Deep-Learning-in-Visual-Recognition-and-Planning

Install requirements:

Install bazel and tensorflow ( check tensorflow's github for more info )

If you have Ubuntu 14.04

Run the following commands

sudo add-apt-repository ppa:webupd8team/java

sudo apt-get update

sudo apt-get install oracle-java8-installer

• Download bazel (version: https://github.com/bazelbuild/bazel/releases/download/0.2.0/bazel-0.2.0-jdk7-installer-linux-x86_64.sh)

-chmod +x PATH_TO_INSTALL.SH

- ./PATH_TO_INSTALL.SH --user

• Place bazel onto path ( exact path to store shown in the output)

How to retrain the imagenet from tensorflow

• For retraining, prepare folder structure as
  • root_folder_name
    • class 1
      • file1
      • file2
    • class 2
      • file1
      • file2
• Clone tensorflow
• Go to root of tensorflow

sudo bazel build tensorflow/examples/image_retraining:retrain

sudo bazel-bin/tensorflow/examples/image_retraining/retrain --image_dir /path/to/root_folder_name  --output_graph /path/output_graph.pb --output_labels /path/output_labels.txt --bottleneck_dir /path/bottleneck

Train done passing for test

How to test it:

Run file evaluate_image.py

Cut videos in frames

You must install ffmpeg for this

ffmpeg -i video.mp4 -r 5 image%03d.jpg

If you need more frames increase the number followed by the flag -r

##Run with kinect 2

roslaunch kinect2_bridge kinect2_bridge.launch

Run evaluate images to get images and save them

In ros directory

 source devel/setup.bash

Then run

rosrun kinect_images save_image.py