Differences

This shows you the differences between two versions of the page.

--- creating_datasets_for_fingerprinting [2022/10/25 15:47] – [Create your airlock scenario] christiandc
+++ creating_datasets_for_fingerprinting [2022/11/09 12:15] (current) – christiandc
@@ Line 1: / Line 1: @@
-#Creating a dataset for fingerprintinp
+#Creating a dataset for fingerprinting
 The objective of this tutorial is to create a non biased dataset for transmitter identification. By fixing the reciever on a robot, the distance and the canal is constantly and randomly changing, forcing the deep learning process to learn on the RF fingerprints. This tutorial explains how to use FIT/Cortexlab to create this dataset.
@@ Line 7: / Line 7: @@
 ## Create your docker image
-With docker, we will enable the nodes to use Gnuradio 3.7. The codes used are written in this version (waiting for an updtae). In order to do that, we will create an image containing theGnuradio 3.7 version and the python/C++ files used for the dataset creation.
+With docker, we will enable the nodes to use Gnuradio 3.7. The codes used are written in this version (waiting for an update). In order to do that, we will create an image containing theGnuradio 3.7 version and the python/C++ files used for the dataset creation.
 First you have to get the python codes used. Download the following folder :
@@ Line 21: / Line 21: @@
 WORKDIR /root
-COPY ./docker /root
+COPY ./<python_folder_name> /root
-RUN chmod -R 777 ./gr-txid-master
+RUN chmod -R 777 ./<python_subfolder_name>
 </code>
@@ Line 29: / Line 29: @@
 In this dockerfile, the first line download the 3.7 Gnuradio version. Then it adds the python files used for the dataset creation and finally it gives the execution rights to the folder.
+Before building the image, take the node list used by the code which is in the scheduler.py file. This node list will be used in the scenario.
 We can now build our image and then access into it with an ssh command :
@@ Line 52: / Line 54: @@
 </code>
- The following lines might be necessary in case of unfound file error :
+The following lines might be necessary in case of unfound file error :
 <code>
@@ Line 226: / Line 228: @@
 ###Switching on the TurtleBot
-Switch on the base of the robot by pressing this switch on :
+Switch on the base of the robot.
-{{ :img_6215.jpeg?400 |}}
 (the green "//Status//" LED should be turned on, and not flash, nor be yellow. In that case the robot hasn't got enough battery.)
@@ Line 239: / Line 238: @@
 {{ :img_6217.jpeg?600 |}}
-{{ :img_6218.jpeg |}}
 ###Launching the programs
@@ Line 245: / Line 243: @@
 Login to the computor with the user : ''CorteXbot'' and the password : ''cxlbusr''.
+Transfer the first part python codes folder in the robot computer.
 To run the reciever code (from gr-txid) enter into the terminal :
 <code>
-./GNU-Radio/gr-txid/examples/src/reciever.py -R re_00 -I im_00
+.<file_path>/reciever.py -R re_00 -I im_00
 </code>
@@ Line 290: / Line 289: @@
 <code>
-thomas@srvairlock:~/workspace/cortexbot$ ~/workspace/experience/examples/generateData.sh
+username@srvairlock:~/workspace/cortexbot$ ~/workspace/experience/examples/generateData.sh
 </code>
-All the radios present in the scenario are succesivly sending packets to the robot. You can check thath everything is fine by doing :
+All the radios present in the scenario are succesivly sending packets to the robot. You can check that everything is fine by doing :
 <code>
@@ Line 307: / Line 306: @@
 ## Gathering the results
+To gather the results, at the end of the emissions we used a USB stick to collect the results directly from the computer of the robot. Copy and paste all the files under the format :
+<code>
+re_00_[number du node] and im_00_[number of node]</code>
+Congratulations, you have succesfully generated a dataset with the FIT/Cortexlab.