Creating a Tensorflow Model Based on Hough Lines
So I have a project of creating an autonomous rc car. In order to do virtual training, I have set up a simulator to collect picture data, along with a steering angle. I then use an OpenCV program, using Hough line Detection, to detect the 3 lines on the road. I want to create a model that when images are inputted the output will be a steering angle. Using TensorFlow, I trained a CNN with these images and the result was extremely poor.
What kind of model should I use ?
How should I approach training such images?
and
I can also train the data using the actual data for each line which looks like this for one line detected:
[[[0.0, 63.0, 54.0, 31.0, -0.5925925925925926]]]
And this for 2 lines detected:
[[[0.0, 61.0, 34.0, 32.0, -0.8529411764705882], [41.0, 42.0, 43.0, 77.0, 17.5]]]
The only problem is I don't know how to deal with inputs of variable size. Help?
python pandas opencv tensorflow computer-vision
edited Dec 28 '18 at 12:47
J...S
3,42911130
asked Nov 25 '18 at 19:31
niallmandalniallmandal
213
add a comment |
So I have a project of creating an autonomous rc car. In order to do virtual training, I have set up a simulator to collect picture data, along with a steering angle. I then use an OpenCV program, using Hough line Detection, to detect the 3 lines on the road. I want to create a model that when images are inputted the output will be a steering angle. Using TensorFlow, I trained a CNN with these images and the result was extremely poor.
What kind of model should I use ?
How should I approach training such images?
and
I can also train the data using the actual data for each line which looks like this for one line detected:
[[[0.0, 63.0, 54.0, 31.0, -0.5925925925925926]]]
And this for 2 lines detected:
[[[0.0, 61.0, 34.0, 32.0, -0.8529411764705882], [41.0, 42.0, 43.0, 77.0, 17.5]]]
The only problem is I don't know how to deal with inputs of variable size. Help?
python pandas opencv tensorflow computer-vision
edited Dec 28 '18 at 12:47
J...S
3,42911130
asked Nov 25 '18 at 19:31
niallmandalniallmandal
213
I thought you were detecting “the 3 lines on the road”? I can only see two in your Hough Lines image.
– barny
Nov 25 '18 at 22:06
Call me a boring old-fashioned old fogey if you want, but I'm not so sure as you that a neural network is what you need here. I'd have thought there is a geometric model you can create which might well be easier and also much more predictable when it comes across the curve that it hasn't seen before rather than attempting to train a neural network to give you a steering angle. And note I said "you" because there's no way I'm going to let any neural network steer my car when I don't know what its possible input->output relationships are in every circumstance it might come across.
– barny
Nov 25 '18 at 23:28
There are 3 possible lines, but sometimes a line is missed and this needs to be accounted for
– niallmandal
Nov 26 '18 at 2:10
So I guess you need two outputs from your solution: a steering angle, and a signal “Human control necessary” that sounds a klaxon and leaves the driver to make the critical decision where to steer?
– barny
Nov 26 '18 at 8:38
add a comment |
So I have a project of creating an autonomous rc car. In order to do virtual training, I have set up a simulator to collect picture data, along with a steering angle. I then use an OpenCV program, using Hough line Detection, to detect the 3 lines on the road. I want to create a model that when images are inputted the output will be a steering angle. Using TensorFlow, I trained a CNN with these images and the result was extremely poor.
What kind of model should I use ?
How should I approach training such images?
and
I can also train the data using the actual data for each line which looks like this for one line detected:
[[[0.0, 63.0, 54.0, 31.0, -0.5925925925925926]]]
And this for 2 lines detected:
[[[0.0, 61.0, 34.0, 32.0, -0.8529411764705882], [41.0, 42.0, 43.0, 77.0, 17.5]]]
The only problem is I don't know how to deal with inputs of variable size. Help?
python pandas opencv tensorflow computer-vision
edited Dec 28 '18 at 12:47
J...S
3,42911130
asked Nov 25 '18 at 19:31
niallmandalniallmandal
213
So I have a project of creating an autonomous rc car. In order to do virtual training, I have set up a simulator to collect picture data, along with a steering angle. I then use an OpenCV program, using Hough line Detection, to detect the 3 lines on the road. I want to create a model that when images are inputted the output will be a steering angle. Using TensorFlow, I trained a CNN with these images and the result was extremely poor.
What kind of model should I use ?
How should I approach training such images?
and
I can also train the data using the actual data for each line which looks like this for one line detected:
[[[0.0, 63.0, 54.0, 31.0, -0.5925925925925926]]]
And this for 2 lines detected:
[[[0.0, 61.0, 34.0, 32.0, -0.8529411764705882], [41.0, 42.0, 43.0, 77.0, 17.5]]]
The only problem is I don't know how to deal with inputs of variable size. Help?
python pandas opencv tensorflow computer-vision
python pandas opencv tensorflow computer-vision
edited Dec 28 '18 at 12:47
J...S
3,42911130
asked Nov 25 '18 at 19:31
niallmandalniallmandal
213
edited Dec 28 '18 at 12:47
J...S
3,42911130
asked Nov 25 '18 at 19:31
niallmandalniallmandal
213
edited Dec 28 '18 at 12:47
J...S
3,42911130
edited Dec 28 '18 at 12:47
J...S
3,42911130
edited Dec 28 '18 at 12:47
J...S
3,42911130
3,42911130
asked Nov 25 '18 at 19:31
niallmandalniallmandal
213
asked Nov 25 '18 at 19:31
niallmandalniallmandal
213
asked Nov 25 '18 at 19:31
niallmandalniallmandal
213
213
I thought you were detecting “the 3 lines on the road”? I can only see two in your Hough Lines image.
– barny
Nov 25 '18 at 22:06
Call me a boring old-fashioned old fogey if you want, but I'm not so sure as you that a neural network is what you need here. I'd have thought there is a geometric model you can create which might well be easier and also much more predictable when it comes across the curve that it hasn't seen before rather than attempting to train a neural network to give you a steering angle. And note I said "you" because there's no way I'm going to let any neural network steer my car when I don't know what its possible input->output relationships are in every circumstance it might come across.
– barny
Nov 25 '18 at 23:28
There are 3 possible lines, but sometimes a line is missed and this needs to be accounted for
– niallmandal
Nov 26 '18 at 2:10
So I guess you need two outputs from your solution: a steering angle, and a signal “Human control necessary” that sounds a klaxon and leaves the driver to make the critical decision where to steer?
– barny
Nov 26 '18 at 8:38
add a comment |
I thought you were detecting “the 3 lines on the road”? I can only see two in your Hough Lines image.
– barny
Nov 25 '18 at 22:06
Call me a boring old-fashioned old fogey if you want, but I'm not so sure as you that a neural network is what you need here. I'd have thought there is a geometric model you can create which might well be easier and also much more predictable when it comes across the curve that it hasn't seen before rather than attempting to train a neural network to give you a steering angle. And note I said "you" because there's no way I'm going to let any neural network steer my car when I don't know what its possible input->output relationships are in every circumstance it might come across.
– barny
Nov 25 '18 at 23:28
There are 3 possible lines, but sometimes a line is missed and this needs to be accounted for
– niallmandal
Nov 26 '18 at 2:10
So I guess you need two outputs from your solution: a steering angle, and a signal “Human control necessary” that sounds a klaxon and leaves the driver to make the critical decision where to steer?
– barny
Nov 26 '18 at 8:38
I thought you were detecting “the 3 lines on the road”? I can only see two in your Hough Lines image.
– barny
Nov 25 '18 at 22:06
I thought you were detecting “the 3 lines on the road”? I can only see two in your Hough Lines image.
– barny
Nov 25 '18 at 22:06
Call me a boring old-fashioned old fogey if you want, but I'm not so sure as you that a neural network is what you need here. I'd have thought there is a geometric model you can create which might well be easier and also much more predictable when it comes across the curve that it hasn't seen before rather than attempting to train a neural network to give you a steering angle. And note I said "you" because there's no way I'm going to let any neural network steer my car when I don't know what its possible input->output relationships are in every circumstance it might come across.
– barny
Nov 25 '18 at 23:28
Call me a boring old-fashioned old fogey if you want, but I'm not so sure as you that a neural network is what you need here. I'd have thought there is a geometric model you can create which might well be easier and also much more predictable when it comes across the curve that it hasn't seen before rather than attempting to train a neural network to give you a steering angle. And note I said "you" because there's no way I'm going to let any neural network steer my car when I don't know what its possible input->output relationships are in every circumstance it might come across.
– barny
Nov 25 '18 at 23:28
There are 3 possible lines, but sometimes a line is missed and this needs to be accounted for
– niallmandal
Nov 26 '18 at 2:10
There are 3 possible lines, but sometimes a line is missed and this needs to be accounted for
– niallmandal
Nov 26 '18 at 2:10
So I guess you need two outputs from your solution: a steering angle, and a signal “Human control necessary” that sounds a klaxon and leaves the driver to make the critical decision where to steer?
– barny
Nov 26 '18 at 8:38
So I guess you need two outputs from your solution: a steering angle, and a signal “Human control necessary” that sounds a klaxon and leaves the driver to make the critical decision where to steer?
– barny
Nov 26 '18 at 8:38
add a comment |
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I thought you were detecting “the 3 lines on the road”? I can only see two in your Hough Lines image.
– barny
Nov 25 '18 at 22:06
Call me a boring old-fashioned old fogey if you want, but I'm not so sure as you that a neural network is what you need here. I'd have thought there is a geometric model you can create which might well be easier and also much more predictable when it comes across the curve that it hasn't seen before rather than attempting to train a neural network to give you a steering angle. And note I said "you" because there's no way I'm going to let any neural network steer my car when I don't know what its possible input->output relationships are in every circumstance it might come across.
– barny
Nov 25 '18 at 23:28
There are 3 possible lines, but sometimes a line is missed and this needs to be accounted for
– niallmandal
Nov 26 '18 at 2:10
So I guess you need two outputs from your solution: a steering angle, and a signal “Human control necessary” that sounds a klaxon and leaves the driver to make the critical decision where to steer?
– barny
Nov 26 '18 at 8:38