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Face Recognition
Atksh Onnx Facial Lmk Detector

Atksh Onnx Facial Lmk Detector

Identify and align faces in a given image

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What is Atksh Onnx Facial Lmk Detector ?

The Atksh Onnx Facial Lmk Detector is an efficient and lightweight toolkit designed for face recognition and facial landmark detection. It leverages the power of ONNX (Open Neural Network Exchange) to deliver high-performance face detection and alignment. The model is optimized for accuracy and speed, making it suitable for real-world applications in computer vision.

Features

• ONNX Compatibility: Optimized for ONNX, ensuring cross-platform compatibility and fast inference.
• Lightweight Design: Minimal resource requirements, enabling deployment on edge devices.
• High Accuracy: Robust detection of facial landmarks and face alignment in various conditions.
• Real-Time Processing: Capable of processing video and images in real-time.
• Multi-Language Support: Works seamlessly with popular programming languages like Python, C++, and more.

How to use Atksh Onnx Facial Lmk Detector ?

Here’s a step-by-step guide to using the Atksh Onnx Facial Lmk Detector:

  1. Install Dependencies: Ensure you have the necessary libraries installed, including ONNX runtime and OpenCV.
  2. Load the Model: Use the ONNX runtime to load the pre-trained model.
  3. Process Input: Read the input image or video frame using OpenCV.
  4. Run Detection: Feed the input to the model and obtain facial landmark predictions.
  5. Extract Landmarks: Parse the output to get the coordinates of facial landmarks.
  6. Visualize Results: Draw the landmarks on the image or video stream for visualization.

Frequently Asked Questions

What is ONNX and why is it used in this tool?
ONNX is an open format for representing trained machine learning models. It allows the model to be used across different frameworks and platforms, ensuring compatibility and performance.

Can this tool work on edge devices?
Yes, the Atksh Onnx Facial Lmk Detector is lightweight and optimized, making it suitable for deployment on edge devices with limited computational resources.

What input formats does this tool support?
The tool supports standard image formats like JPEG, PNG, and BMP, as well as video streams from cameras or files.

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