{"id":19188758,"url":"https://github.com/miquido/ar_quido","last_synced_at":"2025-05-08T02:47:05.686Z","repository":{"id":117382918,"uuid":"608512391","full_name":"miquido/AR_quido","owner":"miquido","description":"Flutter mobile plugin for image recognition using Augmented Reality (AR) features","archived":false,"fork":false,"pushed_at":"2024-08-08T12:45:33.000Z","size":20087,"stargazers_count":9,"open_issues_count":4,"forks_count":3,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-04-20T06:35:00.377Z","etag":null,"topics":["augmented-reality","flutter","image-recognition"],"latest_commit_sha":null,"homepage":"https://miquido.com","language":"Kotlin","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/miquido.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.md","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":"2023-03-02T07:01:52.000Z","updated_at":"2024-09-01T14:11:46.000Z","dependencies_parsed_at":"2023-10-05T01:59:35.170Z","dependency_job_id":"4160b7de-38b1-43c9-94c9-799a42c91a44","html_url":"https://github.com/miquido/AR_quido","commit_stats":null,"previous_names":[],"tags_count":8,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/miquido%2FAR_quido","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/miquido%2FAR_quido/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/miquido%2FAR_quido/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/miquido%2FAR_quido/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/miquido","download_url":"https://codeload.github.com/miquido/AR_quido/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":252989940,"owners_count":21836665,"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":["augmented-reality","flutter","image-recognition"],"created_at":"2024-11-09T11:25:56.543Z","updated_at":"2025-05-08T02:47:05.655Z","avatar_url":"https://github.com/miquido.png","language":"Kotlin","funding_links":[],"categories":[],"sub_categories":[],"readme":"_Ahoy, me hearties! Set sail on the high seas of image recognition with our Flutter plugin. Arrr! 🦜_\n\n# 🏴‍☠️ ar_quido 🏴‍☠️\n\nImage recognition using Augmented Reality (AR) features for mobile Flutter apps.\nIt uses [EasyAR Sense](https://www.easyar.com/view/sdk.html) on Android and native\n[ARKit](https://developer.apple.com/documentation/arkit/content_anchors/detecting_images_in_an_ar_experience)\non iOS.\n\nThe plugin has been built by Flutter Division at [Miquido Software development company](https://www.miquido.com).\n\n## Getting started 🚢\n\nAdd the dependency in your `pubspec.yaml`:\n\n- from command line:\n\n  ```bash\n  flutter pub add ar_quido\n  flutter pub get\n  ```\n\n- directly in pubspec.yaml:\n\n  ```yaml\n  dependencies:\n     ar_quido: 0.2.0\n  ```\n\n### Android\n\nSince the Android version depends on the EasyAR solution, you need to\n[sign up](https://www.easyar.com/view/signUp.html) on their page and obtain\na \"Sense Authorization\" License Key. It can be done through the [EasyAR Dashboard](https://portal.easyar.com/sdk/list).\n\nAfter doing so, provide the key in Android Manifest file as\n`application`'s metadata:\n\n```xml\n\u003cmeta-data\n           android:name=\"com.miquido.ar_quido.API_KEY\"\n           android:value=\"\u003cYOUR_SENSE_LICENSE_KEY\u003e\" /\u003e\n```\n\n#### Proguard\n\nBy default, proguard removes the EasyAR library files from a release build. To fix\nthis, add the following code to the `android/app/src/proguard-rules.pro` file (create\nthe file if it doesn't exist):\n\n```proguard\n-keep class cn.easyar.** { *; }\n-keepattributes SourceFile,LineNumberTable\n-keep public class * extends java.lang.Exception\n```\n\n### iOS\n\n`ARKit` uses the device camera, so do not forget to provide the `NSCameraUsageDescription`\nin Info.plist:\n\n```xml\n\u003ckey\u003eNSCameraUsageDescription\u003c/key\u003e\n\u003cstring\u003eDescribe why your app needs camera (AR) here.\u003c/string\u003e\n```\n\nAlso make sure, that your deployment target in project settings is set to at least 14.0.\nSet the same version in `ios/Podfile`:\n\n```ruby\nplatform :ios, '15.0'\n```\n\n## Usage 🌴\n\n1. Put your reference images inside `assets/reference_images` directory (make\nsure to reference them in `pubspec.yaml`).\n    - please note, that only `.jpg` images are supported at this time\n2. Place `ARQuidoView` widget in your view's code. Provide at least an array of\nimage names you want to detect (through `referenceImageNames` property) and a\ncallback for detected images (through `onImageDetected` property):\n\n   ```dart\n    ARQuidoView(\n      referenceImageNames: const ['applandroid'],\n      onImageDetected: (imageName) {\n        // handle detected image\n      },\n    ),\n   ```\n\n3. That's it, you're all set ⚓\n\nPlease see the [example](https://github.com/miquido/AR_quido/tree/main/example)\nfor more info. You can also check the details in [API Documentation](https://pub.dev/documentation/ar_quido/latest/).\n\n## Disclaimer\n\n\"EasyAR\" is the registered trademark or trademark of VisionStar Information\nTechnology (Shanghai) Co., Ltd in China and other countries for the augmented\nreality technology developed by VisionStar Information Technology (Shanghai) Co., Ltd.\n\nThe copyright notices in the Software and this entire statement, including the above\nlicense grant, this restriction and the following disclaimer, must be included\nin all copies of the Software, in whole or in part, and all derivative works\nof the Software.\n\n---\n#### About Miquido\n\n- [About](https://careers.miquido.com/about-us/)\n- [Careers](https://careers.miquido.com/job-offers/)\n- [Internship at Miquido](https://careers.miquido.com/students/)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmiquido%2Far_quido","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmiquido%2Far_quido","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmiquido%2Far_quido/lists"}