{"id":19024484,"url":"https://github.com/danielstankw/vgg16_xray_image_classifier","last_synced_at":"2025-04-13T11:50:33.885Z","repository":{"id":200934027,"uuid":"706563815","full_name":"danielstankw/VGG16_Xray_Image_Classifier","owner":"danielstankw","description":"Image Classification (3 classes) using VGG-16 Deep Learning Model","archived":false,"fork":false,"pushed_at":"2023-10-18T08:15:02.000Z","size":2547,"stargazers_count":3,"open_issues_count":0,"forks_count":2,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-27T02:51:20.203Z","etag":null,"topics":["covid-19","image","image-classification","keras","tensorflow2","vgg16"],"latest_commit_sha":null,"homepage":"","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/danielstankw.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}},"created_at":"2023-10-18T07:42:42.000Z","updated_at":"2024-12-10T14:20:31.000Z","dependencies_parsed_at":null,"dependency_job_id":"d4fc618a-614d-4450-b6bd-74d079f97907","html_url":"https://github.com/danielstankw/VGG16_Xray_Image_Classifier","commit_stats":null,"previous_names":["danielstankw/xray-image-classifier","danielstankw/vgg16_xray_image_classifier"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/danielstankw%2FVGG16_Xray_Image_Classifier","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/danielstankw%2FVGG16_Xray_Image_Classifier/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/danielstankw%2FVGG16_Xray_Image_Classifier/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/danielstankw%2FVGG16_Xray_Image_Classifier/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/danielstankw","download_url":"https://codeload.github.com/danielstankw/VGG16_Xray_Image_Classifier/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248710435,"owners_count":21149188,"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":["covid-19","image","image-classification","keras","tensorflow2","vgg16"],"created_at":"2024-11-08T20:36:56.294Z","updated_at":"2025-04-13T11:50:33.864Z","avatar_url":"https://github.com/danielstankw.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Multiclass image classification (X-ray)\n\n## 1. Overview\nThis repositiory presents a very simple example of multiclass image classification.  \nThe problem objective was to learn to distinguish 3 classes related to lung state based on X-ray images.  The classes present in the dataset are: COVID-19, Viral Pneumonia, Normal.  \nFor this problem the Vgg16 pre-trained model was used, achieving promising results.\nThe dataset can be downloaded from [Kaggle](https://www.kaggle.com/datasets/pranavraikokte/covid19-image-dataset)\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"images/visual.png\" alt=\"Description of the Image\" width=\"1000\"/\u003e\n\u003c/p\u003e\n\n## 2. Model used\n\nThe used consists of VGG-16 pre-trained model with an addition of layers. The architecture overview is presented below: \n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"images/vgg16-image-classifier.png\" alt=\"Description of the Image\" width=\"400\"/\u003e\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"images/vgg.png\" alt=\"Description of the Image\" width=\"400\"/\u003e\n\u003c/p\u003e\n\n## 3. Training\nThe training/ validation loss is presented below:\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"images/graph1.png\" alt=\"Description of the Image\" width=\"400\"/\u003e\n\u003c/p\u003e\n\nThe training/ validation accuracy is presented below:\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"images/graph2.png\" alt=\"Description of the Image\" width=\"400\"/\u003e\n\u003c/p\u003e\n\n## 4. Results\nBecause the task is a classification task, accuracy is not the best metric for the task. \nTo analyze the performance of the model the confusion matrix is plotted. Based on the obtained results it is noted that only 2 instances were missclassified.\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"images/confusion.png\" alt=\"Description of the Image\" width=\"400\"/\u003e\n\u003c/p\u003e\n\nThe missclassified images are displayed below: \n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"images/missclass.png\" alt=\"Description of the Image\" width=\"800\"/\u003e\n\u003c/p\u003e\n\n\n## 5. Possible improvements\nTo further improve the results a few additions can be made:\n- Data augmentation such as scalling, rotation and more (*the code snippet is added to the notebook*)\n- Optimizing F1 score instead of accuracy (*the code snippet is added to the notebook*)\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdanielstankw%2Fvgg16_xray_image_classifier","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdanielstankw%2Fvgg16_xray_image_classifier","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdanielstankw%2Fvgg16_xray_image_classifier/lists"}