ialhashim/DenseDepth
A deep learning implementation for estimating depth from single RGB images using transfer learning and encoder-decoder architecture.
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This repository provides a neural network implementation for monocular depth estimation, predicting depth maps from single RGB images. It uses an encoder-decoder architecture with transfer learning, supporting both Keras/TensorFlow and experimental PyTorch backends. The models are pre-trained on standard computer vision benchmarks including KITTI and NYU Depth V2 datasets.
Frequently asked
- What is ialhashim/DenseDepth?
- A deep learning implementation for estimating depth from single RGB images using transfer learning and encoder-decoder architecture.
- Is DenseDepth open source?
- Yes — ialhashim/DenseDepth is open source, released under the GPL-3.0 license.
- What language is DenseDepth written in?
- ialhashim/DenseDepth is primarily written in Jupyter Notebook.
- How popular is DenseDepth?
- ialhashim/DenseDepth has 1.6k stars on GitHub.
- Where can I find DenseDepth?
- ialhashim/DenseDepth is on GitHub at https://github.com/ialhashim/DenseDepth.