Merge branch 'lab_calculator' into 'master'

Lab calculator

See merge request !2

.gitlab-ci.yml

+#
+#
+#  ******************************************************************************
+#  MontiCAR Modeling Family, www.se-rwth.de
+#  Copyright (c) 2017, Software Engineering Group at RWTH Aachen,
+#  All rights reserved.
+#
+#  This project is free software; you can redistribute it and/or
+#  modify it under the terms of the GNU Lesser General Public
+#  License as published by the Free Software Foundation; either
+#  version 3.0 of the License, or (at your option) any later version.
+#  This library is distributed in the hope that it will be useful,
+#  but WITHOUT ANY WARRANTY; without even the implied warranty of
+#  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+#  Lesser General Public License for more details.
+#
+#  You should have received a copy of the GNU Lesser General Public
+#  License along with this project. If not, see <http://www.gnu.org/licenses/>.
+# *******************************************************************************
+#
+
+stages:
+- linux
+
+TestMXNET:
+  stage: linux
+  image: registry.git.rwth-aachen.de/monticore/embeddedmontiarc/applications/mnistcalculator/mxnet:v0.0.3
+  script: 
+  - cd mxnet
+  - ./prepare.sh
+  - ./build.sh
+  - RES=$(./build/src/cpp/DigitCalculator resources/images/1.png resources/images/2.png resources/images/3.png resources/images/4.png resources/images/5.png resources/images/6.png)
+  - "if [[ $RES != *\"SUM: 579\"* ]]; then echo \"Wrong result:\" $RES; exit 1; fi;"
+
+
+TestCAFFE2:
+  stage: linux
+  image: registry.git.rwth-aachen.de/monticore/embeddedmontiarc/applications/mnistcalculator/caffe2:v0.0.2
+  script: 
+  - cd caffe2
+  - ./build.sh
+  - RES=$(./build/src/cpp/DigitCalculator resources/images/2.jpg resources/images/3.jpg resources/images/4.png resources/images/6.png resources/images/2.jpg resources/images/3.jpg)
+  - "if [[ $RES != *\"SUM: 857\"* ]]; then echo \"Wrong result:\" $RES; exit 1; fi;"

README.md

+# MNISTCalculator
+
+
+## Prerequisites
+1. Ubuntu Linux 16.04 LTS or 18.04 LTS (experimental)
+2. Deep Learning Framework **Caffe2**. [Follow the instructions from this link](https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/CNNArch2Caffe2#ubuntu).
+3. Deep Learning Framework **MXNet**.
+4. Armadillo (at least armadillo version 6.600 must be used) [Official instructions at Armadillo Website](http://arma.sourceforge.net/download.html).
+4. OpenCV
+
+## MXNet and Caffe2
+For detailed instructions on how to run the MXNet and Caffe2 example, see the README in the corresponding folder.
\ No newline at end of file

example_caffe2/.gitignore → caffe2/.gitignore

 train.log
 target/
-resources/training_data
 model/
 build/
\ No newline at end of file

caffe2/README.md

+# MNISTCalculator Caffe2
+
+
+## Prerequisites
+1. Ubuntu Linux 16.04 LTS or 18.04 LTS (experimental)
+2. Deep Learning Framework **Caffe2**. [Follow the instructions from this link](https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/CNNArch2Caffe2#ubuntu).
+3. Armadillo (at least armadillo version 6.600 must be used) [Official instructions at Armadillo Website](http://arma.sourceforge.net/download.html).
+4. OpenCV
+
+
+## How to Run
+Generate and build the code for the EMADL model by executing:
+
+```
+bash build.sh
+```
+
+Finally, run the calculator as follows:
+```
+./build/src/cpp/DigitCalculator test_img/2.jpg test_img/3.jpg test_img/4.png test_img/6.png test_img/2.jpg test_img/3.jpg
+```
+
+You can try different images from the provided `/test_img` directory or even create your own images for testing. Note that the application program DigitCalculator will automatically rescale the given input image to the size 28x28.
+
+
+## Troubleshooting Help
+
+ERROR: HelperA.h:79:28: error: ‘sqrtmat’ was not declared in this scope.
+
+FIX:
+Copy compiled armadillo lib and include files to usr/lib and usr/include respectively. Replace YOUR_ARMADILLO_REPOSITORY and VERSION (e.g. 8.500.1) with your corresponding information:
+```
+cd YOUR_ARMADILLO_REPOSITORY/armadillo-VERSION
+sudo cp libarmadillo* /usr/lib
+cd YOUR_ARMADILLO_REPOSITORY/armadillo-VERSION/include
+sudo cp -r * /usr/include

example_caffe2/build.sh → caffe2/build.sh

-rm -r target/;
-java -jar embedded-montiarc-emadl-generator-0.2.9-jar-with-dependencies.jar -m src/emadl/models/ -r cNNCalculator.Connector -o target -b CAFFE2
+rm -rf target
+java -jar ../embedded-montiarc-emadl-generator-0.2.13-jar-with-dependencies.jar -m src/emadl/models/ -r cNNCalculator.Connector -o target -b CAFFE2
 
 rm -rf build
 mkdir build && cd build

caffe2/resources/docker/Dockerfile

+FROM registry.git.rwth-aachen.de/monticore/embeddedmontiarc/generators/emadl2cpp/integrationtests/caffe2:v0.0.5
+
+RUN apt-get update
+RUN apt-get install -y libopenblas-dev
\ No newline at end of file

example_caffe2/src/emadl/models/cNNCalculator/Network.cnnt → caffe2/src/emadl/models/cNNCalculator/Network.cnnt

 configuration Network{
-     num_epoch:11
+     num_epoch:10
      batch_size:64
-     context:gpu
+     context:cpu
      eval_metric:accuracy
      optimizer:adam{
          learning_rate:0.001

example/build.sh

-rm -r target/; 
-java -jar embedded-montiarc-emadl-generator-0.2.5-SNAPSHOT-jar-with-dependencies.jar -m src/emadl/models/ -r cNNCalculator.Connector -o target -b MXNET
-
-rm -rf build
-mkdir build && cd build
-
-echo "Building DigitClassifier.."
-cmake ..
-#cp -r /home/christopher/Documents/Master/Semester2/Praktikum/mxnet/include/mxnet/ ../target/
-make
\ No newline at end of file

example/generate.sh

-echo "-- Generating files and training Models:"
-
-java -jar embedded-montiarc-emadl-generator-0.2.5-SNAPSHOT-jar-with-dependencies.jar -m src/emadl/models -r cNNCalculator.Connector -o target -b MXNET
-

example/resources/sort.sh

-mkdir 0
-mv *-num0.png 0/.
-
-mkdir 1
-mv *-num1.png 1/.
-
-
-mkdir 2
-mv *-num2.png 2/.
-
-
-mkdir 3
-mv *-num3.png 3/.
-
-mkdir 4
-mv *-num4.png 4/.
-
-
-mkdir 5
-mv *-num5.png 5/.
-
-
-mkdir 6
-mv *-num6.png 6/.
-
-
-mkdir 7
-mv *-num7.png 7/.
-
-
-mkdir 8
-mv *-num8.png 8/.
-
-
-mkdir 9
-mv *-num9.png 9/.
-
-
-

example_caffe2/resources/imgDir-to-h5.py

-from __future__ import print_function
-from __future__ import division
-import h5py
-import numpy as np
-import cv2
-import os
-import argparse
-import errno
-import random
-import sys
-
-
-def create_img_list(name, data_path):
-    dir_name = data_path + "/" + name
-
-    image_paths = []
-    image_class_indices = []
-    print(dir_name)
-    for class_index_name in os.listdir(dir_name):
-        class_dir_path = dir_name + "/" + class_index_name
-        if os.path.isdir(class_dir_path):
-            for image_name in os.listdir(class_dir_path):
-                image_path = class_dir_path + "/" + image_name
-                image_paths.append(image_path)
-                class_index = float(class_index_name)
-                image_class_indices.append(class_index)
-    return image_paths, image_class_indices
-
-def create_h5_from_list(image_paths, image_class_indices, target_dir, target_file_name, input_port_name, output_port_name, shuffle=True):
-    img = cv2.imread(image_paths[0])
-    t_img = np.transpose(img, (2,0,1)).astype(np.float32)
-    #t_img = t_img[-1:,:,:]
-    #print(t_img)
-    channels = t_img.shape[0]
-    height = t_img.shape[1]
-    width = t_img.shape[2]
-    data_size = len(image_paths)
-    
-    target_file = target_dir + "/" + target_file_name + ".h5"
-    if os.path.isfile(target_file):
-        print("File", target_file, "already exists. Skipping data file creation.")
-        return
-    try:
-        os.makedirs(target_dir)
-    except OSError as e:
-        if e.errno != errno.EEXIST:
-            raise
-
-    if shuffle:
-        combined = list(zip(image_paths, image_class_indices))
-        random.shuffle(combined)
-        image_paths[:], image_class_indices[:] = zip(*combined)
-    
-    print("Creating " + target_file + " (images:" + str(data_size) + ", channels:" + str(channels) + ", height:" + str(height) + ", width:" + str(width) + "):")
-    with h5py.File(target_file, "w") as ofile:
-        in_dset = ofile.create_dataset(input_port_name, (data_size,channels, height, width), dtype=np.float32)
-        out_dset = ofile.create_dataset(output_port_name + "_label", (data_size,), dtype=np.float32)
-        for i in range(data_size):
-            img = cv2.imread(image_paths[i])
-            t_img = np.transpose(img, (2,0,1)).astype(np.float32)
-            #t_img = t_img[-1:,:,:]
-            in_dset[i] = t_img
-            out_dset[i] = image_class_indices[i]
-
-            #print progress
-            if i % 100 == 0:
-                percentage = 100*i / data_size
-                sys.stdout.write("\r{:0.1f}%".format(percentage))
-                sys.stdout.flush()
-    sys.stdout.write("\r100.0%\n")
-    sys.stdout.flush()
-
-
-            
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser(description='Translate image directories into hdf5 training sets for EMADL.')
-    parser.add_argument("--in_port", action="store", dest="in_port", default="data")
-    parser.add_argument("--out_port", action="store", dest="out_port", default="softmax")
-    parser.add_argument("--data_path", action="store", dest="data_path", default=".")
-    parser.add_argument("--target_path", action="store", dest="target_path", default=".")
-    args = parser.parse_args()
-    for file_name in os.listdir(args.data_path):
-        if file_name == "train":
-            image_paths, image_class_indices = create_img_list(file_name, args.data_path)
-            create_h5_from_list(image_paths, image_class_indices, args.target_path, file_name, args.in_port, args.out_port)
-        if file_name == "test":
-            image_paths, image_class_indices = create_img_list(file_name, args.data_path)
-            create_h5_from_list(image_paths, image_class_indices, args.target_path, file_name, args.in_port, args.out_port)

example_caffe2/resources/sort.sh

-mkdir 0
-mv *-num0.png 0/.
-
-mkdir 1
-mv *-num1.png 1/.
-
-
-mkdir 2
-mv *-num2.png 2/.
-
-
-mkdir 3
-mv *-num3.png 3/.
-
-mkdir 4
-mv *-num4.png 4/.
-
-
-mkdir 5
-mv *-num5.png 5/.
-
-
-mkdir 6
-mv *-num6.png 6/.
-
-
-mkdir 7
-mv *-num7.png 7/.
-
-
-mkdir 8
-mv *-num8.png 8/.
-
-
-mkdir 9
-mv *-num9.png 9/.
-
-
-

mxnet/README.md

+# Calculator MXNET
+
+
+## Prerequisites
+1. Ubuntu Linux 16.04 LTS or 18.04 LTS (experimental)
+2. Deep Learning Framework **MXNet**
+3. Armadillo (at least armadillo version 6.600 must be used) [Official instructions at Armadillo Website](http://arma.sourceforge.net/download.html).
+4. OpenCV
+
+## Prepare the data
+
+To create the data for training, execute:
+
+```
+bash ./prepare.sh
+```
+
+## How to Run
+Generate and build the code for the EMADL model by executing:
+
+```
+bash build.sh
+```
+
+Finally, run the calculator as follows:
+```
+./build/src/cpp/DigitCalculator resources/images/1.png resources/images/2.png resources/images/3.png resources/images/4.png resources/images/5.png resources/images/6.png
+```
+
+You can try different images from the provided `/resources/images` directory or even create your own images for testing. Note that the application program DigitCalculator will automatically rescale the given input image to the size 32x32.
+
+Note: Currently, the mxnet example uses CIFAR-10 data, not MNIST!
+
+
+## Troubleshooting Help
+
+ERROR: HelperA.h:79:28: error: ‘sqrtmat’ was not declared in this scope.
+
+FIX:
+Copy compiled armadillo lib and include files to usr/lib and usr/include respectively. Replace YOUR_ARMADILLO_REPOSITORY and VERSION (e.g. 8.500.1) with your corresponding information:
+```
+cd YOUR_ARMADILLO_REPOSITORY/armadillo-VERSION
+sudo cp libarmadillo* /usr/lib
+cd YOUR_ARMADILLO_REPOSITORY/armadillo-VERSION/include
+sudo cp -r * /usr/include

mxnet/build.sh

+MXNET_PATH=$(python -c "import mxnet; print(mxnet.__file__)")
+MXNET_FOLDER=$(dirname $MXNET_PATH)
+echo $MXNET_FOLDER
+
+if [ ! -f $MXNET_FOLDER/libmxnet.so ]; then
+    echo "libmxnet.so not found at default location" $MXNET_FOLDER
+    echo "It should be there if the python mxnet package is installed"
+    echo "Either fix the installation, or adapt the ./build.sh script to locate libmxnet.so correctly"
+    exit 1
+fi
+
+rm -rf target
+java -jar ../embedded-montiarc-emadl-generator-0.2.13-jar-with-dependencies.jar -m src/emadl/models/ -r cNNCalculator.Connector -o target -b MXNET
+
+rm -rf build
+mkdir build && cd build
+
+echo "Building DigitClassifier.."
+cmake -D MXNET_PATH=$MXNET_FOLDER/libmxnet.so ..
+make
\ No newline at end of file

mxnet/resources/docker/Dockerfile

+FROM registry.git.rwth-aachen.de/monticore/embeddedmontiarc/generators/emadl2cpp/integrationtests/mxnet:v0.0.3
+
+RUN pip install opencv-python
+
+# Install Open CV - Warning, this takes absolutely forever
+RUN apt-get update && apt-get install -y libgdal-dev
+RUN mkdir -p ~/opencv cd ~/opencv && \
+    wget https://github.com/Itseez/opencv/archive/3.0.0.zip && \
+    unzip 3.0.0.zip && \
+    rm 3.0.0.zip && \
+    mv opencv-3.0.0 OpenCV
+RUN apt-get install -y qtbase5-dev
+RUN apt-get install -y build-essential
+ENV PATH="${PATH}:/usr/include/"
+RUN cd OpenCV && \
+    mkdir build && \ 
+    cd build && \
+    cmake \
+    -DWITH_QT=ON \ 
+    -DWITH_OPENGL=ON \ 
+    -DFORCE_VTK=ON \
+    -DWITH_TBB=ON \
+    -DWITH_GDAL=ON \
+    -DWITH_XINE=ON \
+    -DBUILD_EXAMPLES=ON \
+    -D ENABLE_PRECOMPILED_HEADERS=OFF ..
+RUN cd OpenCV/build && make -j4
+RUN cd OpenCV/build && make install
+RUN cd OpenCV/build && ldconfig
+
+RUN apt-get install -y libopenblas-dev
\ No newline at end of file

example/src/cpp/CMakeLists.txt → mxnet/src/cpp/CMakeLists.txt

@@ -2,13 +2,14 @@ cmake_minimum_required(VERSION 3.5)
 project(DigitCalculator CXX)
 set(CMAKE_CXX_STANDARD 11)
 
+option(MXNET_PATH "Path to libmxnet.so")
 
 
 add_executable(DigitCalculator DigitCalculator.cpp)
 
 set_target_properties(DigitCalculator PROPERTIES LINKER_LANGUAGE CXX)
 find_package(OpenCV REQUIRED)
-target_link_libraries(DigitCalculator "/home/christopher/Documents/Master/Semester2/Praktikum/mxnet/lib/libmxnet.so")
+target_link_libraries(DigitCalculator ${MXNET_PATH})
 set(INCLUDE_DIRS ${INCLUDE_DIRS} ${OpenCV_INCLUDE_DIRS})
 set(LIBS ${LIBS} ${OpenCV_LIBS})
 target_link_libraries(DigitCalculator  cNNCalculator_connector ${LIBS} -lblas -lopenblas)