caffe
Here are 745 public repositories matching this topic...
Issue Summary
Documentation and error messages are misleading when using a release version of Caffe on Ubuntu.
Executed Command (if any)
cmake .. -DBUILD_CAFFE=OFF -DCaffe_INCLUDE_DIRS=/usr/include/caffe -DCaffe_LIBS=/usr/lib/x86_64-linux-gnu/libcaffe.so
OpenPose Output (if any)
-- The C compiler identification is GNU 7.5.0
-- The CXX compiler identificatio
Visualizer for neural network, deep learning and machine learning models
-
Updated
Jul 16, 2020 - JavaScript
ncnn is a high-performance neural network inference framework optimized for the mobile platform
-
Updated
Jul 16, 2020 - C++
Set up deep learning environment in a single command line.
-
Updated
Jun 10, 2020 - Python
I've moved from Caffe/Digits to TensorFlow in my own work, and I want to update this to show how to do the same tasks with TensorFlow.
Given the hard work by @BirkhoffLee translating the original, I don't want to break what we already have. I'm debating whether to integrate it into the current document, or start a new one. I think it's nice to see how transferable the approach is across ML fr
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
-
Updated
Jul 12, 2020 - Python
Largest list of models for Core ML (for iOS 11+)
-
Updated
Dec 17, 2019 - Python
Code repo for realtime multi-person pose estimation in CVPR'17 (Oral)
-
Updated
Mar 21, 2020 - Jupyter Notebook
Deep Learning GPU Training System
-
Updated
Jun 13, 2020 - HTML
Go package for computer vision using OpenCV 4 and beyond.
-
Updated
Jul 11, 2020 - Go
When attempting to download cityscapes_2048x1024 I got: ./download-models.sh: line 721: download_fcn_resnet18_cityscapes_2048x512: command not found
It looks like there was a typo, and line 721 needs to be changed from:
download_fcn_resnet18_cityscapes_2048x512 to download_fcn_resnet18_cityscapes_2048x1024
Thanks for the amazing repo!
The convertor/conversion of deep learning models for different deep learning frameworks/softwares.
-
Updated
Mar 2, 2020
Deep Learning Visualization Toolkit(『飞桨』深度学习可视化工具 )
-
Updated
Jul 16, 2020 - TypeScript
Machine Learning Platform for Kubernetes
-
Updated
Jul 16, 2020 - Python
Automatic colorization using deep neural networks. "Colorful Image Colorization." In ECCV, 2016.
-
Updated
Mar 9, 2020 - Jupyter Notebook
Deep learning software for colorizing black and white images with a few clicks.
-
Updated
Apr 13, 2020 - Python
Deep Learning API and Server in C++11 support for Caffe, Caffe2, PyTorch,TensorRT, Dlib, NCNN, Tensorflow, XGBoost and TSNE
-
Updated
Jul 13, 2020 - C++
人工智能学习路线图,整理近200个实战案例与项目,免费提供配套教材,零基础入门,就业实战!包括:Python,数学,机器学习,数据分析,深度学习,计算机视觉,自然语言处理,PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-intelligence python tensorflow tensorflow2 caffe keras pytorch algorithm numpy pandas matplotlib seaborn nlp cv等热门领域
-
Updated
Feb 6, 2020
Türkiye'de yapılan derin öğrenme (deep learning) ve makine öğrenmesi (machine learning) çalışmalarının derlendiği sayfa.
-
Updated
Nov 22, 2019
Caffe implementation of Google MobileNet SSD detection network, with pretrained weights on VOC0712 and mAP=0.727.
-
Updated
Jan 4, 2020 - Python
Implementation for <SphereFace: Deep Hypersphere Embedding for Face Recognition> in CVPR'17.
-
Updated
Apr 4, 2019 - Jupyter Notebook
Caffe models (including classification, detection and segmentation) and deploy files for famouse networks
-
Updated
Mar 22, 2018 - Python
《深度学习与计算机视觉》配套代码
-
Updated
Jan 24, 2020 - Python
Caffe Implementation of Google's MobileNets (v1 and v2)
-
Updated
Apr 2, 2019 - Python
FeatherCNN is a high performance inference engine for convolutional neural networks.
-
Updated
Sep 24, 2019 - C++
-
Updated
Nov 22, 2019 - Python
PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume, CVPR 2018 (Oral)
-
Updated
May 2, 2020 - Python
FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
-
Updated
Jul 30, 2019 - C++
Improve this page
Add a description, image, and links to the caffe topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the caffe topic, visit your repo's landing page and select "manage topics."


Alexnet implementation in tensorflow has incomplete architecture where 2 convolution neural layers are missing. This issue is in reference to the python notebook mentioned below.
https://github.com/donnemartin/data-science-ipython-notebooks/blob/master/deep-learning/tensor-flow-examples/notebooks/3_neural_networks/alexnet.ipynb