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Looking for an experienced Android Java developer to build a complete app for an AR glasses device. The device connects to an Android phone via USB-C. The app must: — Open a live USB UVC camera feed fullscreen on the glasses display — Apply real-time zoom from 1x to 10x with sharpness maintained — Apply real-time contrast enhancement — Apply real-time brightness adjustment — Apply edge detection outline mode — Apply colour filter modes — Read visible text aloud using OCR and text to speech — Simple on-screen menu to switch between features — Maintain minimum 30 FPS at all times SDKs provided: — [login to view URL] — USB camera, zoom, image effects (Java API over C/C++ native libraries) — [login to view URL] — glasses communication and display control (Java API over C/C++ native libraries) — [login to view URL] — USB audio output for text to speech (Java API over C/C++ native libraries) All SDKs are Java based. Developer must be comfortable with Java Android development and JNI-based library integration. Deliverables: working APK, GitHub link with clean code, screen recording showing all features. Language: Java (Android). Timeline: open to discussion based on experience.
Project ID: 40376672
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Active 7 days ago
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11 freelancers are bidding on average ₹111,636 INR for this job

Hi there, I will build your AR glasses app — live UVC camera feed, real-time zoom with sharpness, contrast/brightness adjustments, edge detection, color filters, and OCR-to-speech — all targeting 30+ FPS on the glasses display. For maintaining frame rate during image processing, I will pipeline the effects using a dedicated render thread with OpenGL ES shaders so zoom, contrast, and edge detection run on the GPU rather than CPU — keeping latency low even at 10x zoom. Questions: 1) Which AR glasses model are you using — this affects display resolution and refresh rate targets? 2) For OCR, should text-to-speech activate automatically on detected text or only on user trigger? Ready to start whenever you are. Kamran
₹24,746 INR in 10 days
7.5
7.5

As an experienced Mobile and Web Application Developer with a profound mastery of Android App Development, Java, and C++ Programming, I am more than prepared to skillfully handle your project. Over the years, I have established a notable reputation for building high-quality, scalable, Android applications. The specific skills you require like webcam integration via USB-C, real-time contrast adjustments, brightness control, and OCR/text-to-speech implementations using Java APIs will be effortlessly achieved since they are core aspects of my competencies. In addition to the above-highlighted features of your project description, I have further expertise in dealing with challenging scenarios which might arise throughout the task. Considering JNI-based library integrations are pivotal to your project success, my extensive experience working with similar technologies and libraries will ensure a seamless implementation void of glitches. Moreover, as an avid adopter of clean code practices—I pledge to furnish you with deliverables that also include a Github link with well-documented code—a great asset should modifications be necessary in future. To put it succinctly, choosing me for this project guarantees you a consummately qualified professional who is fluent in the required Java-based SDKs as well as other correlated programming languages. The ability to deliver reliable and high-quality solutions that répondent to business goals is among my leading suits as a developer.
₹25,000 INR in 3 days
7.0
7.0

Hello, your AR glasses brief lines up with several Android-native camera and CV projects I have shipped over the last 18 months. For the USB-C connected UVC feed I will use the Android UVCCamera library (saki-io or libusb backed) rather than CameraX, since stock CameraX does not enumerate external UVC devices reliably across OEMs. For the fullscreen render I will use TextureView with a YUV to RGB shader so we avoid the dropped frames that come from a naive ImageView pipe. Real-time zoom one to ten x will be done on the GPU using a fragment shader scaled around the centre point and sharpness preserved with a Lanczos kernel, not bilinear. Contrast will use a CLAHE lookup table so we do not crush shadows at higher values. For the OCR and recognition module I will integrate ML Kit text recognition with an optional on-device Tesseract fallback for low-light text, and wire up haptic feedback via the HapticFeedbackConstants API. The build will target Android 10+ with a fallback for Android 8. I can have a working UVC preview and zoom within week one and ship a signed APK in 25 days. Aditya, Webneco Infotech.
₹23,250 INR in 25 days
3.2
3.2

Patna, India
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Member since Jul 6, 2025
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