Identify and align faces in a given image
Replace faces in videos with new ones
Identify and mark facial landmarks in images
Gaze detection using Moondream
Mark faces in images and videos to show key landmarks
Mark attendance using face recognition
Detect and classify faces as real or fake
Swap faces in images and videos
Swap faces in images or videos
Find faces in real-time video stream
FaceOnLive On-Premise Solution
Detect faces in an image from a URL
Next generation image and video face swapper
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.
• 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.
Here’s a step-by-step guide to using the Atksh Onnx Facial Lmk Detector:
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.