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

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

Platform (like ubuntu 16.04/win10): Windows 10
Python version: 3.7.4, mmdnn==0.2.5

Running scripts: mmconvert -f caffe -df keras -om test

I know that this command is not supposed to run without passing an input file, but the error message is incorrect and should be improved:

mmconvert: error: argument --srcFramework/-f: invalid choice: 'None' (choose from 'caffe', 'caffe2', 'cn

Paper says:

Code is following
https://github.com/CMU-Perceptual-Computing-Lab/caffe_train/blob/master/src/caffe/cpm_data_transformer.cpp
<img width="1077" alt="screen shot 2017-11-14 at 01 33 49" src="https://user-images.

Hi all,
So I'm using DIGITS version: 6.1.1 with Caffe version: 0.17.0 and Caffe flavor: NVIDIA
I've successfully used NVIDIA/Digits many times but when using compatible mode I cant replicate results in opencv or caffe BVLC.

This is the output I get on Digits:

but this is what I

Description

I would like to use OpenVINO as part of my AWS Lambda function in order to load and execute inference with models (packaged in .xml and .bin files) trained by OpenVINO framework.

Problem is, OpenVINO R1 that I am using takes ~900MB. My question is, what parts of OpenVINO do I need in order to load mode

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!

All tensorflow examples use ancient version of tensorflow. They should be updated to work without deprecation warnings with modern versions (1.14+). It is hard to get into polyaxon when examples are years behind (tf 1.4 was released in 2017) in such fast moving field.

I download Caffe and Interactive zip ..
But i can't run them?

i use mac os please guide step by step

Thanks

Hi,

I try to understand Deepdetect right now, starting with the Plattforms Docker container.
It looks great on pictures, but I have a hard time right now using it :)

My Problem: The docs seems to step over important points, like using JupyterLab. All examples shows the finished Custom masks, but how do I get them?

Is there something missing in the docs?

Example: https://www.deepdetec

In the xlearning job web UI, the metrics graph can not be seen for these is no js for it.

I am Android engineer,just follow tutorial "https://docs.opencv.org/3.4.0/d0/d6c/tutorial_dnn_android.html" linked there to find "MobileNetSSD_deploy.caffemodel" file but there is another one ; when i use the file "MobileNet_deploy.caffemodel"
the output is not work as expected

1. 31页，第一行
   
   应改成
   

2. 35 页， 正定矩阵的定义 （公式 2-15）
   标准正定矩阵的定义，应该没有 “对称矩阵” 这一条件吧？ 只是您在本书大多讨论的是“对称”正定矩阵，所以加上了 “对称” 这一条件？

3. 38页， 奇异值分解定义（公式 2-16）
   ![default](https://

In RTC-Feature branch, implementation for Real Time Collaboration is in progress. In order to make code more readable documentation for backend codebase needs to be added.

Hi,
first of all kudos to fantastic developers like you guys... I am very excited to use this library. I plan to use it on an embedded system but I can't get past the basic compiling of ./build_scripts/build_linux.sh
I mean, it would be very nice if you could redirect me to a use case of other resource for using the library on Embedded OS. :)