How to Estimate Depth from a Single Image

• fiftyone

  21 6,843 10.0 Python

  The open-source tool for building high-quality datasets and computer vision models

  

We will use the Hugging Face transformers and diffusers libraries for inference, FiftyOne for data management and visualization, and scikit-image for evaluation metrics.

• scikit-image

  10 5,902 9.7 Python

  Image processing in Python

  

We will use the Hugging Face transformers and diffusers libraries for inference, FiftyOne for data management and visualization, and scikit-image for evaluation metrics.

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• fast-depth

  2 892 0.0 Python

  ICRA 2019 "FastDepth: Fast Monocular Depth Estimation on Embedded Systems"

💡For this walkthrough, we will only use the NYU depth v2 portions. NYU depth v2 is permissively licensed for commercial use (MIT), and can be downloaded from Hugging Face directly.

• replicate-javascript

  7 420 8.9 JavaScript

  Node.js client for Replicate

  

In this section, we’ll show you how to generate MDE depth map predictions with both DPT and Marigold. In both cases, you can optionally run the model locally with the respective Hugging Face library, or run remotely with Replicate.

• DORN

  1 463 - Jupyter Notebook

For a long time, the state-of-the-art models for monocular depth estimation such as DORN and DenseDepth were built with convolutional neural networks. Recently, however, both transformer-based models such as DPT and GLPN, and diffusion-based models like Marigold have achieved remarkable results!

• DenseDepth

  5 1,533 0.0 Jupyter Notebook

  High Quality Monocular Depth Estimation via Transfer Learning

For a long time, the state-of-the-art models for monocular depth estimation such as DORN and DenseDepth were built with convolutional neural networks. Recently, however, both transformer-based models such as DPT and GLPN, and diffusion-based models like Marigold have achieved remarkable results!

• MiDaS

  27 4,159 2.4 Python

  Code for robust monocular depth estimation described in "Ranftl et. al., Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer, TPAMI 2022"

  

The checkpoint below uses MiDaS, which returns the inverse depth map, so we have to invert it back to get a comparable depth map.

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• Marigold

  4 1,759 8.7 Python

  [CVPR 2024 - Oral, Best Paper Candidate] Marigold: Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation

  

git clone https://github.com/prs-eth/Marigold.git

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