Questions tagged [image-segmentation]

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Is it possible to create a 3d to 2d U-net?

I was curious if it is possible to create a U-net type architecture that takes in a 3d image and outputs a 2d image? Or, alternatively, would some other architecture be better suited for this problem? ...
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8 views

Which colour channel from a TIFF image do I have to use?

I'm going to use the following dataset to do semantic segmentation with U-Net network. LGG Segmentation Dataset This dataset contains brain MR images together with manual FLAIR abnormality ...
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Multiple output size in neural network

In the paper "A NOVEL FOCAL TVERSKY LOSS FUNCTION WITH IMPROVED ATTENTIONU-NETFOR LESION SEGMENTATION" the author use deep supervision by outputing multiple outputmask which have different ...
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21 views

Why does dice coefficient equally weigh false positive and false negative?

According to this article: Dice coefficient= The 2-class DSC variant for class c is expressed in Equation 1, where gic ∈ {0, 1} and pic ∈ [0, 1] represent the ground truth label and the predicted ...
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Image segmentation network to extract questions from an image of a test paper?

This is the sample document -> I want to extract questions along with the options. There are other question papers as which have questions with diagrams in them. I want to be able to extract them ...
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How to determine the decrease of resolution in per cent necessary for a partly blurred frame to appear sharp?

Given is a frame of a video taken with a lens focussing on the background, so the foreground is slightly blurred. How to determine the decrease of resolution in per cent necessary for the blurred ...
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How to approach coarse-grained semantic segmentation?

I’m looking at doing something like semantic segmentation of images but where I only have pretty coarse-grained labels - roughly, for each 32x32 patch, I know if the answer should be “yes”, “no” or “...
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DICE loss too low but no overlap between prediction and label

I am trying to achieve the segmentation of the bone on the cross sectional area of MRI images with the Unet I found here. The label is a binary png image which I intend to compare to my prediction. ...
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27 views

How to deal with severe overfitting in a UNet Encoder/Decoder CNN in a task very similar to image translation?

I am trying to fit a UNet CNN to a task very similar to image to image translation. The input to the network is a binary matrix of size (64,256) and the output is of size (64,32). The columns ...
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Image Segmentation Class weight using tensorflow keras

I remember definitely being able to pass a list to class_weight with keras (binary image segmentation specifically). For example: ...
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Segmentation-free character recognition on an image: Multi-label, multi-class or sequential image classification problem?

I have some images which look like this one: They exist of 3 possible characters (A-C) and a length of 4. Now, I would like to run a neural network, which recognizes each character in the picture ...
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63 views

neural network probability output and loss function (example: dice loss)

A commonly loss function used for semantic segmentation is the dice loss function. (see the image below. It resume how I understand it) Using it with a neural network, the output layer can yield ...
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What is the difference between proposal-based approach and proposal-free approach?

From here it says that Techniques to solve instance segmentation can be roughly grouped into two categories: proposal-based methods and proposal-free methods. In proposal-based methods, a set of ...
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How to reduce the detection time in MaskRCNN

I've trained MaskRCNN in GPU instance and using the saved weight, I detected it in CPU instance based system. The detection time is taking too long. ...
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5 views

Refining segmentation masks using predictions of earlier frames

I am performing semantic segmentation. For that I have a dataset of videos in which every frame is labeled. Unfortunately, I don't know the order of the frames. That is why I am performing classic ...
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per class IOU & Jaccard Similarity in a Multiclass setting python

For a multiclass classification problem, How do you compute per class IOU ? I am using the formula which is referenced/accepted in the below link ...
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Confusion matrix of UNET image sgemenation model

I have used Unet model for image segmentation. I have used RGB images and corresponding image masks and at output i got corresponding region of interest. Now i want to find confusion matrix of this ...
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Is it possible to find corresponding coordinates from a downsampled image?

Beforehand, I must apologize, I am just a beginner in image processing and I am not very familiar with many computer vision operations. Here is my problem: I am using deep learning to perform a ...
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Drawing bounding rectangle around the tumor cv2

I am working on a project which predicts that the MRI has tumor or not, now the next step is to draw a bounding rectangle around the tumor. I want to extract the tumor from the MRI and bound the ...
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38 views

How to save multi-output predicted masks into two different folders after using model.predict_generator

I have a multi output segmentation task, the training process went well, but when Im trying to get the prediction I found difficulties to separate the two output into two different folders, in my ...
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24 views

how to compare two images and show the difference in a new image?

I want to compare two web pages images using computer vision techniques. show what are non-unique portions comparing both images. which part image1 not exist in image2 vice versa.
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Multiple RoI per object of interest to train U-Net

I have determined RoI of image that contains an object (an organ on a CT-SCAN) that I wish to segment using a U-Net like network. Should I train my network with the RoI I determined, or should I use ...
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Paragraph extraction from text

I am trying to separate scanned pages of a 3 column book into paragraphs. On the pages there can be images located in an arbitrary location, occupying part of one, two or all three of the columns. ...
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24 views

Is weighted jaccard metric suitable for semantic segmentation?

I'm trying to deal with a binary segmentation peoblem using Unet on Tensorflow 2.0 (Keras module). My classes're higly unbalanced, so I have to use class weights (0.03 for background and 1.0 for ...
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1answer
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Is it cheating to stratified sample the whole dataset based on a previous evaluation result?

I trained a model using a small mri dataset(57 patients). The model's performance was so low(Train set 0.7, Val set 0.7, Test set 0.45). I found the model segment tumor in upper part of brain well, ...
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How to prepare masks for multiclass semantic segmentation?

It's very straightforward for binary semantic segmentation: black color (0s) is responsible for background, whereas white color (1s) is responsible for objects of interest. But what about multiclass ...
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Instance segmentation and scene reconstruction

I've been recently interested in various segmentation tasks especially instance segmentation. Having been experimenting with various different datasets I stumbled upon using the method for indoor ...
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Image segmentation for small images with rectangles

I am doing toy project and trying to make image segmentation for rectangles generated in small images. Here the code: ...
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1answer
78 views

Segmentation Network produces noisy output

I've implemented a SegNet and SegNet ReLU variant in PyTorch. I'm using it as a proof-of-concept for now, but what really bothers me is the noise produced by the network. With ADAM I seem to get ...
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15 views

Guidance required on image segmentation

I am new to deep learning. Specifically to image segmentation. I am trying to localise object from satellite images (screen grab from google maps). When I am going through articles/blogs in the ...
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1answer
36 views

What are features in computer vision?

I'm learning how U-NET network works to do semantic segmentation. I think I have understood everything but features. What are those image features? I read that convolutional layers extract features ...
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1answer
104 views

Patch wise training vs Full Convolutional Training in semantic segmentation

As mentioned in the title, what are those 2 methods? I already checked this question: Patchwise and Full training, (and the mentioned paper) but i can't really understand the meaning and the process ...
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78 views

Use of Active contour loss funtion in U-net

I am using a custom loss function named 'Active contour loss'.(https://github.com/xuuuuuuchen/Active-Contour-Loss/blob/master/Active-Contour-Loss.py) I am getting an issue while segmentation. I have ...
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21 views

Video segmentation vs image segmentation

I am new to data science & working on a segmentation model, Basically I need to deploy this segmentation model in android devices using TensorFlow-Lite for real time camera frame segmentation. I ...
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An CNN seems like capturing specific range of input data. (Image Segmentation)

I'm trying to build a model to segment brain tumors. I trained a model, and the validation dice coefficient is disappointing(0.6). When i saw the predicted images with the ground truths, it seems ...
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Is there a way to test out simple filters before committing to coding them?

Is there a way to test out simple filters before committing to coding them? Like if I want to estimate the feasibility of recognizing some features from images. Or to estimate the effort/...
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1answer
40 views

Google Earth Pro Satellite image segmentation using clustering

I have downloaded a satellite image from Google Earth Pro software corresponding to a particular date for a selected area around a place. I want to specifically segment the road lanes from the image ...
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1answer
153 views

How does the “skip” method work for upsampling? (fully convolutional NN)

I'm studying fully convolutional neural networks for image segmentation, so far i've study and kind of understood the deconv network. Following this tutorial (Upsampling) i can't really understand how ...
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1answer
12 views

Tools suitable for semi-automatic video labeling?

So far I have been using labelme to label objects in videos I use for training, but it is quite time consuming. Are there good tools to help with that? I was thinking about a tool where I label ...
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Splitting a pdf containing batch of scanned documents

My question is primarily: is there any ML research paper about splitting a pdf containing a batch of scanned documents (eg bank statements) into individual documents? I have searched for this but I ...
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Why is my Keras model not learning image segmentation?

Edit: as is turns out, not even the model's initial creator could successfully fine-tune it. This is most likely a problem of implementation, or possibly related to the non-intuitive way in which the ...