wolverinn/Depth-Estimation-PyTorch

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Rank 839,658 (Top 17 %)
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Jupyter Notebook
License
MIT License
Created about 5 years ago
Updated over 4 years ago

wolverinn/Depth-Estimation-PyTorch

wolverinn

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Monocular depth estimation using Feature Pyramid Network implemented in PyTorch 1.1.0

Waking-Up

计算机基础（计算机网络/操作系统/数据库/Git...）面试问题全面总结，包含详细的follow-up question以及答案；全部采用【问题+追问+答案】的形式，即拿即用，直击互联网大厂面试🚀；可用于模拟面试、面试前复习、短期内快速备战面试...

Iridescent

Solid data structure and algorithms

Jupyter Notebook

stable-diffusion-multi-user

stable diffusion multi-user django server code with multi-GPU load balancing

HEVC-CU-depths-prediction-CNN

Using convolutional neural networks to predict the Coding Units (CUs) depths in HEVC intra-prediction mode, in order to reduce the time of the encoding process in HEVC.

Python-tools

Useful & handy tools implemented with Python in 200 lines or less. A good way to practice Python and get productivity improved at the same time!

HEVC-deep-learning-pipeline

Integrating neural network models in HEVC encoder, to test the complexity reduction using deep learning in HEVC intra-prediction.

Build-your-programming-skills

A learning road map for junior programmers focusing from basic to advanced technical skills

igxe-c5-buff-csgo-skins-sale-data-catch

Automatically get the csgo skins sale data on igxe.cn and buff and c5game.com.You can choose the specific skins to get data.

HEVC-CU-depths-dataset

A dataset that contains the Coding Unit image files and their corresponding depths for HEVC intra-prediction.

seu_GPACalculator

automatically log in and calculate GPA for students in southeast university (2020)

my-cpp-practice

What you can do with just a little primary C++ knowledge! (card game, sokoban, Klotski ...)

Machine-Learning-notes

Notes of Andrew Ng's Machine Learning course from coursera.org

Jupyter Notebook

human-pose-estimation-GAN

Estimate 3D human SMPL model from a single RGB image, using GAN, ResNet, GRU, etc.

GOLab-django

a website used for checking and monitoring real time csgo skins' sale data in popular markets using django2.1