{"id":18602144,"url":"https://github.com/build-on-aws/building-a-machine-learning-enabled-web-app","last_synced_at":"2025-04-10T19:31:02.905Z","repository":{"id":204722008,"uuid":"645537888","full_name":"build-on-aws/building-a-machine-learning-enabled-web-app","owner":"build-on-aws","description":"This repository contains sample app code to build an object and text detection web app. An individual can upload images that contains real world objects or text, and get the labels for all the detected objects and texts in the image.","archived":false,"fork":false,"pushed_at":"2024-07-11T17:45:28.000Z","size":74208,"stargazers_count":16,"open_issues_count":3,"forks_count":16,"subscribers_count":53,"default_branch":"main","last_synced_at":"2025-03-25T03:12:35.719Z","etag":null,"topics":["amazon-rekognition","aws"],"latest_commit_sha":null,"homepage":"","language":"Vue","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit-0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/build-on-aws.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":"CODE_OF_CONDUCT.md","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":"2023-05-25T22:10:19.000Z","updated_at":"2024-09-25T15:06:22.000Z","dependencies_parsed_at":"2023-11-21T17:41:43.174Z","dependency_job_id":null,"html_url":"https://github.com/build-on-aws/building-a-machine-learning-enabled-web-app","commit_stats":null,"previous_names":["build-on-aws/building-a-machine-learning-enabled-web-app"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/build-on-aws%2Fbuilding-a-machine-learning-enabled-web-app","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/build-on-aws%2Fbuilding-a-machine-learning-enabled-web-app/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/build-on-aws%2Fbuilding-a-machine-learning-enabled-web-app/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/build-on-aws%2Fbuilding-a-machine-learning-enabled-web-app/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/build-on-aws","download_url":"https://codeload.github.com/build-on-aws/building-a-machine-learning-enabled-web-app/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248281395,"owners_count":21077423,"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":["amazon-rekognition","aws"],"created_at":"2024-11-07T02:10:29.254Z","updated_at":"2025-04-10T19:30:57.892Z","avatar_url":"https://github.com/build-on-aws.png","language":"Vue","funding_links":[],"categories":[],"sub_categories":[],"readme":"## Building a Machine Learning-Enabled Web App: AcadeML\n\nThis repo contains app code to accompany AWS Workshop Studio [Building a Machine Learning-Enabled Web App](https://studio.us-east-1.prod.workshops.aws/workshops/b0b09da3-8c15-4c6a-aaf1-c265fe6e595d).  \nAs this is a standalone repo, it can be used without AWS Workshop Studio.\n\nThere are currently 2 labs in the workshop:\n1. Lab 1: Adding **Amazon Rekognition** to an existing web app\n2. Lab 2: Adding **Amazon Textract** to an existing web app\n\n### Audience\nThis is a foundational repo aimed at students learning how to call ML APIs and interpret JSON returned for the first time.\n\n### Technology and Services\nThe app stack:\n* Node.js, Javascript, AWS SDK V3 (Javascript)\n* Vue.js, Vuetify.js, and Vite\n\n### Prerequisites\nThe following software is required:\n1. [Node.js](https://nodejs.org/en/download)\n1. The app requires an AWS account to run:\n    1. If you are attending an AWS Workshop event, this is supplied to you. \n    1. If you are using this repo outside of an hosted Workshop event, you will need to supply your own AWS account: [Create](https://aws.amazon.com/resources/create-account/) a new account or [sign in](https://aws.amazon.com/console/) to your existing account.\n\n\u003e Warning: The repo calls AWS services, which incur a cost. While briefly running the app as a learning exercise would only incur a relatively small cost, care should be taken to monitor spend and delete AWS resources and associated services when no longer needed to ensure future charges do not accrue.  \n\n### Branches\nThere are 2 branches in this repo; `start-lab` and `complete-lab`.  \nThe `start-lab` branch contains the web app *without* the code for calling ML APIs.  \nThe steps to add this code are in the workshop referenced above.  \nThe `complete-lab` branch contains the final code the student would have at the end of the lab.  \n\n### Installation\n1. Clone the `start-lab` (or `complete-lab` if not attempting the workshop) branch into a new folder:\n    1. `git clone --single-branch --branch start-lab https://github.com/build-on-aws/building-a-machine-learning-enabled-web-app`\n1. In the repo root folder run: `npm install`    \n\n### AWS Credentials\nIf you are attending a hosted workshop, an AWS account with an IAM user with the correct permissions will be supplied to you.  \nIf attempting to run this independently, you will need to supply your own AWS account.  \n\nIn the AWS Console:\n1. Create an IAM user with policies **AmazonRekognitionFullAccess** and **AmazonTextractFullAccess** attached.\n1. Create an access key and secret access key (copy these before navigating away from the page)\n1. Create a file in the **root** folder of the app called `.env.local` (note the `.` before the word `env`).\n1. Add the following lines to `.env.local`:\n* VITE_AWS_ACCESS_KEY_ID=AccessKeyFromStep2\n* VITE_AWS_SECRET_ACCESS_KEY=SecretAccessKeyFromStep2\n* VITE_AWS_REGION=us-east-1\n\n### Running\n1. In the repo root folder run  **npm run dev**\n1. Open the localhost website (http://localhost:3000 is the default)\n\n### Clean-up (non-Workshop Studio users)\nDelete the AWS IAM user that was created by the installation steps above when you no longer need this app.\n\n## Security\nSee [CONTRIBUTING](CONTRIBUTING.md#security-issue-notifications) for more information.\n\n## License\nThis library is licensed under the MIT-0 License. See the LICENSE file.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbuild-on-aws%2Fbuilding-a-machine-learning-enabled-web-app","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbuild-on-aws%2Fbuilding-a-machine-learning-enabled-web-app","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbuild-on-aws%2Fbuilding-a-machine-learning-enabled-web-app/lists"}