CUDA and CuDNN

• https://developer.nvidia.com/cuda-downloads
• https://developer.nvidia.com/rdp/cudnn-download

export CUDA_HOME=/usr/local/cuda
export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64"

Tensor flow Install

• https://www.tensorflow.org/install/install_linux#InstallingAnaconda
  'conda create -n tensorflow pip python=2.7'
  'pip install --ignore-installed --upgrade
  https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.8.0-cp27-none-linux_x86_64.whl'

(tensorflow) dcml@dcml-MS-7B61:~/workspace/virtualenv$ python
Python 2.7.15 |Anaconda, Inc.| (default, May 1 2018, 23:32:55)
[GCC 7.2.0] on linux2
Type "help", "copyright", "credits" or "license" for more information.

import tensorflow
Traceback (most recent call last):
File "", line 1, in
File "/home/dcml/.conda/envs/tensorflow/lib/python2.7/site-packages/tensorflow/init.py", line 24, in
from tensorflow.python import pywrap_tensorflow # pylint: disable=unused-import
File "/home/dcml/.conda/envs/tensorflow/lib/python2.7/site-packages/tensorflow/python/init.py", line 49, in
from tensorflow.python import pywrap_tensorflow
File "/home/dcml/.conda/envs/tensorflow/lib/python2.7/site-packages/tensorflow/python/pywrap_tensorflow.py", line 74, in
raise ImportError(msg)
ImportError: Traceback (most recent call last):
File "/home/dcml/.conda/envs/tensorflow/lib/python2.7/site-packages/tensorflow/python/pywrap_tensorflow.py", line 58, in
from tensorflow.python.pywrap_tensorflow_internal import *
File "/home/dcml/.conda/envs/tensorflow/lib/python2.7/site-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 28, in
_pywrap_tensorflow_internal = swig_import_helper()
File "/home/dcml/.conda/envs/tensorflow/lib/python2.7/site-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 24, in swig_import_helper
_mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
ImportError: libcublas.so.9.0: cannot open shared object file: No such file or directory

Failed to load the native TensorFlow runtime.

See https://www.tensorflow.org/install/install_sources#common_installation_problems

for some common reasons and solutions. Include the entire stack trace
above this error message when asking for help.

quit()

ldconfig -v

added by Anaconda2 installer

export PATH="/opt/anaconda2/bin:$PATH"

export CUDA_HOME=/usr/local/cuda
#export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64"

export LD_LIBRARY_PATH=/usr/local/cuda/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH

sudo /opt/anaconda2/bin/pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.8.0-cp27-none-linux_x86_64.whl

sudo /opt/anaconda2/bin/pip install --ignore-installed --upgrade --force keras

libtbb-dev
libv4l/libv4l2-dev
libgstreamer-plugins-base1.0-dev
tesseract-ocr
libtesseract-dev
libleptonica-dev

nvcc -V

function lib_installed() { /sbin/ldconfig -N -v $(sed 's/:/ /' <<< $LD_LIBRARY_PATH) 2>/dev/null | grep $1; }
function check() { lib_installed $1 && echo "$1 is installed" || echo "ERROR: $1 is NOT installed"; }
check libcudnn

function lib_installed() { /sbin/ldconfig -N -v $(sed 's/:/ /' <<< $LD_LIBRARY_PATH) 2>/dev/null | grep $1; }
function check() { lib_installed $1 && echo "$1 is installed" || echo "ERROR: $1 is NOT installed"; }
check libcuda
check libcudart

Notes

Patch
dcml@sun:~/workspace/training/india/session1/tf4p2$ git diff
diff --git a/scripts/label_image.py b/scripts/label_image.py
index 613a095..18bd5e7 100644
--- a/scripts/label_image.py
+++ b/scripts/label_image.py
@@ -39,6 +39,11 @@ def read_tensor_from_image_file(file_name, input_height=299, input_width=299,
input_mean=0, input_std=255):
input_name = "file_reader"
output_name = "normalized"
+

• #force values

• input_height=224

• input_width=224

• file_reader = tf.read_file(file_name, input_name)
  if file_name.endswith(".png"):
  image_reader = tf.image.decode_png(file_reader, channels = 3,
  @@ -73,9 +78,14 @@ if name == "main":
  label_file = "tf_files/retrained_labels.txt"
  input_height = 224
  input_width = 224
• input_height = 299
• input_width = 299
• input_mean = 128
  input_std = 128

• input_layer = "input"

• input_layer = "input"

• input_layer = "Mul"
  output_layer = "final_result"

  parser = argparse.ArgumentParser()
  @@ -118,6 +128,8 @@ if name == "main":

  input_name = "import/" + input_layer
  output_name = "import/" + output_layer

• print(input_name)

• print(output_name)
  input_operation = graph.get_operation_by_name(input_name);
  output_operation = graph.get_operation_by_name(output_name);

Png to Jpg

mogrify -format jpg *.png

#!/bin/bash

cd tf_files/objects
cd Bus
mogrify -format jpg *.png
cd ..

cd Car
mogrify -format jpg *.png
cd ..

cd LCV
mogrify -format jpg *.png
cd ..

cd MAV
mogrify -format jpg *.png
cd ..

cd MCL
mogrify -format jpg *.png
cd ..

cd MiniBus
mogrify -format jpg *.png
cd ..

cd NoVehicle
mogrify -format jpg *.png
cd ..

cd Truck
mogrify -format jpg *.png
cd ..

Train

export ARCHITECTURE="inception_v3"

python -m scripts.retrain
--bottleneck_dir=tf_files/bottlenecks
--how_many_training_steps=500
--model_dir=tf_files/models/
--summaries_dir=tf_files/training_summaries/"${ARCHITECTURE}"
--output_graph=tf_files/retrained_graph.pb
--output_labels=tf_files/retrained_labels.txt
--architecture="${ARCHITECTURE}"
--image_dir=tf_files/objects

Test

#!/bin/bash

python -m scripts.label_image
--graph=tf_files/retrained_graph.pb
--image=$1