Easy mobile app - Face Detection App
Budget: ₹1,500 – ₹12,500 INR
I need a lightweight mobile application that can automatically locate faces in both photos and live video, running smoothly on iOS and Android.
The core detector must be YOLO; however, you’re free to combine it with OpenCV or MediaPipe for preprocessing or post-processing as long as overall inference stays fast on mid-range devices.
The front end can be built in Flutter or React Native—whichever lets you reach 60 fps video preview without draining the battery. A minimal, clean UI is enough: pick an image from the gallery, record or stream video, and immediately see bounding boxes appear in real time.
You will train or fine-tune the model yourself, document the training pipeline, and include the final weights in the repo. Optimisation for size and speed (quantisation, pruning, Core ML / NNAPI delegates, etc.) is important, and I’ll want to review your benchmarks. We’re aiming to wrap this up within a month, so please factor that into your plan.
Deliverables
• Fully functional app for iOS & Android
• Complete source code with clear commit history
• Reproducible model-training scripts and final trained weights
• Installation / build guide and basic user documentation
• Short demo video showing face detection on device
I’ll test by building from scratch and running the demo scenarios; acceptance is based on accurate face detection, real-time performance, and the documentation’s clarity.
The core detector must be YOLO; however, you’re free to combine it with OpenCV or MediaPipe for preprocessing or post-processing as long as overall inference stays fast on mid-range devices.
The front end can be built in Flutter or React Native—whichever lets you reach 60 fps video preview without draining the battery. A minimal, clean UI is enough: pick an image from the gallery, record or stream video, and immediately see bounding boxes appear in real time.
You will train or fine-tune the model yourself, document the training pipeline, and include the final weights in the repo. Optimisation for size and speed (quantisation, pruning, Core ML / NNAPI delegates, etc.) is important, and I’ll want to review your benchmarks. We’re aiming to wrap this up within a month, so please factor that into your plan.
Deliverables
• Fully functional app for iOS & Android
• Complete source code with clear commit history
• Reproducible model-training scripts and final trained weights
• Installation / build guide and basic user documentation
• Short demo video showing face detection on device
I’ll test by building from scratch and running the demo scenarios; acceptance is based on accurate face detection, real-time performance, and the documentation’s clarity.
Related categories:
JavaScript
Mobile App Development
Android
OpenCV
iOS Development
React Native
Flutter
Computer Vision
Deep Learning
YOLO