Skykai521/StickerCamera

This is an Android application with camera,picture cropping,collage sticking and tagging.贴纸标签相机,功能:拍照,相片裁剪,给图片贴贴纸,打标签。

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Skykai521/StickerCamera has 3k+ stars and 800+ forks on GitHub, is written in Java, and was last pushed on Jun 18, 2026. Data as of . Signed-in members get hourly updates — create a free account.

Summary Information

Updated 2 hours ago
Added to GitGenius on September 21st, 2026
Created on July 5th, 2015
Open Issues & Pull Requests: 46 (+0)
GitHub issues: Enabled
Number of forks: 847
Total Stargazers: 3,170 (+0)
Total Subscribers: 168 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 1204.0 days
Mean response time: 1204.0 days
90th percentile: 1204.0 days
Tracked items: 1

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Issue Activity (beta)

Open issues: 1
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 1,391 days
Stale 30+ days: 1
Stale 90+ days: 1

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

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Detailed Description

StickerCamera is an Android application that integrates camera capture, photo editing, and creative annotation features into a single tool.

The application addresses the need for a comprehensive photo editing experience on Android by combining multiple capabilities in one place. Users can capture photos directly through the camera, crop images to desired dimensions, apply filters for visual effects, and enhance photos with stickers and text tags. Stickers can be positioned freely, scaled, and rotated to suit the composition, while tags offer similar flexibility for adding text annotations. The completed edited images are saved locally for later access.

The project suits developers building Android photo editing applications or those seeking reference implementations for camera integration, image manipulation, and custom UI components. The codebase emphasizes custom views and architectural patterns, making it valuable for learning purposes. The application is available as a demo APK for evaluation.

Development activity shows ongoing engagement with the codebase through maintenance and refinement of the editing pipeline. The project incorporates multiple established libraries for core functionality, including GPU-accelerated image processing, universal image loading, and event-driven architecture, indicating a pragmatic approach to leveraging proven solutions rather than reimplementing standard features.