image-segmentation Questions
2
How do you compute the top k accuracy in semantic segmentation? In classification, we might compute the topk accuracy as:
correct = output.eq(gt.view(1, -1).expand_as(output))
Dikmen asked 25/12, 2019 at 3:29
3
Solved
I have an image in RGB and another segmented image in which the pixels have 3 values(segmented image). I want to overlay the segmented image on top of the main image as the segmented areas make con...
Briquet asked 20/8, 2019 at 15:12
2
I have the following image:
and I would like to fill in its contours (i.e. I would like to gap fill the lines in this image).
I have tried a morphological closing, but using a rectangular kerne...
Cathead asked 21/1, 2015 at 23:4
2
Solved
I'm throwing this out there in hope that someone will have attempted something this ridiculous before. My goal is to take in an input image, and segment it based upon the standard deviation of a sm...
Polymerization asked 12/7, 2012 at 16:40
3
Solved
I am using Tensorflow as a backend to Keras and I am trying to understand how to bring in my labels for image segmentation training.
I am using the LFW Parts Dataset which has both the ground trut...
Euchre asked 18/7, 2017 at 23:8
1
Solved
I have a 2D color image and a label image (projection of labels)
The output of label image is as follows:
[[16 16 16 ... 16 16 16 ]
[16 16 16 ... 16 16 16 ]
[16 16 16 ... 16 16 16 ]
...
[ 2 2 2...
Larger asked 20/10, 2020 at 2:22
1
Solved
I'm using the code below for segmenting the articles from an image of newspaper.
def segmenter(image_received):
# Process 1: Lines Detection
img = image_received
gray = cv2.cvtColor(img, cv2.CO...
Mariomariology asked 7/10, 2020 at 10:8
4
How to compute the mean IU (mean Intersection over Union) score as in this paper?
Long, Jonathan, Evan Shelhamer, and Trevor Darrell. "Fully Convolutional Networks for Semantic Segmentation."
Fishmonger asked 27/7, 2015 at 12:50
2
Solved
The following is a small snippet of my code. Using this, I can train my model called 'lolnet' on cityscapes dataset. But the dataset contains 35 classes/labels [0-34].
imports ***
trainloader = ...
Ambi asked 18/6, 2019 at 13:23
2
Solved
I have a Talmud page like these:
And I want to find the text areas with opencv to get such a result, that each text will be on its own like this:
In the attached image, each area is marked in a ...
Bricklayer asked 12/9, 2020 at 21:50
2
Solved
I am SUPER new to python coding and would like some help. I was able to segment each cell outline within a biological tissue (super cool!) and now I am trying to find the centroid of each cell with...
Archfiend asked 18/7, 2020 at 14:39
2
Solved
Consider the following image, stored as a numpy array:
a = [[0,0,0,0,0,1,1,0,0,0],
[0,0,0,0,1,1,1,1,0,0],
[0,0,0,0,0,1,1,0,0,0],
[0,0,0,0,0,0,0,0,0,0],
[0,0,0,0,0,2,0,0,0,0],
[0,0,0,0,0,2,2,0,...
Manicure asked 9/7, 2020 at 8:43
2
Solved
I am using OpenCV in Python to be able to identify only the Leaf presented on the image. I already be able to segment my image, and now I am currently stuck at "how to crop the largest component af...
Briggs asked 1/11, 2017 at 13:17
0
I have the following formula to extend the mathematical expectaion of the original random walk algorithm which is already implemented in SciKit-Image segmentation.
I tried to implement the Guided ...
Secretive asked 3/5, 2020 at 10:50
4
Solved
I used Keras biomedical image segmentation to segment brain neurons. I used model.evaluate() it gave me Dice coefficient: 0.916. However, when I used model.predict(), then loop through the predicte...
Puerile asked 10/6, 2017 at 18:28
2
Solved
I have a binary image of a brain. I only want to leave the blob in the center and remove the surrounding "noise" that is in this circular looking shape.
Here's an example image:
I tried using O...
Anabolite asked 13/6, 2019 at 23:26
2
I am using a Unet based model to perform image segmentation on a biomedical image. Each image is 224x224 and I have four classes including the background class. Each mask is sized as (224x224x4) an...
Stancil asked 16/2, 2020 at 20:52
1
Solved
I have pictures of apple slices that have been soaked in an iodine solution. The goal is to segment the apples into individual regions of interest and evaluate the starch level of each one. This is...
Indoeuropean asked 10/2, 2020 at 22:44
1
Solved
As I was training UNET, the dice coef and iou sometimes become greater than 1 and iou > dice, then after several batches they would become normal again.
As shown in the picture.
I have defined...
Calamitous asked 6/2, 2020 at 8:14
3
Solved
How can I make these lines connect at the target points? The image is a result of a skeletonization process.
I'm trying to segment each line as a region using Watershed Transform.
Sibilate asked 9/5, 2017 at 1:48
1
Solved
I must be getting something terribly wrong with the fast-ai library, since I seem to be the only one having this problem. Everytime I try the learning rate finder or training the network, it gives ...
Glogau asked 29/12, 2019 at 15:25
2
Solved
There is a famous trick in u-net architecture to use custom weight maps to increase accuracy. Below are the details of it:
Now, by asking here and at multiple other place, I get to know about 2 ap...
Neoterism asked 14/10, 2019 at 13:28
1
Solved
I have an image segmentation problem I have to solve in TensorFlow 2.
In particular I have a training set composed by aerial images paired with their respective masks. In a mask the terrain is col...
Momently asked 11/12, 2019 at 19:45
2
I am using bounding box marking tools like BBox and YOLO marker for object localisation. I wanted to know is there any equivalent marking tools available for image segmentation tasks. How people in...
Araarab asked 20/11, 2019 at 12:0
1
Solved
I’m currently exploring how to apply Dice metric to a multiclass segmentation problem with fastai. I checked the concepts and discovered that Dice is really similar to the F1Score. Following this, ...
Goosestep asked 19/11, 2019 at 20:11
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