{"id":18745566,"url":"https://github.com/vpanjeta/meme-classifier","last_synced_at":"2025-10-23T16:26:52.303Z","repository":{"id":216017218,"uuid":"96275317","full_name":"VPanjeta/Meme-Classifier","owner":"VPanjeta","description":"Deep Learning model to predict the template of the given meme","archived":false,"fork":false,"pushed_at":"2017-07-05T07:52:15.000Z","size":79357,"stargazers_count":42,"open_issues_count":0,"forks_count":8,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-03-26T16:01:36.468Z","etag":null,"topics":["cnn","deep-learning","deep-neural-networks","meme-classifier","meme-templates","memes","neural-network","prediction","tensorflow"],"latest_commit_sha":null,"homepage":null,"language":"Python","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/VPanjeta.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}},"created_at":"2017-07-05T04:01:37.000Z","updated_at":"2024-02-13T16:21:20.000Z","dependencies_parsed_at":"2024-01-08T02:21:59.022Z","dependency_job_id":null,"html_url":"https://github.com/VPanjeta/Meme-Classifier","commit_stats":null,"previous_names":["vpanjeta/meme-classifier"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/VPanjeta%2FMeme-Classifier","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/VPanjeta%2FMeme-Classifier/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/VPanjeta%2FMeme-Classifier/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/VPanjeta%2FMeme-Classifier/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/VPanjeta","download_url":"https://codeload.github.com/VPanjeta/Meme-Classifier/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248636332,"owners_count":21137430,"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":["cnn","deep-learning","deep-neural-networks","meme-classifier","meme-templates","memes","neural-network","prediction","tensorflow"],"created_at":"2024-11-07T16:18:40.622Z","updated_at":"2025-10-23T16:26:52.219Z","avatar_url":"https://github.com/VPanjeta.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Meme-Classifier\n## A tensorflow project in python to classify given meme\n\nTraining done by replacing last layer of Inception model. \u003cbr/\u003e\nTraining has been done using very few images so the accuracy of prediction might be low in some meme templates. \u003cbr/\u003e\n\n## Supported Meme templates\n\n*evil kermit \u003cbr/\u003e\n*bad luck brian \u003cbr/\u003e\n*good guy greg \u003cbr/\u003e\n*the most interesting man in the world\u003cbr/\u003e\n*conspiracy keanu \u003cbr/\u003e\n*philosoraptor \u003cbr/\u003e\n*overly attached girlfriend \u003cbr/\u003e\n*doge \u003cbr/\u003e\n*one does not simply \u003cbr/\u003e\n*condescending wonka \u003cbr/\u003e\n*first world problems girl \u003cbr/\u003e\n*grumpy cat \u003cbr/\u003e\n*success kid \u003cbr/\u003e\n*ancient aliens guy \u003cbr/\u003e\n\n## Description\n\nTraining has been done by using InceptionV3 model and training the last layer using bottlenecks. \u003cbr/\u003e\nInstall dependencies using pip as `sudo pip install -r requirements.txt` \u003cbr/\u003e\nYou can run the program and find the prediction by using `python classify_meme.py path/to/meme.jpg` \u003cbr/\u003e\n\n## Using given test images\n1. cd into the directory.\n2. Then run `python classify_meme.py memes/meme1.jpg`\n3. The model will predict the normalised score as per the template of the meme (5 best results will be given)\n4. The results should be somewhat like this for the given meme:\n![evil_kermit](memes/meme1.jpg)\n\n```\nevil kermit                 : 0.97493\ncondescending wonka         : 0.00606\ndoge                        : 0.00417\ngood guy greg               : 0.00226\nsuccess kid                 : 0.00224\n```\n5. Test again by running `python classify_meme.py memes/meme2.jpg`\n6. The expected result for the given meme would be :\n![doge](memes/meme2.jpg)\n```\ndoge                        : 0.99790\ngood guy greg               : 0.00055\none does not simply         : 0.00037\ngrumpy cat                  : 0.00027\nconspiracy keanu            : 0.00014\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvpanjeta%2Fmeme-classifier","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fvpanjeta%2Fmeme-classifier","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvpanjeta%2Fmeme-classifier/lists"}