face recognition component for a React Native mobile application
Budget: $250 – $750 USD
We are looking for the development of a **face recognition component for a React Native mobile application** that works completely on-device. The scope of this project is limited strictly to face detection, embedding generation, and matching functionality.
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## **Functional Requirements**
The component must:
* Accept **reference images/selfies** and:
* Detect faces within each image
* Generate and return facial embeddings for each detected face
* Accept **media inputs (images and videos)** and:
* Detect faces in images
* For videos, process selected frames (e.g., initial or sampled frames) to detect faces
* Generate embeddings for all detected faces
* Provide **face matching functionality**:
* Compare embeddings from media inputs against stored reference embeddings
* Return match results with confidence scores
* Be implemented as a **modular, reusable component/service** that can be integrated into an existing React Native app
* Operate **fully within the React Native ecosystem**:
* Can use native modules (iOS/Android) if required
* Should expose a clean JavaScript/TypeScript interface
* Handle real-world conditions:
* Variations in lighting, pose, and image quality
* Similar-looking individuals (e.g. cast members of a crew)
* Family Members (e.g., siblings)
---
## **Performance Requirements**
* Face detection, embedding generation, and matching should target:
* **≤ 500 ms per operation** (depending on device capabilities)
* Accuracy target:
* **≥ 95% under typical usage conditions**
---
## **Technical Requirements**
* Must use **open-source libraries** that are:
* Free for commercial use
* The solution should:
* Be optimized for **mobile performance (iOS and Android)**
* Minimize memory and battery usage
* Work efficiently on mid-range devices
* Preferred (but not mandatory):
* Experience with libraries like TensorFlow Lite, ONNX, or similar mobile ML runtimes
* Models that can be further extended to work seamlessly across both browser and mobile platforms developed using react.
---
## **Deliverables**
* React Native-compatible **face recognition module**
* Native bridge (if applicable) for iOS and Android
* Clean API for:
* Face detection
* Embedding generation
* Face matching
* Documentation including:
* Setup instructions
* Example usage
---
## **Intellectual Property**
* All deliverables will become the exclusive property of us.
* The developer/vendor may not reuse or redistribute the solution
---
---
## **Functional Requirements**
The component must:
* Accept **reference images/selfies** and:
* Detect faces within each image
* Generate and return facial embeddings for each detected face
* Accept **media inputs (images and videos)** and:
* Detect faces in images
* For videos, process selected frames (e.g., initial or sampled frames) to detect faces
* Generate embeddings for all detected faces
* Provide **face matching functionality**:
* Compare embeddings from media inputs against stored reference embeddings
* Return match results with confidence scores
* Be implemented as a **modular, reusable component/service** that can be integrated into an existing React Native app
* Operate **fully within the React Native ecosystem**:
* Can use native modules (iOS/Android) if required
* Should expose a clean JavaScript/TypeScript interface
* Handle real-world conditions:
* Variations in lighting, pose, and image quality
* Similar-looking individuals (e.g. cast members of a crew)
* Family Members (e.g., siblings)
---
## **Performance Requirements**
* Face detection, embedding generation, and matching should target:
* **≤ 500 ms per operation** (depending on device capabilities)
* Accuracy target:
* **≥ 95% under typical usage conditions**
---
## **Technical Requirements**
* Must use **open-source libraries** that are:
* Free for commercial use
* The solution should:
* Be optimized for **mobile performance (iOS and Android)**
* Minimize memory and battery usage
* Work efficiently on mid-range devices
* Preferred (but not mandatory):
* Experience with libraries like TensorFlow Lite, ONNX, or similar mobile ML runtimes
* Models that can be further extended to work seamlessly across both browser and mobile platforms developed using react.
---
## **Deliverables**
* React Native-compatible **face recognition module**
* Native bridge (if applicable) for iOS and Android
* Clean API for:
* Face detection
* Embedding generation
* Face matching
* Documentation including:
* Setup instructions
* Example usage
---
## **Intellectual Property**
* All deliverables will become the exclusive property of us.
* The developer/vendor may not reuse or redistribute the solution
---