nn VS ZoeDepth

Compare nn vs ZoeDepth and see what are their differences.

nn

🧑‍🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠 (by lab-ml)
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nn ZoeDepth
26 4
48,004 1,939
8.5% 9.4%
7.7 2.5
about 1 month ago 6 months ago
Jupyter Notebook Jupyter Notebook
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

nn

Posts with mentions or reviews of nn. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-01-09.

ZoeDepth

Posts with mentions or reviews of ZoeDepth. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-04-27.

What are some alternatives?

When comparing nn and ZoeDepth you can also consider the following projects:

GFPGAN-for-Video-SR - A colab notebook for video super resolution using GFPGAN

DenseDepth - High Quality Monocular Depth Estimation via Transfer Learning

labml - 🔎 Monitor deep learning model training and hardware usage from your mobile phone 📱

Online3DViewer - A solution to visualize and explore 3D models in your browser.

functorch - functorch is JAX-like composable function transforms for PyTorch.

Depth-Anything - [CVPR 2024] Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data. Foundation Model for Monocular Depth Estimation

onnx-simplifier - Simplify your onnx model

monodepth2 - [ICCV 2019] Monocular depth estimation from a single image

Basic-UI-for-GPT-J-6B-with-low-vram - A repository to run gpt-j-6b on low vram machines (4.2 gb minimum vram for 2000 token context, 3.5 gb for 1000 token context). Model loading takes 12gb free ram.

HugsVision - HugsVision is a easy to use huggingface wrapper for state-of-the-art computer vision

Behavior-Sequence-Transformer-Pytorch - This is a pytorch implementation for the BST model from Alibaba https://arxiv.org/pdf/1905.06874.pdf

AdaBins - Official implementation of Adabins: Depth Estimation using adaptive bins