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initial commit, simple, separated models #1
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Sorry, my notification settings were messed up. I have to fix some CLAbot settings, and then I'll look at your PR in detail. Thanks! |
Can you say something? I'm checking that the CLA bot works. |
something. :) |
Thanks for your pull request. It looks like this may be your first contribution to a Google open source project. Before we can look at your pull request, you'll need to sign a Contributor License Agreement (CLA). 📝 Please visit https://cla.developers.google.com/ to sign. Once you've signed, please reply here (e.g.
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Why do I need sign some CLA? I don't want to fill in my mobile number atc... #justWhyGoogle |
The CLA is the only way for us to ensure that the code in this repository is actually licensed under Apache2. If we didn't have CLAs, it would be nominally Apache2, but if someone finds their code here, or thinks they do, our defense may be weak. Therefore we cannot accept contributions without a CLA -- it protects not only Google, but also everybody who uses this code. Our CLA is very reasonable. I'd love to accept your contribution, but I cannot without the CLA. |
I signed it! |
CLAs look good, thanks! |
here you go. but only because you are Google, guys :P |
would you be interested in more sophisticated, objected oriented model? Or are these simple separated models great as PoC? I can add some more, parametrized models. |
@@ -0,0 +1 @@ | |||
autoencoder/MNIST_data/* |
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If you are adding .gitignore cosider adding *.pyc there and remove the pyc files from this PR (and squash it, so the never make it to the repo).
These models are great. Can you remove the pyc as Jan said, then we can merge. @ilblackdragon, this is using sklearn "bare", maybe down the road we can merge with some of your examples? |
sure, I will do it, sorry for late responses On 14 March 2016 at 18:47, Martin Wicke [email protected] wrote:
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What about now? |
Looks good. Can you rebase and squash? |
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sure, done 👍 |
initial commit, simple, separated models
Thank you! |
update to tensorflow/model master
add parens around the print, so runs in py3
Add Dockerfile
Add graphs of percents for the prediction array
Add example image classification inference script and readme
…-src Move files into src
lable map for 'Sebastian Houben, Johannes Stallkamp, Jan Salmen, Marc Schlipsing and Christian Igel, "Detection of Traffic Signs in Real-World Images: The German Traffic Sign Detection Benchmark", IEEE International Joint Conference on Neural Networks (submitted), 2013' ID's are original ID's+1 for a pbtxt-map always starts with tensorflow#1
Fixed Code Execution on tensorflow/models
Modified return_coordinates function from EdjeElectronics/TensorFlow-Object-Detection-API-Tutorial-Train-Multiple-Objects-Windows-10#69
code of "Solving Low-Dose CT Reconstruction via GAN with Local Coherence"
not sure, how this repository is planned to be. so this is just first attemt. feel free to criticise it