Dpt Hybrid Midas
Hybrid depth estimation model developed by Intel, combining the advantages of convolutional neural networks and Transformer architecture
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Release Time : 11/11/2023
Model Overview
DPT-Hybrid-MiDaS is a deep learning model for monocular depth estimation, capable of predicting depth maps from a single RGB image. The model combines the local feature extraction capability of CNNs with the global context understanding of Transformers.
Model Features
Hybrid Architecture
Combines the strengths of CNNs and Transformers to capture both local details and global context
High-Precision Depth Estimation
Capable of generating accurate depth maps from a single RGB image
Web Compatibility
Provides ONNX format weights for easy deployment in web environments
Model Capabilities
Monocular Depth Estimation
3D Scene Understanding
Image Depth Analysis
Use Cases
Computer Vision
Augmented Reality
Provides scene depth information for AR applications
Enables more realistic virtual object placement and occlusion effects
Robotic Navigation
Helps robots understand the 3D structure of the environment
Improves path planning and obstacle avoidance capabilities
Photography
Depth-of-Field Simulation
Adjusts post-processing depth-of-field effects based on depth maps
Creates professional-level bokeh effects
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