b[0m: name 'f1' is not defined"
+ ]
+ }
+ ],
+ "source": [
+ "generated_code_indice = f1[0][0]\n",
+ "generated_code_indice = torch.flatten(generated_code_indice)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "unique_vals = [134, 418]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "NameError",
+ "evalue": "name 'generated_code_indice' is not defined",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
+ "Cell \u001b[0;32mIn [16], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m input_min \u001b[38;5;241m=\u001b[39m torch\u001b[38;5;241m.\u001b[39mmin(\u001b[43mgenerated_code_indice\u001b[49m)\n\u001b[1;32m 2\u001b[0m input_max \u001b[38;5;241m=\u001b[39m torch\u001b[38;5;241m.\u001b[39mmax(generated_code_indice)\n\u001b[1;32m 4\u001b[0m num_intervals \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlen\u001b[39m(unique_vals) \n",
+ "\u001b[0;31mNameError\u001b[0m: name 'generated_code_indice' is not defined"
+ ]
+ }
+ ],
+ "source": [
+ "input_min = torch.min(generated_code_indice)\n",
+ "input_max = torch.max(generated_code_indice)\n",
+ "\n",
+ "num_intervals = len(unique_vals) \n",
+ "interval_size = (input_max - input_min)/num_intervals\n",
+ "\n",
+ "for i in range(0, num_intervals):\n",
+ " MIN = input_min + i*interval_size\n",
+ " generated_code_indice[torch.logical_and(MIN<= generated_code_indice, generated_code_indice<=(MIN+interval_size))] = unique_vals[i]\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 17,
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "NameError",
+ "evalue": "name 'generated_code_indice' is not defined",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
+ "Cell \u001b[0;32mIn [17], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m torch\u001b[38;5;241m.\u001b[39munique(\u001b[43mgenerated_code_indice\u001b[49m)\n",
+ "\u001b[0;31mNameError\u001b[0m: name 'generated_code_indice' is not defined"
+ ]
+ }
+ ],
+ "source": [
+ "torch.unique(generated_code_indice)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "NameError",
+ "evalue": "name 'generated_code_indice' is not defined",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
+ "Cell \u001b[0;32mIn [18], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;66;03m# Visualise generated codebook indice\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m ffqq \u001b[38;5;241m=\u001b[39m \u001b[43mgenerated_code_indice\u001b[49m\n\u001b[1;32m 3\u001b[0m ffqq \u001b[38;5;241m=\u001b[39m ffqq\u001b[38;5;241m.\u001b[39mview(\u001b[38;5;241m64\u001b[39m,\u001b[38;5;241m64\u001b[39m)\n\u001b[1;32m 4\u001b[0m ffqq \u001b[38;5;241m=\u001b[39m ffqq\u001b[38;5;241m.\u001b[39mto(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mcpu\u001b[39m\u001b[38;5;124m'\u001b[39m)\n",
+ "\u001b[0;31mNameError\u001b[0m: name 'generated_code_indice' is not defined"
+ ]
+ }
+ ],
+ "source": [
+ "# Visualise generated codebook indice\n",
+ "ffqq = generated_code_indice\n",
+ "ffqq = ffqq.view(64,64)\n",
+ "ffqq = ffqq.to('cpu')\n",
+ "ffqq = ffqq.detach().numpy()\n",
+ "plt.imshow(ffqq)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 19,
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "NameError",
+ "evalue": "name 'generated_code_indice' is not defined",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
+ "Cell \u001b[0;32mIn [19], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m generated_code_indice \u001b[38;5;241m=\u001b[39m \u001b[43mgenerated_code_indice\u001b[49m\u001b[38;5;241m.\u001b[39mlong()\n\u001b[1;32m 2\u001b[0m generated_output \u001b[38;5;241m=\u001b[39m model\u001b[38;5;241m.\u001b[39mvq\u001b[38;5;241m.\u001b[39mget_quantized(generated_code_indice)\n\u001b[1;32m 3\u001b[0m generated_output \u001b[38;5;241m=\u001b[39m model\u001b[38;5;241m.\u001b[39mdecoder(generated_output)\n",
+ "\u001b[0;31mNameError\u001b[0m: name 'generated_code_indice' is not defined"
+ ]
+ }
+ ],
+ "source": [
+ "generated_code_indice = generated_code_indice.long()\n",
+ "generated_output = model.vq.get_quantized(generated_code_indice)\n",
+ "generated_output = model.decoder(generated_output)\n",
+ "# Visualise\n",
+ "tt = generated_output[0][0]\n",
+ "tt = tt.to('cpu')\n",
+ "tt = tt.detach().numpy()\n",
+ "plt.imshow(tt)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 41,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ " 0%| | 0/9664 [00:00, ?it/s]\n"
+ ]
+ },
+ {
+ "ename": "NotImplementedError",
+ "evalue": "The operator 'aten::_slow_conv2d_forward' is not current implemented for the MPS device. If you want this op to be added in priority during the prototype phase of this feature, please comment on https://github.com/pytorch/pytorch/issues/77764. As a temporary fix, you can set the environment variable `PYTORCH_ENABLE_MPS_FALLBACK=1` to use the CPU as a fallback for this op. WARNING: this will be slower than running natively on MPS.",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mNotImplementedError\u001b[0m Traceback (most recent call last)",
+ "Cell \u001b[0;32mIn [41], line 21\u001b[0m\n\u001b[1;32m 18\u001b[0m image \u001b[38;5;241m=\u001b[39m tfss(image)\n\u001b[1;32m 19\u001b[0m image \u001b[38;5;241m=\u001b[39m image\u001b[38;5;241m.\u001b[39munsqueeze(\u001b[38;5;241m0\u001b[39m)\n\u001b[0;32m---> 21\u001b[0m generated_output \u001b[38;5;241m=\u001b[39m \u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mencoder\u001b[49m\u001b[43m(\u001b[49m\u001b[43mimage\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 22\u001b[0m generated_output \u001b[38;5;241m=\u001b[39m model\u001b[38;5;241m.\u001b[39mpre_quantization_conv(generated_output)\n\u001b[1;32m 23\u001b[0m generated_output \u001b[38;5;241m=\u001b[39m model\u001b[38;5;241m.\u001b[39mvector_quantizer(generated_output)\n",
+ "File \u001b[0;32m/opt/homebrew/Caskroom/mambaforge/base/envs/comp3710/lib/python3.9/site-packages/torch/nn/modules/module.py:1190\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *input, **kwargs)\u001b[0m\n\u001b[1;32m 1186\u001b[0m \u001b[39m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m 1187\u001b[0m \u001b[39m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m 1188\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m (\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_pre_hooks \u001b[39mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m 1189\u001b[0m \u001b[39mor\u001b[39;00m _global_forward_hooks \u001b[39mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1190\u001b[0m \u001b[39mreturn\u001b[39;00m forward_call(\u001b[39m*\u001b[39;49m\u001b[39minput\u001b[39;49m, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m 1191\u001b[0m \u001b[39m# Do not call functions when jit is used\u001b[39;00m\n\u001b[1;32m 1192\u001b[0m full_backward_hooks, non_full_backward_hooks \u001b[39m=\u001b[39m [], []\n",
+ "File \u001b[0;32m~/Documents/GitHub/PatternFlow/recognition/45375325_VQVAE_for_image_creation/modules/encoder.py:41\u001b[0m, in \u001b[0;36mEncoder.forward\u001b[0;34m(self, x)\u001b[0m\n\u001b[1;32m 40\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mforward\u001b[39m(\u001b[39mself\u001b[39m, x):\n\u001b[0;32m---> 41\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mconv_steps(x)\n",
+ "File \u001b[0;32m/opt/homebrew/Caskroom/mambaforge/base/envs/comp3710/lib/python3.9/site-packages/torch/nn/modules/module.py:1190\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *input, **kwargs)\u001b[0m\n\u001b[1;32m 1186\u001b[0m \u001b[39m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m 1187\u001b[0m \u001b[39m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m 1188\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m (\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_pre_hooks \u001b[39mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m 1189\u001b[0m \u001b[39mor\u001b[39;00m _global_forward_hooks \u001b[39mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1190\u001b[0m \u001b[39mreturn\u001b[39;00m forward_call(\u001b[39m*\u001b[39;49m\u001b[39minput\u001b[39;49m, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m 1191\u001b[0m \u001b[39m# Do not call functions when jit is used\u001b[39;00m\n\u001b[1;32m 1192\u001b[0m full_backward_hooks, non_full_backward_hooks \u001b[39m=\u001b[39m [], []\n",
+ "File \u001b[0;32m/opt/homebrew/Caskroom/mambaforge/base/envs/comp3710/lib/python3.9/site-packages/torch/nn/modules/container.py:204\u001b[0m, in \u001b[0;36mSequential.forward\u001b[0;34m(self, input)\u001b[0m\n\u001b[1;32m 202\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mforward\u001b[39m(\u001b[39mself\u001b[39m, \u001b[39minput\u001b[39m):\n\u001b[1;32m 203\u001b[0m \u001b[39mfor\u001b[39;00m module \u001b[39min\u001b[39;00m \u001b[39mself\u001b[39m:\n\u001b[0;32m--> 204\u001b[0m \u001b[39minput\u001b[39m \u001b[39m=\u001b[39m module(\u001b[39minput\u001b[39;49m)\n\u001b[1;32m 205\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39minput\u001b[39m\n",
+ "File \u001b[0;32m/opt/homebrew/Caskroom/mambaforge/base/envs/comp3710/lib/python3.9/site-packages/torch/nn/modules/module.py:1190\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *input, **kwargs)\u001b[0m\n\u001b[1;32m 1186\u001b[0m \u001b[39m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m 1187\u001b[0m \u001b[39m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m 1188\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m (\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_pre_hooks \u001b[39mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m 1189\u001b[0m \u001b[39mor\u001b[39;00m _global_forward_hooks \u001b[39mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1190\u001b[0m \u001b[39mreturn\u001b[39;00m forward_call(\u001b[39m*\u001b[39;49m\u001b[39minput\u001b[39;49m, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m 1191\u001b[0m \u001b[39m# Do not call functions when jit is used\u001b[39;00m\n\u001b[1;32m 1192\u001b[0m full_backward_hooks, non_full_backward_hooks \u001b[39m=\u001b[39m [], []\n",
+ "File \u001b[0;32m/opt/homebrew/Caskroom/mambaforge/base/envs/comp3710/lib/python3.9/site-packages/torch/nn/modules/conv.py:463\u001b[0m, in \u001b[0;36mConv2d.forward\u001b[0;34m(self, input)\u001b[0m\n\u001b[1;32m 462\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mforward\u001b[39m(\u001b[39mself\u001b[39m, \u001b[39minput\u001b[39m: Tensor) \u001b[39m-\u001b[39m\u001b[39m>\u001b[39m Tensor:\n\u001b[0;32m--> 463\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_conv_forward(\u001b[39minput\u001b[39;49m, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mweight, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mbias)\n",
+ "File \u001b[0;32m/opt/homebrew/Caskroom/mambaforge/base/envs/comp3710/lib/python3.9/site-packages/torch/nn/modules/conv.py:459\u001b[0m, in \u001b[0;36mConv2d._conv_forward\u001b[0;34m(self, input, weight, bias)\u001b[0m\n\u001b[1;32m 455\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mpadding_mode \u001b[39m!=\u001b[39m \u001b[39m'\u001b[39m\u001b[39mzeros\u001b[39m\u001b[39m'\u001b[39m:\n\u001b[1;32m 456\u001b[0m \u001b[39mreturn\u001b[39;00m F\u001b[39m.\u001b[39mconv2d(F\u001b[39m.\u001b[39mpad(\u001b[39minput\u001b[39m, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_reversed_padding_repeated_twice, mode\u001b[39m=\u001b[39m\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mpadding_mode),\n\u001b[1;32m 457\u001b[0m weight, bias, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mstride,\n\u001b[1;32m 458\u001b[0m _pair(\u001b[39m0\u001b[39m), \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdilation, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mgroups)\n\u001b[0;32m--> 459\u001b[0m \u001b[39mreturn\u001b[39;00m F\u001b[39m.\u001b[39;49mconv2d(\u001b[39minput\u001b[39;49m, weight, bias, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mstride,\n\u001b[1;32m 460\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mpadding, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mdilation, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mgroups)\n",
+ "\u001b[0;31mNotImplementedError\u001b[0m: The operator 'aten::_slow_conv2d_forward' is not current implemented for the MPS device. If you want this op to be added in priority during the prototype phase of this feature, please comment on https://github.com/pytorch/pytorch/issues/77764. As a temporary fix, you can set the environment variable `PYTORCH_ENABLE_MPS_FALLBACK=1` to use the CPU as a fallback for this op. WARNING: this will be slower than running natively on MPS."
+ ]
+ }
+ ],
+ "source": [
+ "\n",
+ "from PIL import Image\n",
+ "from skimage.metrics import structural_similarity as ssim\n",
+ "import cv2\n",
+ "import os\n",
+ "from tqdm import tqdm\n",
+ "\n",
+ "# Load test image for SSIM\n",
+ "images = os.listdir('./data/train/images/')\n",
+ "max_ssim = 0\n",
+ "max_ssim_image = None\n",
+ "accepted_ssim_count = 0\n",
+ "for image_name in tqdm(images):\n",
+ " img_path = './data/train/images/' + image_name\n",
+ " image = Image.open(img_path).convert('RGB')\n",
+ " tfss = torchvision.transforms.Compose([\n",
+ " torchvision.transforms.ToTensor()\n",
+ " ])\n",
+ " image = tfss(image)\n",
+ " image = image.unsqueeze(0)\n",
+ "\n",
+ " image1 = generated_output[0][0].to('cpu').detach().numpy()\n",
+ " image2 = image[0][0].to('cpu').detach().numpy()\n",
+ " ssim_val = ssim(image1, image2)\n",
+ " if ssim_val > 0.6:\n",
+ " accepted_ssim_count += 1\n",
+ " if ssim_val > max_ssim:\n",
+ " max_ssim = ssim_val\n",
+ " max_ssim_image_name = image_name\n",
+ " max_ssim_image = image2\n",
+ "\n",
+ "print(f\"SSIM was >0.60 against {accepted_ssim_count} images\")\n",
+ "print(f\"Max SSIM with {max_ssim_image_name} = {max_ssim}\")\n",
+ "fig, (ax1, ax2) = plt.subplots(1, 2)\n",
+ "fig.suptitle('Generated vs real (MAX SSIM)')\n",
+ "ax1.imshow(tt)\n",
+ "ax2.imshow(max_ssim_image)\n",
+ "\n"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3.9.13 ('comp3710')",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.9.13"
+ },
+ "vscode": {
+ "interpreter": {
+ "hash": "9b95a958677244b4d6bd7f80f106d51a95a8d705e67da7983369de3b3a9efca8"
+ }
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/recognition/45375325_VQVAE_for_image_creation/modules/decoder.py b/recognition/45375325_VQVAE_for_image_creation/modules/decoder.py
new file mode 100644
index 0000000000..09e51855a6
--- /dev/null
+++ b/recognition/45375325_VQVAE_for_image_creation/modules/decoder.py
@@ -0,0 +1,47 @@
+import torch.nn as nn
+from modules.stack import ResidualStack
+
+
+class Decoder(nn.Module):
+ """
+ Decoder network
+
+ given a latent sample z, maps to the original space
+ """
+
+ def __init__(self, input_dim, between_latent_dim, latent_dim):
+ super(Decoder, self).__init__()
+ kernel = 4
+ stride = 2
+
+ self.inverse_conv_steps = nn.Sequential(
+ nn.Conv2d(in_channels=input_dim,
+ out_channels=latent_dim,
+ kernel_size=kernel - 1,
+ stride=stride - 1,
+ padding=1
+ ),
+ ResidualStack(input_dim=latent_dim,
+ between_latent_dim=between_latent_dim,
+ latent_dim=latent_dim
+ ),
+ ResidualStack(input_dim=latent_dim,
+ between_latent_dim=between_latent_dim,
+ latent_dim=latent_dim
+ ),
+ nn.ConvTranspose2d(in_channels=latent_dim,
+ out_channels=latent_dim//2,
+ kernel_size=kernel,
+ stride=stride,
+ padding=1
+ ),
+ nn.ConvTranspose2d(in_channels=latent_dim//2,
+ out_channels=3,
+ kernel_size=kernel,
+ stride=stride,
+ padding=1
+ )
+ )
+
+ def forward(self, x):
+ return self.inverse_conv_steps(x)
diff --git a/recognition/45375325_VQVAE_for_image_creation/modules/encoder.py b/recognition/45375325_VQVAE_for_image_creation/modules/encoder.py
new file mode 100644
index 0000000000..09d4d68f1d
--- /dev/null
+++ b/recognition/45375325_VQVAE_for_image_creation/modules/encoder.py
@@ -0,0 +1,41 @@
+import torch.nn as nn
+from modules.stack import ResidualStack
+
+
+class Encoder(nn.Module):
+ """
+ Encoding network
+
+ given data x, maps the data to latent space
+ """
+
+ def __init__(self, input_dim, between_latent_dim, latent_dim):
+ super(Encoder, self).__init__()
+ kernel = 4
+ stride = 2
+ self.conv_steps = nn.Sequential(
+ nn.Conv2d(in_channels=input_dim,
+ out_channels=latent_dim//2,
+ kernel_size=kernel,
+ stride=stride,
+ padding=1
+ ),
+ nn.ReLU(),
+ nn.Conv2d(in_channels=latent_dim//2,
+ out_channels=latent_dim,
+ kernel_size=kernel,
+ stride=stride,
+ padding=1
+ ),
+ ResidualStack(input_dim=latent_dim,
+ between_latent_dim=between_latent_dim,
+ latent_dim=latent_dim
+ ),
+ ResidualStack(input_dim=latent_dim,
+ between_latent_dim=between_latent_dim,
+ latent_dim=latent_dim
+ )
+ )
+
+ def forward(self, x):
+ return self.conv_steps(x)
diff --git a/recognition/45375325_VQVAE_for_image_creation/modules/pixelcnn.py b/recognition/45375325_VQVAE_for_image_creation/modules/pixelcnn.py
new file mode 100644
index 0000000000..cde280fd85
--- /dev/null
+++ b/recognition/45375325_VQVAE_for_image_creation/modules/pixelcnn.py
@@ -0,0 +1,132 @@
+import torch.nn as nn
+import torch
+
+
+def init_weights(module):
+ classname = module.__class__.__name__
+ if classname.find('Conv') != -1:
+ try:
+ nn.init.xavier_uniform_(module.weight.data)
+ module.bias.data.fill_(0)
+ except AttributeError:
+ print(f"Skipping initialisation of {classname}")
+
+
+class GatedActivation(nn.Module):
+ def __init__(self):
+ super().__init__()
+
+ def forward(self, x):
+ x, y = x.chunk(2, dim=1)
+ return nn.functional.tanh(x) * nn.functional.sigmoid(y)
+
+
+class MaskedGatedConv2d(nn.Module):
+ def __init__(self, mask_type, dim, kernel, residual=True, num_classes=10):
+ super().__init__()
+ assert kernel % 2 == 1, print("Kernel size must be odd")
+ self.mask_type = mask_type
+ self.residual = residual
+
+ self.class_conditional_embedding = nn.Embedding(num_classes, 2 * dim)
+
+ kernel_shape = (kernel // 2 + 1, kernel)
+ padding_shape = (kernel // 2, kernel // 2)
+ self.vertical_stack = nn.Conv2d(
+ dim, dim * 2, kernel_shape, 1, padding_shape
+ )
+
+ self.vertical_to_horizontal = nn.Conv2d(2 * dim, 2 * dim, 1)
+
+ kernel_shape = (1, kernel // 2 + 1)
+ padding_shape = (0, kernel // 2)
+ self.horizontal_stack = nn.Conv2d(
+ dim, dim * 2, kernel_shape, 1, padding_shape
+ )
+
+ self.horizontal_residuals = nn.Conv2d(dim, dim, 1)
+
+ self.gate = GatedActivation()
+
+ def make_causal(self):
+ self.vertical_stack.weight.data[:, :, -1].zero_() # mask final row
+ self.horizontal_stack.weight.data[:, :, :, -1].zero_() # mask final column
+
+ def forward(self, x_vertical, x_horizontal, h):
+ if self.mask_type == 'A':
+ self.make_causal()
+
+ h = self.class_conditional_embedding(h)
+ h_vertical = self.vertical_stack(x_vertical)
+ h_vertical = h_vertical[:, :, :, :x_horizontal.size(-2)]
+ out_vertical = self.gate(h_vertical + h[:, :, None, None])
+
+ h_horizontal = self.horizontal_stack(x_horizontal)
+ h_horizontal = h_horizontal[:, :, :, :x_horizontal.size(-2)]
+ v2h = self.vertical_to_horizontal(h_vertical)
+
+ out = self.gate(v2h + h_horizontal + h[:, :, None, None])
+ if self.residual:
+ out_horizontal = self.horizontal_residuals(out) + h_horizontal
+ else:
+ out_horizontal = self.horizontal_residuals(out)
+
+ return out_vertical, out_horizontal
+
+
+class PixelCNN(nn.Module):
+ def __init__(self, input_dimension=256, dim=64, num_layers=15, num_classes=10):
+ super().__init__()
+ self.dim = dim
+
+ self.embedding = nn.Embedding(input_dimension, dim)
+
+ self.layers = nn.ModuleList()
+
+ for i in range(num_layers):
+ mask_type = 'A' if i == 0 else 'B'
+ kernel = 7 if i == 0 else 3
+ residual = False if i == 0 else True
+
+ layer = MaskedGatedConv2d(mask_type=mask_type, dim=dim, kernel=kernel, residual=residual, num_classes=num_classes)
+
+ self.layers.append(module=layer)
+
+ self.out_conv = nn.Sequential(
+ nn.Conv2d(dim, 512, 1),
+ nn.ReLU(True),
+ nn.Conv2d(512, input_dimension, 1)
+ )
+
+ self.apply(init_weights)
+
+ def forward(self, x, label):
+ shape = x.size() + (-1, )
+ print(shape)
+ x = self.embedding(x.view(-1)).view(shape)
+ print('hello_world')
+ x = x.permute(0, 3, 1, 2)
+
+ x_vertical, x_horizontal = (x, x)
+ for i, layer in enumerate(self.layers):
+ x_vertical, h_horizontal = layer(x_vertical, x_horizontal, label)
+
+ return self.out_conv(x_horizontal)
+
+ def generate(self, label, shape=(8, 8), batch_size = 64):
+ param = next(self.parameters())
+ x = torch.zeros((batch_size, *shape), dtype=torch.int64, device=param.device)
+
+ for i in range(shape[0]):
+ for j in range(shape[1]):
+ logits = self.forward(x, label)
+ probs = nn.functional.softmax(logits[:, :, i, j], -1)
+ x.data[:, i, j].copy_(probs.multinomial(1).squeeze().data)
+
+ return x
+
+# model = PixelCNN()
+# x = torch.randn(1,3,256,256)
+# x = x.type(torch.LongTensor)
+# y = model(x,x)
+
diff --git a/recognition/45375325_VQVAE_for_image_creation/modules/quantizer.py b/recognition/45375325_VQVAE_for_image_creation/modules/quantizer.py
new file mode 100644
index 0000000000..b4a6270bd5
--- /dev/null
+++ b/recognition/45375325_VQVAE_for_image_creation/modules/quantizer.py
@@ -0,0 +1,63 @@
+import torch
+import torch.nn as nn
+
+DEVICE = torch.device("mps" if torch.has_mps else "cuda" if torch.cuda.is_available() else "cpu")
+
+
+class Quantizer(nn.Module):
+ """
+ Discretizer
+ """
+
+ def __init__(self, num_embeddings, embedding_dim, beta):
+ super(Quantizer, self).__init__()
+ self.num_embeddings = num_embeddings
+ self.embedding_dim = embedding_dim
+ self.beta = beta
+
+ self.embedding = nn.Embedding(self.num_embeddings, self.embedding_dim)
+ self.embedding.weight.data.uniform_(-1.0 / self.num_embeddings, 1.0 / self.num_embeddings)
+
+ def forward(self, z):
+ """
+ transforms the encoder network z to a discrete one-hot vector mapping that is the index
+ of the closest embedding vector e_j
+ :param z: the encoder network to be quantized
+ :return: loss, quantized z z_q, perplexity, minimum encodings, minimum encoding indicies
+ """
+ # convert z from z.shape = (batch, channel, height, width) to (batch, height, width, channel)
+ z = z.permute(0, 2, 3, 1).contiguous()
+ # then flatten
+ z_flattened = z.view(-1, self.embedding_dim)
+
+ # z to embeddings e_j (z - e)^2 = z^2 + e^2 - 2e * z
+ d = (torch.sum(z_flattened ** 2, dim=1, keepdim=True)
+ + torch.sum(self.embedding.weight ** 2, dim=1)
+ - 2 * torch.matmul(z_flattened, self.embedding.weight.t()))
+
+ # calculate closest encodings
+ train_indices = torch.argmin(d, dim=1)
+ min_encoding_indices = torch.argmin(d, dim=1).unsqueeze(1)
+ min_encodings = torch.zeros(min_encoding_indices.shape[0], self.num_embeddings, device=DEVICE)
+ min_encodings.scatter_(1, min_encoding_indices, 1)
+
+ # get quantized vectors
+ z_q = torch.matmul(min_encodings, self.embedding.weight).view(z.shape)
+
+ # compute embedding loss
+ embedding_loss = nn.functional.mse_loss(z_q.detach(), z)
+ q_latent_loss = nn.functional.mse_loss(z_q, z.detach())
+ loss = q_latent_loss + self.beta * embedding_loss
+
+ # maintain gradients
+ z_q = z + (z_q - z).detach()
+ # reshape quantized z to look like original input
+
+ return loss, z_q.permute(0, 3, 1, 2).contiguous(), min_encodings, train_indices
+
+ def get_quantized(self, x):
+ encoding_indices = x.unsqueeze(1)
+ encodings = torch.zeros(encoding_indices.shape[0], self.num_embeddings, device=DEVICE)
+ encodings.scatter_(1, encoding_indices, 1)
+ quantized = torch.matmul(encodings, self.embedding.weight).view(1, 64, 64, 64)
+ return quantized.permute(0, 3, 1, 2).contiguous()
diff --git a/recognition/45375325_VQVAE_for_image_creation/modules/stack.py b/recognition/45375325_VQVAE_for_image_creation/modules/stack.py
new file mode 100644
index 0000000000..6c05d83f43
--- /dev/null
+++ b/recognition/45375325_VQVAE_for_image_creation/modules/stack.py
@@ -0,0 +1,30 @@
+import torch.nn as nn
+
+
+class ResidualStack(nn.Module):
+ """
+ A stack of residual layers
+ """
+
+ def __init__(self, input_dim, between_latent_dim, latent_dim):
+ super(ResidualStack, self).__init__()
+ self.net = nn.Sequential(
+ nn.ReLU(),
+ nn.Conv2d(in_channels=input_dim,
+ out_channels=between_latent_dim,
+ kernel_size=3,
+ stride=1,
+ padding=1,
+ bias=False
+ ),
+ nn.ReLU(),
+ nn.Conv2d(in_channels=between_latent_dim,
+ out_channels=latent_dim,
+ kernel_size=1,
+ stride=1,
+ bias=False
+ )
+ )
+
+ def forward(self, x):
+ return x + self.net(x)
diff --git a/recognition/45375325_VQVAE_for_image_creation/modules/vqvae.py b/recognition/45375325_VQVAE_for_image_creation/modules/vqvae.py
new file mode 100644
index 0000000000..7efb862f2b
--- /dev/null
+++ b/recognition/45375325_VQVAE_for_image_creation/modules/vqvae.py
@@ -0,0 +1,40 @@
+import torch.nn as nn
+from modules.encoder import Encoder
+from modules.decoder import Decoder
+from modules.quantizer import Quantizer
+
+
+class VQVAE(nn.Module):
+ def __init__(self, latent_dim, res_h_dim,
+ num_embeddings, embedding_dim, beta):
+ super(VQVAE, self).__init__()
+ # encode image
+ self.encoder = Encoder(input_dim=3,
+ between_latent_dim=res_h_dim,
+ latent_dim=latent_dim
+ )
+
+ self.pre_quantization_conv = nn.Conv2d(in_channels=latent_dim,
+ out_channels=embedding_dim,
+ kernel_size=1,
+ stride=1)
+
+ # pass continuous latent dim to quantizer
+ self.vector_quantizer = Quantizer(num_embeddings=num_embeddings,
+ embedding_dim=embedding_dim,
+ beta=beta)
+
+ # decode discrete latent repr
+ self.decoder = Decoder(input_dim=embedding_dim,
+ between_latent_dim=res_h_dim,
+ latent_dim=latent_dim
+ )
+
+ def forward(self, x):
+ z_e = self.encoder(x)
+
+ z_e = self.pre_quantization_conv(z_e)
+ embedding_loss, z_q, _, _ = self.vector_quantizer(z_e)
+ x_hat = self.decoder(z_q)
+
+ return embedding_loss, x_hat
diff --git a/recognition/45375325_VQVAE_for_image_creation/predict.py b/recognition/45375325_VQVAE_for_image_creation/predict.py
new file mode 100644
index 0000000000..5ab256116e
--- /dev/null
+++ b/recognition/45375325_VQVAE_for_image_creation/predict.py
@@ -0,0 +1,11 @@
+import torch
+DEVICE = torch.device("mps" if torch.has_mps else "cuda" if torch.cuda.is_available() else "cpu")
+
+
+def generate_samples(model, img_dim):
+ label = torch.arange(10).expand(10, 10).contiguous().view(-1)
+ label = label.long().to(DEVICE)
+
+ x_tilde = model.generate(label, shape=(img_dim, img_dim), batch_size=100)
+
+ print(x_tilde[0])
diff --git a/recognition/45375325_VQVAE_for_image_creation/results/vqvae.pth b/recognition/45375325_VQVAE_for_image_creation/results/vqvae.pth
new file mode 100644
index 0000000000..b53e2a7421
Binary files /dev/null and b/recognition/45375325_VQVAE_for_image_creation/results/vqvae.pth differ
diff --git a/recognition/45375325_VQVAE_for_image_creation/train.py b/recognition/45375325_VQVAE_for_image_creation/train.py
new file mode 100644
index 0000000000..3613a9f14f
--- /dev/null
+++ b/recognition/45375325_VQVAE_for_image_creation/train.py
@@ -0,0 +1,75 @@
+import torch
+import numpy as np
+import random
+
+EPOCHS = 2
+DEVICE = torch.device("mps" if torch.has_mps else "cuda" if torch.cuda.is_available() else "cpu")
+
+
+def train_vqvae(dl, model, optim):
+ losses = []
+ for batch, (x, _) in enumerate(dl):
+ x = x.to(DEVICE)
+
+ optim.zero_grad()
+ vq_loss, data_recon = model(x)
+ recon_error = torch.nn.functional.mse_loss(data_recon, x) / 0.0338
+ loss = recon_error + vq_loss
+ loss.backward()
+ optim.step()
+ losses.append(recon_error.item())
+ if batch % 25 == 0:
+ print(f"batch {batch:4}/{len(dl)} \t |current loss: {recon_error.item():.6f}")
+
+ losses = sum(losses) / len(losses)
+ return losses
+
+
+def train_pixel_cnn(model, dl, criterion, n_embeddings, optimiser):
+ train_loss = []
+ for batch_idx, (x, _) in enumerate(dl):
+
+ x = (x[:, 0]).to(DEVICE)
+
+ # Train PixelCNN with images
+ print('before')
+ logits = model(x, x)
+ print('after')
+ logits = logits.permute(0, 2, 3, 1).contiguous()
+
+ print(logits.view(-1, n_embeddings).shape)
+ print(x.view(-1).shape)
+
+ loss = criterion(
+ logits.view(-1, n_embeddings),
+ x.view(-1)
+ )
+
+ optimiser.zero_grad()
+ loss.backward()
+ optimiser.step()
+
+ train_loss.append(loss.item())
+
+ if batch_idx % 25 == 0:
+ print(f"Batch {batch_idx * len(x)}/{len(dl.dataset)} \tLoss: {loss.item()}")
+
+
+def test_pixel_cnn(model, dl, criterion, n_embeddings):
+ val_loss = []
+ with torch.no_grad():
+ for batch_idx, (x, label) in enumerate(dl):
+ x = (x[:, 0]).to(DEVICE)
+
+ logits = model(x, label)
+
+ logits = logits.permute(0, 2, 3, 1).contiguous()
+ loss = criterion(
+ logits.view(-1, n_embeddings),
+ x.view(-1)
+ )
+
+ val_loss.append(loss.item())
+
+ print(f"Validation Completed!\tLoss: {np.asarray(val_loss).mean(0)}")
+ return np.asarray(val_loss).mean(0)
diff --git a/recognition/ISICs_UNet/README.md b/recognition/ISICs_UNet/README.md
index 788ea17b79..8c9439559a 100644
--- a/recognition/ISICs_UNet/README.md
+++ b/recognition/ISICs_UNet/README.md
@@ -1,101 +1,52 @@
-# Segment the ISICs data set with the U-net
+# Segmenting ISICs with U-Net
-## Project Overview
-This project aim to solve the segmentation of skin lesian (ISIC2018 data set) using the U-net, with all labels having a minimum Dice similarity coefficient of 0.7 on the test set[Task 3].
+COMP3710 Report recognition problem 3 (Segmenting ISICs data set with U-Net) solved in TensorFlow
-## ISIC2018
-
+Created by Christopher Bailey (45576430)
-Skin Lesion Analysis towards Melanoma Detection
+## The problem and algorithm
+The problem solved by this program is binary segmentation of the ISICs skin lesion data set. Segmentation is a way to label pixels in an image according to some grouping, in this case lesion or non-lesion. This translates images of skin to masks representing areas of concern for skin lesions.
-Task found in https://challenge2018.isic-archive.com/
+U-Net is a form of autoencoder where the downsampling path is expected to learn the features of the image and the upsampling path learns how to recreate the masks. Long skip connections between downpooling and upsampling layers are utilised to overcome the bottleneck in traditional autoencoders allowing feature representations to be recreated.
+## How it works
+A four layer padded U-Net is used, preserving skin features and mask resolution. The implementation utilises Adam as the optimizer and implements Dice distance as the loss function as this appeared to give quicker convergence than other methods (eg. binary cross-entropy).
-## U-net
-
+The utilised metric is a Dice coefficient implementation. My initial implementation appeared faulty and was replaced with a 3rd party implementation which appears correct. 3 epochs was observed to be generally sufficient to observe Dice coefficients of 0.8+ on test datasets but occasional non-convergence was observed and could be curbed by increasing the number of epochs. Visualisation of predictions is also implemented and shows reasonable correspondence. Orange bandaids represent an interesting challenge for the implementation as presented.
-U-net is one of the popular image segmentation architectures used mostly in biomedical purposes. The name UNet is because it’s architecture contains a compressive path and an expansive path which can be viewed as a U shape. This architecture is built in such a way that it could generate better results even for a less number of training data sets.
+### Training, validation and testing split
+Training, validation and testing uses a respective 60:20:20 split, a commonly assumed starting point suggested by course staff. U-Net in particular was developed to work "with very few training images" (Ronneberger et al, 2015) The input data for this problem consists of 2594 images and masks. This split appears to provide satisfactory results.
-## Data Set Structure
+## Using the model
+### Dependencies required
+* Python3 (tested with 3.8)
+* TensorFlow 2.x (tested with 2.3)
+* glob (used to load filenames)
+* matplotlib (used for visualisations, tested with 3.3)
-data set folder need to be stored in same directory with structure same as below
-```bash
-ISIC2018
- |_ ISIC2018_Task1-2_Training_Input_x2
- |_ ISIC_0000000
- |_ ISIC_0000001
- |_ ...
- |_ ISIC2018_Task1_Training_GroundTruth_x2
- |_ ISIC_0000000_segmentation
- |_ ISIC_0000001_segmentation
- |_ ...
-```
+### Parameter tuning
+The model was developed on a GTX 1660 TI (6GB VRAM) and certain values (notably batch size and image resolution) were set lower than might otherwise be ideal on more capable hardware. This is commented in the relevant code.
-## Dice Coefficient
+### Running the model
+The model is executed via the main.py script.
-The Sørensen–Dice coefficient is a statistic used to gauge the similarity of two samples.
+### Example output
+Given a batch size of 1 and 3 epochs the following output was observed on a single run:
+Era | Loss | Dice coefficient
+--- | ---- | ----------------
+Epoch 1 | 0.7433 | 0.2567
+Epoch 2 | 0.3197 | 0.6803
+Epoch 3 | 0.2657 | 0.7343
+Testing | 0.1820 | 0.8180
-Further information in https://en.wikipedia.org/wiki/S%C3%B8rensen%E2%80%93Dice_coefficient
-## Dependencies
+### Figure 1 - example visualisation plot
+Skin images in left column, true mask middle, predicted mask right column
+
-- python 3
-- tensorflow 2.1.0
-- pandas 1.1.4
-- numpy 1.19.2
-- matplotlib 3.3.2
-- scikit-learn 0.23.2
-- pillow 8.0.1
-
-
-## Usages
-
-- Run `train.py` for training the UNet on ISIC data.
-- Run `evaluation.py` for evaluation and case present.
-
-## Advance
-
-- Modify `setting.py` for custom setting, such as different batch size.
-- Modify `unet.py` for custom UNet, such as different kernel size.
-
-## Algorithm
-
-- data set:
- - The data set we used is the training set of ISIC 2018 challenge data which has segmentation labels.
- - Training: Validation: Test = 1660: 415: 519 = 0.64: 0.16 : 0.2 (Training: Test = 4: 1 and in Training, further split 4: 1 for Training: Validation)
- - Training data augmentations: rescale, rotate, shift, zoom, grayscale
-- model:
- - Original UNet with padding which can keep the shape of input and output same.
- - The first convolutional layers has 16 output channels.
- - The activation function of all convolutional layers is ELU.
- - Without batch normalization layers.
- - The inputs is (384, 512, 1)
- - The output is (384, 512, 1) after sigmoid activation.
- - Optimizer: Adam, lr = 1e-4
- - Loss: dice coefficient loss
- - Metrics: accuracy & dice coefficient
-
-## Results
-
-Evaluation dice coefficient is 0.805256724357605.
-
-plot of train/valid Dice coefficient:
-
-
-
-case present:
-
-
-
-## Reference
-Manna, S. (2020). K-Fold Cross Validation for Deep Learning using Keras. [online] Medium. Available at: https://medium.com/the-owl/k-fold-cross-validation-in-keras-3ec4a3a00538 [Accessed 24 Nov. 2020].
-
-zhixuhao (2020). zhixuhao/unet. [online] GitHub. Available at: https://github.com/zhixuhao/unet.
-
-GitHub. (n.d.). NifTK/NiftyNet. [online] Available at: https://github.com/NifTK/NiftyNet/blob/a383ba342e3e38a7ad7eed7538bfb34960f80c8d/niftynet/layer/loss_segmentation.py [Accessed 24 Nov. 2020].
-
-Team, K. (n.d.). Keras documentation: Losses. [online] keras.io. Available at: https://keras.io/api/losses/#creating-custom-losses [Accessed 24 Nov. 2020].
-
-262588213843476 (n.d.). unet.py. [online] Gist. Available at: https://gist.github.com/abhinavsagar/fe0c900133cafe93194c069fe655ef6e [Accessed 24 Nov. 2020].
-
-Stack Overflow. (n.d.). python - Disable Tensorflow debugging information. [online] Available at: https://stackoverflow.com/questions/35911252/disable-tensorflow-debugging-information [Accessed 24 Nov. 2020].
+## References
+Segments of code in this assignment were used from or based on the following sources:
+1. COMP3710-demo-code.ipynb from Guest Lecture
+1. https://www.tensorflow.org/tutorials/load_data/images
+1. https://www.tensorflow.org/guide/gpu
+1. Karan Jakhar (2019) https://medium.com/@karan_jakhar/100-days-of-code-day-7-84e4918cb72c
\ No newline at end of file
diff --git a/recognition/ISICs_Unet/README.md b/recognition/ISICs_Unet/README.md
index f2c009212e..8c9439559a 100644
--- a/recognition/ISICs_Unet/README.md
+++ b/recognition/ISICs_Unet/README.md
@@ -49,4 +49,4 @@ Segments of code in this assignment were used from or based on the following sou
1. COMP3710-demo-code.ipynb from Guest Lecture
1. https://www.tensorflow.org/tutorials/load_data/images
1. https://www.tensorflow.org/guide/gpu
-1. Karan Jakhar (2019) https://medium.com/@karan_jakhar/100-days-of-code-day-7-84e4918cb72c
+1. Karan Jakhar (2019) https://medium.com/@karan_jakhar/100-days-of-code-day-7-84e4918cb72c
\ No newline at end of file
diff --git a/recognition/XUE4645768/README.md b/recognition/XUE4645768/README.md
index 36250adaa3..a70fe02923 100644
--- a/recognition/XUE4645768/README.md
+++ b/recognition/XUE4645768/README.md
@@ -55,5 +55,3 @@ Warning: Please pay attention to whether the data path is correct when you run t
```python
-
-```
diff --git a/recognition/XUE4645768/Readme.md b/recognition/XUE4645768/Readme.md
index 94bc1848c0..efe1acd2e7 100644
--- a/recognition/XUE4645768/Readme.md
+++ b/recognition/XUE4645768/Readme.md
@@ -91,15 +91,9 @@ Epoch 196: Loss 0.1599, TrainAcc 0.9562, ValAcc 0.9126
Epoch 197: Loss 0.1595, TrainAcc 0.9562, ValAcc 0.9123
Epoch 198: Loss 0.1591, TrainAcc 0.9562, ValAcc 0.9123
Epoch 199: Loss 0.1587, TrainAcc 0.9562, ValAcc 0.9123```
-
For test accuracy:around 0.9
-
# TSNE
For the test:iteration=500, with lower dimension to 2
-
-
```python
-
-```