Differences

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

--- creating_datasets_for_fingerprinting [2022/11/02 13:55] – [Create your docker image] 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 243: / 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 288: / 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 305: / 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.