{"id":17236070,"url":"https://github.com/hnarayanan/artistic-style-transfer","last_synced_at":"2025-04-09T13:07:44.005Z","repository":{"id":149732696,"uuid":"81736914","full_name":"hnarayanan/artistic-style-transfer","owner":"hnarayanan","description":"Convolutional neural networks for artistic style transfer.","archived":false,"fork":false,"pushed_at":"2017-12-07T11:29:42.000Z","size":16788,"stargazers_count":354,"open_issues_count":2,"forks_count":78,"subscribers_count":16,"default_branch":"master","last_synced_at":"2025-04-02T06:51:25.251Z","etag":null,"topics":["convolutional-neural-networks","keras","talk","tensorflow","tutorial-code"],"latest_commit_sha":null,"homepage":"https://harishnarayanan.org/writing/artistic-style-transfer/","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/hnarayanan.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2017-02-12T15:44:44.000Z","updated_at":"2025-02-15T02:24:15.000Z","dependencies_parsed_at":null,"dependency_job_id":"92a909b7-ecb6-4b4a-8438-f19ea38648d4","html_url":"https://github.com/hnarayanan/artistic-style-transfer","commit_stats":{"total_commits":34,"total_committers":1,"mean_commits":34.0,"dds":0.0,"last_synced_commit":"05c95e5ac7001201d1ae9bf734a9224cf3445388"},"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hnarayanan%2Fartistic-style-transfer","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hnarayanan%2Fartistic-style-transfer/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hnarayanan%2Fartistic-style-transfer/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hnarayanan%2Fartistic-style-transfer/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/hnarayanan","download_url":"https://codeload.github.com/hnarayanan/artistic-style-transfer/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248045232,"owners_count":21038553,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["convolutional-neural-networks","keras","talk","tensorflow","tutorial-code"],"created_at":"2024-10-15T05:35:19.161Z","updated_at":"2025-04-09T13:07:43.985Z","avatar_url":"https://github.com/hnarayanan.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Convolutional neural networks for artistic style transfer\n\nThis repository contains (TensorFlow and Keras) code that goes along\nwith a [related blog post][blog-post] and [talk\n(PDF)][talk-slides]. Together, they act as a systematic look at\nconvolutional neural networks from theory to practice, using artistic\nstyle transfer as a motivating example. The blog post provides context\nand covers the underlying theory, while working through the Jupyter\nnotebooks in this repository offers a more hands-on learning\nexperience.\n\nIf you have any questions about any of this stuff, feel free to [open\nan issue][support-issue] or tweet at me: [@copingbear][twitter].\n\n## Setup\n\n1. Install Python (2.7), pip and virtualenv on your machine. The\ninstructions to do this depend on your operating system (Linux, macOS,\nWindows), but there are many tutorials on the internet that should\nhelp you get started.\n\n2. Once you have the above setup, it is quite easy to setup the\nrequirements for the notebooks in this repository. First you clone a\ncopy of this repository:\n\n   ````\n   git clone https://github.com/hnarayanan/artistic-style-transfer.git\n   ````\n\n3. Then you navigate to this folder in your shell and then install the\nrequirements needed for the Jupyter notebooks.\n\n   ````\n   cd artistic-style-transfer\n   virtualenv venv\n   source venv/bin/activate\n   pip install -r requirements.txt\n   ````\n\n4. If it doesn't exist, create a file called `~/.keras/keras.json` and\nmake sure it looks like the following:\n\n   ````\n   {\n       \"image_dim_ordering\": \"tf\",\n       \"epsilon\": 1e-07,\n       \"floatx\": \"float32\",\n       \"backend\": \"tensorflow\"\n   }\n   ````\n\n5. That's it! You can now start Jupyter and browse, open, run and\nmodify the notebooks.\n\n   ````\n   jupyter notebook\n   ````\n\n## Contents\n\n### iPython Notebooks\n\n1. [A linear classifier for MNIST data][linear-mnist]\n2. [A neural network-based classifier for MNIST data (Attempt 1)][neural-mnist-1]\n3. [A neural network-based classifier for MNIST data (Attempt 2)][neural-mnist-2]\n4. [A convolutional neural network-based classifier for MNIST data][convnet-mnist]\n5. [VGG Net (16) on ImageNet, the easy way][vggnet-imagenet]\n6. [Artistic style transfer with a repurposed VGG Net (16)][style-transfer]\n\n### External Resources\n\n1. [Related blog post][blog-post]\n2. [Related talk slides][talk-slides]\n\n\n[blog-post]: https://harishnarayanan.org/writing/artistic-style-transfer/\n[talk-slides]: https://speakerdeck.com/hnarayanan/convolutional-neural-networks-for-artistic-style-transfer\n[support-issue]: https://github.com/hnarayanan/artistic-style-transfer/issues\n[twitter]: https://twitter.com/copingbear\n[linear-mnist]: notebooks/1_Linear_Image_Classifier.ipynb\n[neural-mnist-1]: notebooks/2_Neural_Network-based_Image_Classifier-1.ipynb\n[neural-mnist-2]: notebooks/3_Neural_Network-based_Image_Classifier-2.ipynb\n[convnet-mnist]: notebooks/4_Convolutional_Neural_Network-based_Image_Classifier.ipynb\n[vggnet-imagenet]: notebooks/5_VGG_Net_16_the_easy_way.ipynb\n[style-transfer]: notebooks/6_Artistic_style_transfer_with_a_repurposed_VGG_Net_16.ipynb\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhnarayanan%2Fartistic-style-transfer","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhnarayanan%2Fartistic-style-transfer","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhnarayanan%2Fartistic-style-transfer/lists"}