Quelltext der Seite Walkthrough all Matlab Code Used In This Project

{| class="wikitable"
|+ Tabelle 17: Storing input data
|-
! Name  !!  Description
|-
| storingcropsteeringandframesoncsvrgb.m 
|| Steering values are stored in a CSV file as well as their corresponding frames in RGB.
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| storingcropsteeringandframesoncsvrgb_calibrated.m 
|| Steering values are stored in a CSV file as well as their corresponding calibrated frames in RGB.
|-
| Frames_conversion.m || 
Convert RGB frames to BW, grey, and Canny edge.


|-
| Video_conversion.m || 
Convert RGB videos to BW, grey, and Canny edge.


|-
| speedlimit.m || 

Script which implement minimum and max throttle values

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| storingcropsteeringandframesoncsvgrayscale.m || 

Steering values are stored in a CSV file as well as their corresponding frames in gray.

|}

{| class="wikitable"
|+ Tabelle 18: Calibration
|-
! Name  !! Description
|-
| Calibrationchecker.m || 

Matlab script to check if calibration works on frames.
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| Calibrationchecker_video.m || 
 
Matlab script to check if calibration works on Video.
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| test_camera_calibration.m || 

Matlab script to check if calibration works on frames.

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| 256by256frames.m || 



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| cali.m || 

 calibration 224 x 224 script.
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| calibration_256_256_script.m || 

calibration 256 x 256 script.

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| calibration_500by220.m || 

Calibration with 500 x 220 parameters.

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| calibration_500by220_final.m || 

Calibration with 500 x 220 parameters.

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| calibration_with_one_image.m || 

Calibration with 500 x 220 script.

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| test_extractedframes_256by256_calibrationpara.m || 

testing a frame with the 500 x 220 parameters.

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| Bird_eye_view.m || 


Matlab script to load a parameter and calibrate. 

|}


{| class="wikitable"
|+ Tabelle 19: Lane Tracking
|-
! Name  !! Description
|-
| Lane_angle_tracking.m || 
 
Matlab script to print right lane angle.
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| Lane_tracking.m || 
Matlab script to detect and track lanes.
 
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| Lane_tracking_lane_change.m || 
Matlab script which tracks either the left or right lane and switches the ROI when no lane is detected.
 
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| addinglanepliudot.m || 

Matlab script that displays the steering values as a dot on the screen as well as the detected lanes.

|}

{| class="wikitable"
|+ Tabelle 20: python libraries
|-
! Name  !! Description
|-
| Jtest.py || 
 Python script steering without incrementation.

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| Jtest0.py || 
 
Python script that allows steering by incrementation through buttons 4 and 3.
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| Jtest01.py || 

Python script steering by incrementation with speed constraint.

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| Jtest02-object.py || 
Python script that reads steering_value.txt for autonomous driving and steers automatically when an object is detected.


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| Jtest4.py || 

Python script that reads steering_value.txt for autonomous driving.

|}

{| class="wikitable"
|+ Tabelle 21: autonomous driving.
|-
! Name  !! Description
|-
| autonomous_driving.m || 

Matlab script for autonomous driving with trained NN.

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| autonomous_driving_lanetracking.m || 
Matlab script for autonomous driving by tracking of lane. 

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| RunningtheJetRacerAutonomouslyupdate.m || 

Matlab script for autonomous driving update.

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| RunningtheJetRacerAutonomously.m || 

Matlab script for autonomous driving.

|}

{| class="wikitable"
|+ Tabelle 22: Models
|-
! Name   !! Description
|-
| Improved_Classified_CNN_Model.mat || 
 
Classified CNN Model.

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| Improved_Regression_CNN_Model.mat || 
 
Regression CNN Model.

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| Improved_RGB_CNN_model.mat || 

RGB CNN model improved.
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| RGB_CNN_model.mat || 
 RGB CNN model.
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| RGB_CNN_Regresssion_model.mat || 

RGB CNN Regresssion model.
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| RGB_RGBRect_CNN_Model.mat || 

RGB RGB Rectified CNN Model.
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| RNN_model.mat || 

RNN model.
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| trainedNet.mat || 
Online trained model.

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| Gray_CNN_Classification.mat || 

Gray CNN Classification.
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| Gray_CNN_Regresssion_model.mat || 
Gray CNN Regresssion model.

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| MultiInput_CNN_Model_GrayOnly.mat || 
MultiInput_CNN_Model_Gray.

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| CannyEdge_CNN_Regresssion_model.mat || 

CannyEdge_CNN_Regresssion_model.
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| BW_CNN_Regresssion_model.mat || 
BW_CNN_Regresssion_model.

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| MultiInput_CNN_Model_BW.mat || 

MultiInput_CNN_Model_BW.
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| trainedCNN_Model_1.mat trainedCNN_Model_2.mat trainedCNN_Model_3.mat || 

 Online trained models with trainedCNN_Model_3.mat being traind on trainedCNN_Model_2.mat and so on.
|-
| trained12vid.fig || 

pretrained model with 12 videos.

|}
{| class="wikitable"
|+ Tabelle 23: Training
|-
! Name  !! Description
|-
| Cleaned_RGB_CNN_Classify_model.m || 

Matlab script to train the CNN by classification model using RGB frames with more inputs like direction, steering angles etc.

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| Cleaned_RGB_RGBRect_CNN_Classify_model.m || 
 
Matlab script to train the CNN by classification model using RGB rectified frames.

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| Complete_CNN_Classification.m || 

Matlab script to train the CNN by classification model using RGB frames.

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| RGB_CNN_Classify_model.m || 

Matlab script to train the Classification model using RGB frames.

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| RGB_CNN_model.m || 
 Matlab script to train the CNN model using RGB frames.
 
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| RGB_CNN_Regression_model.m || 

Matlab script to train the Regression model using RGB frames.
 
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| RGB_LSTM_model.m || 

Matlab script to train the LSTM model using RGB frames.

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| RGB_Pretrained_model.m || 
 
Matlab script to train the Pretrained model using RGB frames.
 
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| RGB_Pretrained_model_script.m || 

Matlab script to train the Pretrained model using RGB frames.
 
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| RGB_Reinforcementlearning_model.m || 

Matlab script to train the reinforcement learning model using RGB frames.

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| RGB_RNN_model.m || 
 
Matlab script to train the RNN using RGB frames.

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| RGB_Transferlearning_model.m || 

Matlab script to train the Transferlearning model using RGB frames.

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| RGBmodel.m || 

Matlab script to train the model using RGB frames.

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| Cleaned_Gray_CNN_Classify_model.m || 
 
Matlab script to train the Classification model using grey scale frames.

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| Gray_CNN_model.m || 
 
Matlab script to train the CNN model using grey scale frames.

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| Gray_LSTM_model.m || 
 
Matlab script to train the LSTM model using grey scale frames.

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| Gray_Pretrained_model.m || 

Matlab script to train the ResNet18 model using grey scale frames.
 
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| Gray_Reinforcementlearning_model.m || 

Matlab script to train the model by Reinforcementlearning using grey scale frames.

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| Gray_RNN_model.m || 

Matlab script to train the model by RNN using grey scale frames.

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| Gray_Transferlearning_model.m || 
 
Matlab script to train the model by transfer learning using grey scale frames.

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| Graymodel.m || 

Matlab script to train the model using grey scale frames.

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| greendottraining.m || 

Matlab script to train the NN with the steering angle represented by a dot on the screen

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| online_training.m || 

Matlab script to continue training the model with new data.

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| online_training_RNN.m || 

Matlab script to continue training the RNN model with new data.
 
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| PretrainedNN.m || 

Matlab script to load the pretrained ResNet18 with other parameters.

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| resnet_pretrained.m || 

Matlab script to load the pretrained ResNet18 with another configuration.

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| ResNet18.m || 

Matlab script to load the pretrained ResNet18.

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| ResNet18gray.m || 
 
Matlab script to train the NN with ResNet18 on grey frames.

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| ResNet18rgb.m || 
Matlab script to train the NN with ResNet18 on RGB frames.


|-
| Resnet18trainonceperfram.m || 
 


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| traininglaneplusdot.m || 
Matlab script to train the NN with both the steering angle represented by a dot on the screen and the detected edges.

|}
{| class="wikitable"
|+ Tabelle 8: .MAT files
|-
! Name  !! Description
|-
| cameraParams.mat || 
 


|-
| cameraCalibrationParams.mat || 
 
224 x 224 calibrated parameter.

|-
| cameraCalibrationParams0.mat || 

224 x 224 calibrated parameter improved.

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| cameraCalibrationParams_singleangle.mat || 

224 x 224 calibrated parameter with one checker frame.

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| calibration256by256.mat || 

256 x 256 calibrated parameter.

|}

{| class="wikitable"
|+ Tabelle 8: zeigeMessdaten
|-
! Name   !! Description
|-
| Messdaten2MAT.m || 

Matlab script to convert CSV steering data to a .mat file.

|-
| zeigeMessdaten.m || 

Matlab script to compare actual steering with predicted steering.

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| zeigeMessdaten_CNN_classify_model.m || 
 
Matlab script to compare actual steering with predicted steering for classification model.

|-
| zeigeMessdaten_CNN_Regression.m || 

Matlab script to compare actual steering with predicted steering for regression model.

|-
| zeigeMessdaten_grayscale.m || 

Matlab script to compare actual steering with predicted steering for grayscale model.


|}