{"id":20810626,"url":"https://github.com/vivekcode101/mlimagepipeline","last_synced_at":"2026-04-21T17:31:54.915Z","repository":{"id":240646959,"uuid":"803202747","full_name":"vivekcode101/mlimagepipeline","owner":"vivekcode101","description":null,"archived":false,"fork":false,"pushed_at":"2024-05-21T18:06:48.000Z","size":486,"stargazers_count":0,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-01-18T14:32:57.283Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"JavaScript","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/vivekcode101.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":"2024-05-20T09:16:21.000Z","updated_at":"2024-05-21T18:06:51.000Z","dependencies_parsed_at":null,"dependency_job_id":"fc02c528-4e6c-4687-8c7d-65be6c4c6ad2","html_url":"https://github.com/vivekcode101/mlimagepipeline","commit_stats":null,"previous_names":["vivekcode101/mlimagepipeline"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vivekcode101%2Fmlimagepipeline","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vivekcode101%2Fmlimagepipeline/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vivekcode101%2Fmlimagepipeline/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vivekcode101%2Fmlimagepipeline/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/vivekcode101","download_url":"https://codeload.github.com/vivekcode101/mlimagepipeline/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243158872,"owners_count":20245663,"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":[],"created_at":"2024-11-17T20:26:32.198Z","updated_at":"2026-04-21T17:31:49.877Z","avatar_url":"https://github.com/vivekcode101.png","language":"JavaScript","funding_links":[],"categories":[],"sub_categories":[],"readme":"# AI Model Project\n\nThis project contains an AI model implemented in Python. It provides a simple API with two endpoints: one for returning a \"Hello World\" message and another for processing an image and returning information about it.\n\n![Sample](asset/image.png)\n\n\n\n## Table of Contents\n\n- [Installation](#installation)\n- [Usage](#usage)\n- [API Endpoints](#api-endpoints)\n- [Docker](#docker)\n- [Contributing](#contributing)\n- [License](#license)\n\n## Installation\n\nTo run this project, you need to have Docker installed on your machine. Follow these steps to set up and run the project:\n\nFor backend\n\n1. Clone the repository:\n    ```sh\n    git clone https://github.com/vivekcode101/mlimagepipeline\n    cd mlimagepipeline/backend\n    ```\n2. Building the Docker Image\n\n```sh\ndocker build -t ai-model -f model.dockerfile .\n```\n3. Procfile\nProcfile is also provided to assign web commands.\n\n## Usage\n\nOnce the Docker container is running, the API will be available at `http://localhost:8000`.\n\n## API Endpoints\n\n### GET /\n\n- **Description**: Returns a \"Hello World\" message.\n- **URL**: `/`\n- **Method**: `GET`\n- **Response**:\n    ```json\n    {\n        \"message\": \"Hello World\"\n    }\n    ```\n\n### POST /process\n\n- **Description**: Processes an image and returns information about it.\n- **URL**: `/process`\n- **Method**: `POST`\n- **Parameters**:\n    - `text` (query parameter): A string parameter required in the query.\n    - `image` (form-data multipart): An image file uploaded as form-data.\n- **Response**: JSON object containing information about the image.\n- **Example cURL request**:\n    ```sh\n    curl -X POST http://localhost:8000/process \\\n    -F \"text=your_query_string\" \\\n    -F \"image=@path_to_your_image_file\"\n    ```\n\n## Docker Running the Docker Container\n\n```sh\ndocker run -it -p 8000:8000 ai-model\n```\nFor frontend\n\n1.You should have npm installed in your local machine\n\n2.Run npm install in the vqa-frontend folder to install all the dependencies\n\n```sh\nnpm i\n```\n3. Run the frontend\n\n```sh\nnpm start\n```\n\n\n\nContributing\nContributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.\n\nLicense\nThis project is licensed under the MIT License. See the LICENSE file for details.\n\nThis project includes a `Dockerfile` to simplify the setup and deployment process. Using Docker ensures a consistent environment for running the project.\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvivekcode101%2Fmlimagepipeline","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fvivekcode101%2Fmlimagepipeline","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvivekcode101%2Fmlimagepipeline/lists"}