Run 3D human pose estimation with images
streamlit application to for ANPR/ALPR
Extract image sections by description
Detect lines in images using a transformer-based model
Compute normals for images and videos
Tag images with labels
Apply artistic style to your photos
Segment body parts in images
Try CANVAS-S in this huggingface space
Swap faces in images
Highlight objects in images using text prompts
https://huggingface.co/spaces/VIDraft/mouse-webgen
Rate quality of image edits based on instructions
GVHMR is an AI tool designed to run 3D human pose estimation with images. It leverages advanced computer vision techniques to analyze and predict the three-dimensional pose of a human body from a given two-dimensional image. This technology is particularly useful for applications like fitness tracking, healthcare, and animation, where understanding human movement and posture is essential.
• 3D Pose Estimation: Accurately estimates the 3D coordinates of body joints from 2D images.
• High Precision: Delivers precise results for human pose detection in various scenarios.
• Image Compatibility: Works with multiple image formats, including RGB and depth images.
• Flexibility: Can be integrated into various applications, such as fitness trackers, video games, and medical tools.
• User-Friendly Interface: Offers an intuitive way to process and visualize results.
• Real-Time Processing: Enables quick estimation for live or streaming data.
1. What formats does GVHMR support?
GVHMR supports common image formats like PNG, JPG, and BMP. It can also process depth images if available.
2. Can GVHMR work with low-quality images?
Yes, but the accuracy may vary depending on the image quality. For best results, use clear, well-lit images.
3. Is GVHMR suitable for real-time applications?
Yes, GVHMR is optimized for real-time processing, making it ideal for live demonstrations, fitness tracking, or interactive applications.