rename ROS pkgs with image_recognition_prefix

Author: reinzor

README.md

@@ -10,13 +10,13 @@ Package | Build status Xenial Kinetic x64 | Description
 [image_recognition_analysis](https://github.com/tue-robotics/image_recognition/tree/master/image_recognition_analysis) | [![Build Status](http://build.ros.org/job/Ksrc_uX__image_recognition_analysis__ubuntu_xenial__source/1//badge/icon)](http://build.ros.org/job/Ksrc_uX__image_recognition_analysis__ubuntu_xenial__source/1/) | analysis for image recognition
 [image_recognition_msgs](https://github.com/tue-robotics/image_recognition/tree/master/image_recognition_msgs) | [![Build Status](http://build.ros.org/job/Ksrc_uX__image_recognition_msgs__ubuntu_xenial__source/1//badge/icon)](http://build.ros.org/job/Ksrc_uX__image_recognition_msgs__ubuntu_xenial__source/1/) | Interface definition for image recognition
 [image_recognition_rqt](https://github.com/tue-robotics/image_recognition/tree/master/image_recognition_rqt) | [![Build Status](http://build.ros.org/job/Ksrc_uX__image_recognition_rqt__ubuntu_xenial__source/1//badge/icon)](http://build.ros.org/job/Ksrc_uX__image_recognition_rqt__ubuntu_xenial__source/1/) | RQT tools with helpers testing this interface and training/labeling data.
-[tensorflow_ros](https://github.com/tue-robotics/image_recognition/tree/master/tensorflow_ros) | [![Build Status](http://build.ros.org/job/Ksrc_uX__tensorflow_ros__ubuntu_xenial__source/1//badge/icon)](http://build.ros.org/job/Ksrc_uX__tensorflow_ros__ubuntu_xenial__source/1/) | Object recognition with use of Tensorflow. The user can retrain the top layers of a neural network to perform classification with its own dataset as described in [this tutorial](https://www.tensorflow.org/versions/r0.11/how_tos/image_retraining/index.html).
-[tensorflow_ros_rqt](https://github.com/tue-robotics/image_recognition/tree/master/tensorflow_ros_rqt) | [![Build Status](http://build.ros.org/job/Ksrc_uX__tensorflow_ros_rqt__ubuntu_xenial__source/1//badge/icon)](http://build.ros.org/job/Ksrc_uX__tensorflow_ros_rqt__ubuntu_xenial__source/1/) | RQT tools for retraining a Tensorflow neural network.
-[openface_ros](https://github.com/tue-robotics/image_recognition/tree/master/openface_ros) | [![Build Status](http://build.ros.org/job/Ksrc_uX__openface_ros__ubuntu_xenial__source/1//badge/icon)](http://build.ros.org/job/Ksrc_uX__openface_ros__ubuntu_xenial__source/1/) | ROS wrapper for Openface (https://github.com/cmusatyalab/openface) to detect and recognize faces in images.
-[skybiometry_ros](https://github.com/tue-robotics/image_recognition/tree/master/skybiometry_ros) | [![Build Status](http://build.ros.org/job/Ksrc_uX__skybiometry_ros__ubuntu_xenial__source/1//badge/icon)](http://build.ros.org/job/Ksrc_uX__skybiometry_ros_ubuntu_xenial__source/1/) | ROS wrapper for Skybiometry (https://skybiometry.com/) for getting face properties of a detected face, e.g. age estimation, gender estimation etc.
-[openpose_ros](https://github.com/tue-robotics/image_recognition/tree/master/openpose_ros) | [![Build Status](http://build.ros.org/job/Ksrc_uX__openpose_ros__ubuntu_xenial__source/1//badge/icon)](http://build.ros.org/job/Ksrc_uX__openpose_ros_ubuntu_xenial__source/1/) | ROS wrapper for Openpose (https://github.com/CMU-Perceptual-Computing-Lab/) for getting poses of 2D images.
-[jetson_inference_ros](https://github.com/tue-robotics/image_recognition/tree/master/jetson_inference_ros) | [![Build Status](http://build.ros.org/job/Ksrc_uX__jetson_inference_ros__ubuntu_xenial__source/1//badge/icon)](http://build.ros.org/job/Ksrc_uX__jetson_inference_ros_ubuntu_xenial__source/1/) | ROS wrapper for Jetson Inference (https://github.com/dusty-nv/jetson-inference) for running inference using TensorRT.
-[keras_ros](https://github.com/tue-robotics/image_recognition/tree/master/keras_ros) | [![Build Status](http://build.ros.org/job/Ksrc_uX__keras_ros__ubuntu_xenial__source/1//badge/icon)](http://build.ros.org/job/Ksrc_uX__keras_ros_ubuntu_xenial__source/1/) | ROS wrappers for Keras neural nets.
+[image_recognition_tensorflow](https://github.com/tue-robotics/image_recognition/tree/master/image_recognition_tensorflow) | [![Build Status](http://build.ros.org/job/Ksrc_uX__image_recognition_tensorflow__ubuntu_xenial__source/1//badge/icon)](http://build.ros.org/job/Ksrc_uX__image_recognition_tensorflow__ubuntu_xenial__source/1/) | Object recognition with use of Tensorflow. The user can retrain the top layers of a neural network to perform classification with its own dataset as described in [this tutorial](https://www.tensorflow.org/versions/r0.11/how_tos/image_retraining/index.html).
+[image_recognition_tensorflow_rqt](https://github.com/tue-robotics/image_recognition/tree/master/image_recognition_tensorflow_rqt) | [![Build Status](http://build.ros.org/job/Ksrc_uX__image_recognition_tensorflow_rqt__ubuntu_xenial__source/1//badge/icon)](http://build.ros.org/job/Ksrc_uX__image_recognition_tensorflow_rqt__ubuntu_xenial__source/1/) | RQT tools for retraining a Tensorflow neural network.
+[image_recognition_openface](https://github.com/tue-robotics/image_recognition/tree/master/image_recognition_openface) | [![Build Status](http://build.ros.org/job/Ksrc_uX__image_recognition_openface__ubuntu_xenial__source/1//badge/icon)](http://build.ros.org/job/Ksrc_uX__image_recognition_openface__ubuntu_xenial__source/1/) | ROS wrapper for Openface (https://github.com/cmusatyalab/openface) to detect and recognize faces in images.
+[image_recognition_skybiometry](https://github.com/tue-robotics/image_recognition/tree/master/image_recognition_skybiometry) | [![Build Status](http://build.ros.org/job/Ksrc_uX__image_recognition_skybiometry__ubuntu_xenial__source/1//badge/icon)](http://build.ros.org/job/Ksrc_uX__image_recognition_skybiometry_ubuntu_xenial__source/1/) | ROS wrapper for Skybiometry (https://skybiometry.com/) for getting face properties of a detected face, e.g. age estimation, gender estimation etc.
+[image_recognition_openpose](https://github.com/tue-robotics/image_recognition/tree/master/image_recognition_openpose) | [![Build Status](http://build.ros.org/job/Ksrc_uX__image_recognition_openpose__ubuntu_xenial__source/1//badge/icon)](http://build.ros.org/job/Ksrc_uX__image_recognition_openpose_ubuntu_xenial__source/1/) | ROS wrapper for Openpose (https://github.com/CMU-Perceptual-Computing-Lab/) for getting poses of 2D images.
+[image_recognition_jetson](https://github.com/tue-robotics/image_recognition/tree/master/image_recognition_jetson) | [![Build Status](http://build.ros.org/job/Ksrc_uX__image_recognition_jetson__ubuntu_xenial__source/1//badge/icon)](http://build.ros.org/job/Ksrc_uX__image_recognition_jetson_ubuntu_xenial__source/1/) | ROS wrapper for Jetson Inference (https://github.com/dusty-nv/jetson-inference) for running inference using TensorRT.
+[image_recognition_keras](https://github.com/tue-robotics/image_recognition/tree/master/image_recognition_keras) | [![Build Status](http://build.ros.org/job/Ksrc_uX__image_recognition_keras__ubuntu_xenial__source/1//badge/icon)](http://build.ros.org/job/Ksrc_uX__image_recognition_keras_ubuntu_xenial__source/1/) | ROS wrappers for Keras neural nets.
 
 ## Travis CI Build Status
 
@@ -30,7 +30,7 @@ Step 1: label images with the [image_recognition_rqt#annotation-plugin](https://
 [![Annotate](http://img.youtube.com/vi/uAQvn7SInlg/0.jpg)](http://www.youtube.com/watch?v=uAQvn7SInlg)
 <-- Youtube video
 
-Step 2: train a neural network with the [tensorflow_ros_rqt](https://github.com/tue-robotics/image_recognition/tree/master/tensorflow_ros_rqt)
+Step 2: train a neural network with the [image_recognition_tensorflow_rqt](https://github.com/tue-robotics/image_recognition/tree/master/image_recognition_tensorflow_rqt)
 
 [![Train](http://img.youtube.com/vi/6JdtWa8FD04/0.jpg)](http://www.youtube.com/watch?v=6JdtWa8FD04)
 <-- Youtube video
@@ -41,7 +41,7 @@ Step 3: predict labels for new data with the [image_recognition_rqt#test-plugin]
 <-- Youtube video
 
 ## Face recognition
-See the tutorial at [openface_ros](https://github.com/tue-robotics/image_recognition/tree/master/openface_ros)
+See the tutorial at [image_recognition_openface](https://github.com/tue-robotics/image_recognition/tree/master/image_recognition_openface)
 
 [![Face recognition](http://img.youtube.com/vi/yGqDdfYxHZw/0.jpg)](http://www.youtube.com/watch?v=yGqDdfYxHZw)
 <-- Youtube video

image_recognition/package.xml

@@ -11,16 +11,16 @@
 
   <run_depend>image_recognition_msgs</run_depend>
 
-  <run_depend>tensorflow_ros</run_depend>
-  <run_depend>keras_ros</run_depend>
-  <run_depend>openface_ros</run_depend>
-  <run_depend>skybiometry_ros</run_depend>
-  <run_depend>openpose_ros</run_depend>
+  <run_depend>image_recognition_tensorflow</run_depend>
+  <run_depend>image_recognition_keras</run_depend>
+  <run_depend>image_recognition_openface</run_depend>
+  <run_depend>image_recognition_skybiometry</run_depend>
+  <run_depend>image_recognition_openpose</run_depend>
   <run_depend>image_recognition_util</run_depend>
   <run_depend>image_recognition_analysis</run_depend>
 
   <run_depend>image_recognition_rqt</run_depend>
-  <run_depend>tensorflow_ros_rqt</run_depend>
+  <run_depend>image_recognition_tensorflow_rqt</run_depend>
 
   <export>
       <metapackage/>

image_recognition_analysis/README.md

@@ -28,6 +28,6 @@ dog,0.3,0.7
 To use this on e.g. a tensorflow model:
 ```bash
 cd path/to/dir/with/evaluation_set # directory with a subdir for each class, as with training
-rosrun tensorflow_ros evaluate_classifier output_graph.pb $output_labels.txt -o result.csv .
+rosrun image_recognition_tensorflow evaluate_classifier output_graph.pb $output_labels.txt -o result.csv .
 rosrun image_recognition_analysis classifier_metrics result.csv
 ```

jetson_inference_ros/CMakeLists.txt renamed to image_recognition_jetson/CMakeLists.txt

@@ -1,5 +1,5 @@
 cmake_minimum_required(VERSION 2.8.3)
-project(jetson_inference_ros)
+project(image_recognition_jetson)
 
 ## Compile as C++11, supported in ROS Kinetic and newer
 add_compile_options(-std=c++11)

jetson_inference_ros/README.md renamed to image_recognition_jetson/README.md

@@ -1,4 +1,4 @@
-jetson_inference_ros
+image_recognition_jetson
 ====================================
 
 ROS Wrapper for Jetson inference https://github.com/dusty-nv/jetson-inference
@@ -16,7 +16,7 @@ Provides a service and topic interface for jetson inference. For now only the de
 
 Run the install jetson-inference script
 
-    rosrun jetson_inference_ros install_jetson_inference.bash 
+    rosrun image_recognition_jetson install_jetson_inference.bash 
 
 If the jetson-inference cannot be found using CMake, it will compile a mock.
 

jetson_inference_ros/doc/bottles.png renamed to image_recognition_jetson/doc/bottles.png

@@ -5,7 +5,7 @@
   <arg name="model_path" default="ped-100/snapshot_iter_70800.caffemodel" />
 
   <group ns="camera/rgb">
-    <node pkg="jetson_inference_ros" type="detect_net_ros" name="detect_net" output="screen">
+    <node pkg="image_recognition_jetson" type="detect_net_ros" name="detect_net" output="screen">
       <param name="prototxt_path" value="$(arg networks_path)/$(arg prototxt_path)" />
       <param name="model_path" value="$(arg networks_path)/$(arg model_path)" />
       <remap from="image" to="image_rect_color" />

jetson_inference_ros/doc/faces.png renamed to image_recognition_jetson/doc/faces.png

@@ -1,5 +1,5 @@
 <launch>
-  <include file="$(find jetson_inference_ros)/launch/static_kinect.launch">
+  <include file="$(find image_recognition_jetson)/launch/static_kinect.launch">
     <arg name="prototxt_path" value="DetectNet-COCO-Bottle/deploy.prototxt" />
     <arg name="model_path" value="DetectNet-COCO-Bottle/snapshot_iter_59700.caffemodel" />
   </include>