{"id":20976439,"url":"https://github.com/architgargpro/emotiondetector","last_synced_at":"2025-03-13T09:19:59.960Z","repository":{"id":147903494,"uuid":"204315368","full_name":"ArchitGargPro/EmotionDetector","owner":"ArchitGargPro","description":"This Machine Learning project aims to classify the emotion on a person's face into one of four categories, using deep convolutional neural networks.","archived":false,"fork":false,"pushed_at":"2019-08-25T15:53:50.000Z","size":8641,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-01-20T05:51:26.021Z","etag":null,"topics":["cnn-keras","deep-neural-networks","keras-tensorflow","machine-learning","python"],"latest_commit_sha":null,"homepage":"","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/ArchitGargPro.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":"2019-08-25T15:45:20.000Z","updated_at":"2019-08-25T15:56:10.000Z","dependencies_parsed_at":"2023-05-27T21:30:18.514Z","dependency_job_id":null,"html_url":"https://github.com/ArchitGargPro/EmotionDetector","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/ArchitGargPro%2FEmotionDetector","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ArchitGargPro%2FEmotionDetector/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ArchitGargPro%2FEmotionDetector/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ArchitGargPro%2FEmotionDetector/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ArchitGargPro","download_url":"https://codeload.github.com/ArchitGargPro/EmotionDetector/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243374739,"owners_count":20280730,"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-keras","deep-neural-networks","keras-tensorflow","machine-learning","python"],"created_at":"2024-11-19T04:53:54.655Z","updated_at":"2025-03-13T09:19:59.933Z","avatar_url":"https://github.com/ArchitGargPro.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Face and Emotion Detection\n\n## Introduction\nThis project aims to classify the emotion on a person's face into one of four categories, using deep convolutional neural networks. This repository is an implementation of [this](https://github.com/atulapra/Emotion-detection/blob/master/ResearchPaper.pdf) research paper and some help from [this](https://github.com/atulapra/Emotion-detection) GitHub repo. \n\n## Dataset\nThe model is trained on the FER-2013 dataset which was published on International Conference on Machine Learning (ICML) available [here](https://anonfile.com/bdj3tfoeba/data_zip). This dataset consists of 35887 grayscale, 48x48 sized face images with seven emotions - angry, disgusted, fearful, happy, neutral, sad and surprised.\n\n## Dependencies\n* Python 3.6\n* [OpenCV](https://opencv.org/)\n* [Tensorflow](https://www.tensorflow.org/)\n* [Keras.](https://keras.io/)\n\n## Usage\n* First clone or downlad this repository then enter the folder: 'cd emotionDetector'\n* Now, you can either use this pretrained modelby loading the weights or train your oun custom model:\n\tThe code is modified in order to use the pretrained model, to use the model use this command: 'python edModel.py'\n\n\tTo train your model, uncomment code at line 18-74 and place your dataset in data/train/ and data/test/ directories.\n\tThen use this command 'python edModel.py --mode train' to start training, then 'python edModel.py --mode display'\n\n## Algorithm\n* First, we use **haar cascade** to detect faces in each frame of the webcam feed.\n* The region of image containing the face is resized to **48x48** and is passed as input to the ConvNet.\n* The network outputs a list of **softmax scores** for the seven classes. (we have modified it to give result out of 4 emotions)\n* The emotion with maximum score is displayed on the screen.\n\n## References\n  \"Challenges in Representation Learning: A report on three machine learning contests.\" I Goodfellow, D Erhan, PL Carrier, A Courville, M Mirza, B\n   Hamner, W Cukierski, Y Tang, DH Lee, Y Zhou, C Ramaiah, F Feng, R Li,  \n   X Wang, D Athanasakis, J Shawe-Taylor, M Milakov, J Park, R Ionescu,\n   M Popescu, C Grozea, J Bergstra, J Xie, L Romaszko, B Xu, Z Chuang, and\n   Y. Bengio. arXiv 2013.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Farchitgargpro%2Femotiondetector","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Farchitgargpro%2Femotiondetector","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Farchitgargpro%2Femotiondetector/lists"}