create 3d-gltf face-mesh from image with mediapipe
Turn 2D images into 3D models
Generate 3D models from images
Generate 3D recursive polygons and math functions
Display 3D food models
Generate 3D scenes with dynamic lighting and shapes
Generate 3D models of various objects
Transform images into 3D depth models
Create 3D models and videos from images
Create a 3D model from an image in 10 seconds!
Create an interactive GTA-style city with collisions and NPC dialogue
Generate 3D molecular models from SMILES strings
Create 3D scenes with recursive polygons and math functions
Mediapipe Face Mesh 3D is a powerful tool that enables the creation of 3D GL Transmission Format (GLTF) face meshes from 2D images. It leverages MediaPipe's robust framework to analyze facial features and generate accurate 3D representations. This technology is particularly useful for applications in augmented reality (AR), 3D modeling, and facial animation.
pip install mediapipe
import mediapipe as mp
import cv2
mp_face_mesh = mp.solutions.face_mesh
face_mesh = mp_face_mesh.FaceMesh(max_num_faces=1)
image = cv2.cvtColor(cv2.imread("input_image.jpg"), cv2.COLOR_BGR2RGB)
results = face_mesh.process(image)
Can MediaPipe Face Mesh 3D work with live video?
Yes, MediaPipe Face Mesh 3D can process live video streams in real-time, making it suitable for AR and interactive applications.
What kind of input images does MediaPipe Face Mesh 3D support?
It supports standard image formats like JPEG, PNG, and BMP. The image should contain a clear view of the face for optimal results.
Can I customize the 3D mesh output?
Yes, the output mesh can be customized using external 3D modeling tools. MediaPipe provides the base mesh, which can be further refined or modified as needed.