{"id":15650355,"url":"https://github.com/devamoghs/keras-style-transfer","last_synced_at":"2025-04-30T16:47:31.335Z","repository":{"id":40953799,"uuid":"173675213","full_name":"devAmoghS/Keras-Style-Transfer","owner":"devAmoghS","description":"An implementation of \"A Neural Algorithm of Artistic Style\" in Keras","archived":false,"fork":false,"pushed_at":"2023-02-10T23:09:41.000Z","size":3394,"stargazers_count":35,"open_issues_count":5,"forks_count":5,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-03-30T18:03:34.724Z","etag":null,"topics":["deep-learning","neural-networks","neural-style","neural-style-transfer","style-transfer"],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/devAmoghS.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","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":"2019-03-04T04:44:03.000Z","updated_at":"2024-10-28T12:17:12.000Z","dependencies_parsed_at":"2024-10-03T12:34:40.944Z","dependency_job_id":"3f991806-8fbe-4a8c-b647-2c2656b24063","html_url":"https://github.com/devAmoghS/Keras-Style-Transfer","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/devAmoghS%2FKeras-Style-Transfer","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/devAmoghS%2FKeras-Style-Transfer/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/devAmoghS%2FKeras-Style-Transfer/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/devAmoghS%2FKeras-Style-Transfer/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/devAmoghS","download_url":"https://codeload.github.com/devAmoghS/Keras-Style-Transfer/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":251747833,"owners_count":21637405,"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":["deep-learning","neural-networks","neural-style","neural-style-transfer","style-transfer"],"created_at":"2024-10-03T12:34:16.536Z","updated_at":"2025-04-30T16:47:31.306Z","avatar_url":"https://github.com/devAmoghS.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Keras-Style-Transfer (KeSTra)\nAn implementation of \"A Neural Algorithm of Artistic Style\" (http://arxiv.org/abs/1508.06576) in Keras\n\nThe code present in this repository is presented in this [blog](https://medium.com/@singhal.amogh1995/utilising-cnns-to-transform-your-model-into-a-budding-artist-1330dc392e25).\n\nThe code is written in Keras 2.2.2\n\n# Preview\nThis is a 5-sec gif of **Chicago city** painted in the style of **Rain Princess**\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"https://media.giphy.com/media/i4ElhKepMTcIZiqcma/giphy.gif\" width=\"480\" height=\"270\"/\u003e\n\u003c/p\u003e\n\n### Content Image and Style Image\n| Content Image  | Style Image  |\n|---|---|\n| \u003cimg align=\"left\" src=\"https://reiinakano.github.io/arbitrary-image-stylization-tfjs/images/chicago.jpg\" width=\"500\" height=\"270\" /\u003e  |   \u003cimg align=\"right\" src=\"https://afremov.com/images/product/RAIN-PRINCESS.jpg\" width=\"320\" height=\"270\" /\u003e |\n  \n\n## Installation notes\nKeSTra is built using Python 3.5.  The easiest way to set up a compatible\nenvironment is to use [Conda](https://conda.io/).  This will set up a virtual\nenvironment with the exact version of Python used for development along with all the\ndependencies needed to run KeSTra.\n\n1.  [Download and install Conda](https://conda.io/docs/download.html).\n2.  Create a Conda environment with Python 3. \n\n(**Note**: enter ```cd ~``` to go on **$HOME** , then perform these commands)\n\n    ```\n    conda create --name *your env name* python=3.5\n    ```\n   \n   You will get the following, kestra-test is the env name used in this example\n   \n   ```\n   Solving environment: done\n   \n## Package Plan ##\n\n  environment location: /home/user/anaconda3/envs/kestra-test\n\n  added / updated specs: \n    - python=3.5\n\n\nThe following NEW packages will be INSTALLED:\n\n    ca-certificates: 2018.12.5-0            \n    certifi:         2018.8.24-py35_1       \n    libedit:         3.1.20181209-hc058e9b_0\n    libffi:          3.2.1-hd88cf55_4       \n    libgcc-ng:       8.2.0-hdf63c60_1       \n    libstdcxx-ng:    8.2.0-hdf63c60_1       \n    ncurses:         6.1-he6710b0_1         \n    openssl:         1.0.2p-h14c3975_0      \n    pip:             10.0.1-py35_0          \n    python:          3.5.6-hc3d631a_0       \n    readline:        7.0-h7b6447c_5         \n    setuptools:      40.2.0-py35_0          \n    sqlite:          3.26.0-h7b6447c_0      \n    tk:              8.6.8-hbc83047_0       \n    wheel:           0.31.1-py35_0          \n    xz:              5.2.4-h14c3975_4       \n    zlib:            1.2.11-h7b6447c_3      \n\nProceed ([y]/n)?  *Press y*\n\nPreparing transaction: done\nVerifying transaction: done\nExecuting transaction: done\n#\n# To activate this environment, use:\n# \u003e source activate kestra-test\n#\n# To deactivate an active environment, use:\n# \u003e source deactivate\n#\n\n   ```\n   The environment is successfully created.\n\n3.  Now activate the Conda environment.\n\n    ```\n    source activate *your env name*\n    ```\n    You will get the following\n    \n    ```\n    (kestra-test) amogh@hp15X34:~$ \n    ```\n    Enter `conda list` to get the list of available packages\n    \n    ```\n        (kestra-test) amogh@hp15X34:~$ conda list\n    # packages in environment at /home/amogh/anaconda3/envs/mlwp-test:\n    #\n    # Name                    Version                   Build  Channel\n    ca-certificates           2018.12.5                     0  \n    certifi                   2018.8.24                py35_1  \n    libedit                   3.1.20181209         hc058e9b_0  \n    libffi                    3.2.1                hd88cf55_4  \n    libgcc-ng                 8.2.0                hdf63c60_1  \n    libstdcxx-ng              8.2.0                hdf63c60_1  \n    ncurses                   6.1                  he6710b0_1  \n    openssl                   1.0.2p               h14c3975_0  \n    pip                       10.0.1                   py35_0  \n    python                    3.5.6                hc3d631a_0  \n    readline                  7.0                  h7b6447c_5  \n    setuptools                40.2.0                   py35_0  \n    sqlite                    3.26.0               h7b6447c_0  \n    tk                        8.6.8                hbc83047_0  \n    wheel                     0.31.1                   py35_0  \n    xz                        5.2.4                h14c3975_4  \n    zlib                      1.2.11               h7b6447c_3 \n    ```\n\n4.  Install the required dependencies.\n\n    ```\n    (kestra-test) amogh@hp15X34:~$ conda install --yes --file *path to requirements.txt*\n    ```\n    \n5. In case you are not able to install the packages or getting `PackagesNotFoundError`\nUse the following command ` conda install -c conda-forge *list of packages separated by space*`.\n\n## How good is the code ?\n* It is well tested\n* It passes style checks (PEP8 compliant)\n* It can compile in its current state (and there are relatively no issues)\n\n## How much support is available?\n* FAQs (coming soon)\n* Documentation (coming soon)\n\n## Issues\nFeel free to submit issues and enhancement requests.\n\n## Contributing\nPlease refer to each project's style guidelines and guidelines for submitting patches and additions. In general, we follow the \"fork-and-pull\" Git workflow.\n\n 1. **Fork** the repo on GitHub\n 2. **Clone** the project to your own machine\n 3. **Commit** changes to your own branch\n 4. **Push** your work back up to your fork\n 5. Submit a **Pull request** so that we can review your changes\n\nNOTE: Be sure to merge the latest from \"upstream\" before making a pull request!\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdevamoghs%2Fkeras-style-transfer","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdevamoghs%2Fkeras-style-transfer","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdevamoghs%2Fkeras-style-transfer/lists"}