Swin-Transformer-Serve VS merged_depth

Compare Swin-Transformer-Serve vs merged_depth and see what are their differences.

Swin-Transformer-Serve

Deploy Swin Transformer using TorchServe (by kamalkraj)
Torch Pytorch Deploy torchserve swin-transformer Microsoft eager-load torchscript Docker Cuda Python3
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merged_depth

Monocular Depth Estimation - Weighted-average prediction from multiple pre-trained depth estimation models (by p-ranav)
depth-prediction neural-networks Pytorch Python3 Torch torchvision Image processing Prediction average mit-license open-source Academic depth-estimation Camera Youtube Images average-calculator Machine Learning Deep Learning
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Swin-Transformer-Serve merged_depth
1 3
26 45
- -
0.0 1.8
almost 3 years ago over 2 years ago
Python Python
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.
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Swin-Transformer-Serve

Posts with mentions or reviews of Swin-Transformer-Serve. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-04-14.

merged_depth

Posts with mentions or reviews of merged_depth. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-03-19.

What are some alternatives?

When comparing Swin-Transformer-Serve and merged_depth you can also consider the following projects:

Swin-Transformer-Semantic-Segmentation - This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Semantic Segmentation.

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

Swin-Transformer-Object-Detection - This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Object Detection and Instance Segmentation.

Cam-Hackers - Hack Cameras CCTV FREE

torchlambda - Lightweight tool to deploy PyTorch models to AWS Lambda

magicavoxel-shaders - A collection of shaders for MagicaVoxel to generate geometry, noise, patterns, and simplify common and repetitive tasks.

QualityScaler - QualityScaler - image/video deeplearning upscaling for any GPU

mildlyoverfitted - Paper implementations from scratch and machine learning tutorials

OpenSeeFace - Robust realtime face and facial landmark tracking on CPU with Unity integration

Jetson-Nano-Ubuntu-20-image - Jetson Nano with Ubuntu 20.04 image

koila - Prevent PyTorch's `CUDA error: out of memory` in just 1 line of code.

torchextractor - Feature extraction made simple with torchextractor

Swin-Transformer-Serve vs Swin-Transformer-Semantic-Segmentation merged_depth vs AdaBins Swin-Transformer-Serve vs Swin-Transformer-Object-Detection merged_depth vs Cam-Hackers Swin-Transformer-Serve vs torchlambda merged_depth vs magicavoxel-shaders Swin-Transformer-Serve vs QualityScaler merged_depth vs mildlyoverfitted merged_depth vs OpenSeeFace merged_depth vs Jetson-Nano-Ubuntu-20-image merged_depth vs koila merged_depth vs torchextractor