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Kaggle dogs vs cats solution
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demo
finetuning
learning_from_scratch
.gitignore
README.md
average_results.py
convert_all_mean_files.sh
convert_mean.py
create_kaggle_submission_binary.py
create_kaggle_submission_probability.py
create_submissions_for_all.sh
forward_pass_time.sh
get_prediction_errors.py
usefull_utils.py

README.md

Solutions for https://www.kaggle.com/c/dogs-vs-cats and https://www.kaggle.com/c/dogs-vs-cats-redux-kernels-edition competition.

Here is table with results, but hyperparameters of neural nets can drastically affect accuracy, so feel free to try it out, reproduce results and improve them!

Name Acc. test finetuned Acc. test. Train time Forward pass time On disk model size Year Paper
AlexNet 93.65% 97.98% 35m 3.01 ms 227.5Mb 2012 link
SqeezeNet v1.1 92.46% 98.87% ~2h 3.91 ms 2.9Mb 2016 link
GoogLeNet 94.62% 99.58% 50m 11.73 ms 41.3Mb 2014 link
VGG-16 96.51% 99.40% 5h20m 15.41 ms 537.1Mb 2014 link
VGG-19 97.42% 99.48% 25h50m 19.23 ms 558.3Mb 2014 link
Network-In-Network 93.65% 98.49% ~2h 3.17 ms 26.3Mb 2014 link
ResNet-50 95.84% 99.52% 18h 24.91 ms 94.3Mb 2015 link
ResNet-101 96.39% 99.48% 1d 20h 40.95 ms 170.5Mb 2015 link

Test accuracy was measured on train-test split 80%-20%.

1.learning_from_scratch is folder with models that were trained in NVIDIA DIGITS with Caffe backend.

2.finetuning is folder with models that were finetuned from models trained on ImageNet.

3.feature_extraction is folder where CNN used only as feature extractor and SVM was used for training.

Tested on system with following configuration:

Ubuntu version:

`lsb_release -a`

Ubuntu 14.04.4 LTS

`uname -a`

Linux myuser-computer 3.19.0-61-generic #69~14.04.1-Ubuntu SMP Thu Jun 9 09:09:13 UTC 2016 x86_64 x86_64 x86_64 GNU/Linux

gcc version:

`gcc --version`

gcc (Ubuntu 4.8.4-2ubuntu1~14.04.3) 4.8.4

DIGITS version:

`./digits-devserver --version`

4.1-dev

Caffe version:

`git status`

branch caffe-0.15

`git log -n 1`

commit e638c0b1cb19afff50d830ce87cc1898f18568fd
Author: Sergei Nikolaev <snikolaev@nvidia.com>
Date:   Wed Aug 31 14:32:28 2016 -0700
Mark 0.15.13

CPU:

`cat /proc/cpuinfo | grep "model name"`

Intel(R) Core(TM)2 Duo CPU     E8500  @ 3.16GHz

GPU:

`nvidia-smi`

+-----------------------------------------------------------------------------+
| NVIDIA-SMI 367.44                 Driver Version: 367.44                    |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  GeForce GTX 1070    On   | 0000:01:00.0      On |                  N/A |
| 27%   38C    P8    10W / 151W |    150MiB /  8108MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
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