How can I create a pixel labelled image for Semantic Segmentation?
I am following the Semantic Segmentation Examples tutorial by MathWorks.
I understand that I can load pixel labeled images
pxDir = fullfile(dataDir,'buildingPixelLabels');
Define the class names.
classNames = ["sky" "grass" "building" "sidewalk"];
Define the label ID for each class name.
pixelLabelID = [1 2 3 4];
and create a pixelLabelDatastore.
pxds = pixelLabelDatastore(pxDir,classNames,pixelLabelID);
But, how do I create a custom pixel labelled image where every pixel value represents the categorical label of that pixel?
I would then proceed by writing:
pxDir = fullfile(dataDir,'myCustomPixelLabels');
If I understood correctly, imageDatastore
holds the actual image and not the pixel labels for that image.
EDIT:
On my system pxDir
points to 'C:Program FilesMATLABR2017atoolboxvisionvisiondatabuildingPixelLabels'
. Since I am on Matlab2017a so this example is not included by default, and I cannot compare or view the file to get a better understanding of what I need to do to reproduce this example.
image matlab image-processing machine-learning computer-vision
add a comment |
I am following the Semantic Segmentation Examples tutorial by MathWorks.
I understand that I can load pixel labeled images
pxDir = fullfile(dataDir,'buildingPixelLabels');
Define the class names.
classNames = ["sky" "grass" "building" "sidewalk"];
Define the label ID for each class name.
pixelLabelID = [1 2 3 4];
and create a pixelLabelDatastore.
pxds = pixelLabelDatastore(pxDir,classNames,pixelLabelID);
But, how do I create a custom pixel labelled image where every pixel value represents the categorical label of that pixel?
I would then proceed by writing:
pxDir = fullfile(dataDir,'myCustomPixelLabels');
If I understood correctly, imageDatastore
holds the actual image and not the pixel labels for that image.
EDIT:
On my system pxDir
points to 'C:Program FilesMATLABR2017atoolboxvisionvisiondatabuildingPixelLabels'
. Since I am on Matlab2017a so this example is not included by default, and I cannot compare or view the file to get a better understanding of what I need to do to reproduce this example.
image matlab image-processing machine-learning computer-vision
1
Isn't that what the tutorial does just there after the last line you got from it?
– Ander Biguri
Nov 22 '18 at 10:29
Actually, this is what exactly happening atpxds = pixelLabelDatastore(pxDir,classNames,pixelLabelID);
– Nouman Riaz Khan
Nov 22 '18 at 13:19
@NoumanRiazKhan butpxDir
loads the pixel labeled image, and that is what I'm asking about. How would one go about creatingmyCustomPixelLabels
– Rrz0
Nov 22 '18 at 13:42
@AnderBiguri so imds = imageDatastore(imDir); represents the image data where I need to label the pixels? How would this look like sinceimageDatastore
is usually used to manage a collection of image files.
– Rrz0
Nov 22 '18 at 13:53
@AnderBiguriimageDatastore
holds the actual image and not the pixel lables for that image.
– Rrz0
Nov 22 '18 at 14:31
add a comment |
I am following the Semantic Segmentation Examples tutorial by MathWorks.
I understand that I can load pixel labeled images
pxDir = fullfile(dataDir,'buildingPixelLabels');
Define the class names.
classNames = ["sky" "grass" "building" "sidewalk"];
Define the label ID for each class name.
pixelLabelID = [1 2 3 4];
and create a pixelLabelDatastore.
pxds = pixelLabelDatastore(pxDir,classNames,pixelLabelID);
But, how do I create a custom pixel labelled image where every pixel value represents the categorical label of that pixel?
I would then proceed by writing:
pxDir = fullfile(dataDir,'myCustomPixelLabels');
If I understood correctly, imageDatastore
holds the actual image and not the pixel labels for that image.
EDIT:
On my system pxDir
points to 'C:Program FilesMATLABR2017atoolboxvisionvisiondatabuildingPixelLabels'
. Since I am on Matlab2017a so this example is not included by default, and I cannot compare or view the file to get a better understanding of what I need to do to reproduce this example.
image matlab image-processing machine-learning computer-vision
I am following the Semantic Segmentation Examples tutorial by MathWorks.
I understand that I can load pixel labeled images
pxDir = fullfile(dataDir,'buildingPixelLabels');
Define the class names.
classNames = ["sky" "grass" "building" "sidewalk"];
Define the label ID for each class name.
pixelLabelID = [1 2 3 4];
and create a pixelLabelDatastore.
pxds = pixelLabelDatastore(pxDir,classNames,pixelLabelID);
But, how do I create a custom pixel labelled image where every pixel value represents the categorical label of that pixel?
I would then proceed by writing:
pxDir = fullfile(dataDir,'myCustomPixelLabels');
If I understood correctly, imageDatastore
holds the actual image and not the pixel labels for that image.
EDIT:
On my system pxDir
points to 'C:Program FilesMATLABR2017atoolboxvisionvisiondatabuildingPixelLabels'
. Since I am on Matlab2017a so this example is not included by default, and I cannot compare or view the file to get a better understanding of what I need to do to reproduce this example.
image matlab image-processing machine-learning computer-vision
image matlab image-processing machine-learning computer-vision
edited Nov 22 '18 at 19:06
Rrz0
asked Nov 21 '18 at 22:10
Rrz0Rrz0
487518
487518
1
Isn't that what the tutorial does just there after the last line you got from it?
– Ander Biguri
Nov 22 '18 at 10:29
Actually, this is what exactly happening atpxds = pixelLabelDatastore(pxDir,classNames,pixelLabelID);
– Nouman Riaz Khan
Nov 22 '18 at 13:19
@NoumanRiazKhan butpxDir
loads the pixel labeled image, and that is what I'm asking about. How would one go about creatingmyCustomPixelLabels
– Rrz0
Nov 22 '18 at 13:42
@AnderBiguri so imds = imageDatastore(imDir); represents the image data where I need to label the pixels? How would this look like sinceimageDatastore
is usually used to manage a collection of image files.
– Rrz0
Nov 22 '18 at 13:53
@AnderBiguriimageDatastore
holds the actual image and not the pixel lables for that image.
– Rrz0
Nov 22 '18 at 14:31
add a comment |
1
Isn't that what the tutorial does just there after the last line you got from it?
– Ander Biguri
Nov 22 '18 at 10:29
Actually, this is what exactly happening atpxds = pixelLabelDatastore(pxDir,classNames,pixelLabelID);
– Nouman Riaz Khan
Nov 22 '18 at 13:19
@NoumanRiazKhan butpxDir
loads the pixel labeled image, and that is what I'm asking about. How would one go about creatingmyCustomPixelLabels
– Rrz0
Nov 22 '18 at 13:42
@AnderBiguri so imds = imageDatastore(imDir); represents the image data where I need to label the pixels? How would this look like sinceimageDatastore
is usually used to manage a collection of image files.
– Rrz0
Nov 22 '18 at 13:53
@AnderBiguriimageDatastore
holds the actual image and not the pixel lables for that image.
– Rrz0
Nov 22 '18 at 14:31
1
1
Isn't that what the tutorial does just there after the last line you got from it?
– Ander Biguri
Nov 22 '18 at 10:29
Isn't that what the tutorial does just there after the last line you got from it?
– Ander Biguri
Nov 22 '18 at 10:29
Actually, this is what exactly happening at
pxds = pixelLabelDatastore(pxDir,classNames,pixelLabelID);
– Nouman Riaz Khan
Nov 22 '18 at 13:19
Actually, this is what exactly happening at
pxds = pixelLabelDatastore(pxDir,classNames,pixelLabelID);
– Nouman Riaz Khan
Nov 22 '18 at 13:19
@NoumanRiazKhan but
pxDir
loads the pixel labeled image, and that is what I'm asking about. How would one go about creating myCustomPixelLabels
– Rrz0
Nov 22 '18 at 13:42
@NoumanRiazKhan but
pxDir
loads the pixel labeled image, and that is what I'm asking about. How would one go about creating myCustomPixelLabels
– Rrz0
Nov 22 '18 at 13:42
@AnderBiguri so imds = imageDatastore(imDir); represents the image data where I need to label the pixels? How would this look like since
imageDatastore
is usually used to manage a collection of image files.– Rrz0
Nov 22 '18 at 13:53
@AnderBiguri so imds = imageDatastore(imDir); represents the image data where I need to label the pixels? How would this look like since
imageDatastore
is usually used to manage a collection of image files.– Rrz0
Nov 22 '18 at 13:53
@AnderBiguri
imageDatastore
holds the actual image and not the pixel lables for that image.– Rrz0
Nov 22 '18 at 14:31
@AnderBiguri
imageDatastore
holds the actual image and not the pixel lables for that image.– Rrz0
Nov 22 '18 at 14:31
add a comment |
1 Answer
1
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oldest
votes
The answer can be found here.
Matlab 2017a
Go to the APPS tab, and search for Image Labeler
, or Training Image Labeler
Click on Add Images
to add your training images.
Click on Add ROI Labels
to add class names for the regions of interest.
Proceed to select the regions of interest manually from the uploaded images.
Once areas are selected, the data can be exported to workspace as a Ground Truth object.
add a comment |
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1 Answer
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active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
The answer can be found here.
Matlab 2017a
Go to the APPS tab, and search for Image Labeler
, or Training Image Labeler
Click on Add Images
to add your training images.
Click on Add ROI Labels
to add class names for the regions of interest.
Proceed to select the regions of interest manually from the uploaded images.
Once areas are selected, the data can be exported to workspace as a Ground Truth object.
add a comment |
The answer can be found here.
Matlab 2017a
Go to the APPS tab, and search for Image Labeler
, or Training Image Labeler
Click on Add Images
to add your training images.
Click on Add ROI Labels
to add class names for the regions of interest.
Proceed to select the regions of interest manually from the uploaded images.
Once areas are selected, the data can be exported to workspace as a Ground Truth object.
add a comment |
The answer can be found here.
Matlab 2017a
Go to the APPS tab, and search for Image Labeler
, or Training Image Labeler
Click on Add Images
to add your training images.
Click on Add ROI Labels
to add class names for the regions of interest.
Proceed to select the regions of interest manually from the uploaded images.
Once areas are selected, the data can be exported to workspace as a Ground Truth object.
The answer can be found here.
Matlab 2017a
Go to the APPS tab, and search for Image Labeler
, or Training Image Labeler
Click on Add Images
to add your training images.
Click on Add ROI Labels
to add class names for the regions of interest.
Proceed to select the regions of interest manually from the uploaded images.
Once areas are selected, the data can be exported to workspace as a Ground Truth object.
edited Nov 29 '18 at 7:26
answered Nov 22 '18 at 19:42
Rrz0Rrz0
487518
487518
add a comment |
add a comment |
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1
Isn't that what the tutorial does just there after the last line you got from it?
– Ander Biguri
Nov 22 '18 at 10:29
Actually, this is what exactly happening at
pxds = pixelLabelDatastore(pxDir,classNames,pixelLabelID);
– Nouman Riaz Khan
Nov 22 '18 at 13:19
@NoumanRiazKhan but
pxDir
loads the pixel labeled image, and that is what I'm asking about. How would one go about creatingmyCustomPixelLabels
– Rrz0
Nov 22 '18 at 13:42
@AnderBiguri so imds = imageDatastore(imDir); represents the image data where I need to label the pixels? How would this look like since
imageDatastore
is usually used to manage a collection of image files.– Rrz0
Nov 22 '18 at 13:53
@AnderBiguri
imageDatastore
holds the actual image and not the pixel lables for that image.– Rrz0
Nov 22 '18 at 14:31