Questions tagged [image-segmentation]

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Number classes in tf.keras.metrics.MeanIoU for one class in image segmentation why must set num_classes = 2? What difference between this and IoU?

I train U-Net model for audiometric CT image segmentation. I have one class in train data set and test data set (such as bladder). At the first time I set tf.keras.metrics.MeanIoU in model.fit, I set (...
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13 views

Computing symmetric difference hypothesis divergence $H \Delta H$ for two domains using a segmentation network

Given two domains $D_1$ and $D_2$, the symmetric difference hypothesis divergence ($H \Delta H$) is used as a measure how much two domains differ from each other. Let the hypothesis, segmentation ...
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1answer
39 views

Correct way of computing dice score for image segmentation?

In binary image segmentation, for given a set of images, it's true mask and predicted mask. How do you compute dice score? Should I compute the dice score for each image separately and then find mean ...
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1answer
24 views

How to design a model for contour recognition? In particular, how to shape the output layer?

I want to design and train a neural network for the automatic recognition of the edges, in some microscopic images. I am using Keras for a start, I may consider PyTorch later. The structure of the ...
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1answer
16 views

How to resize image along with their mask?

I have original images of the size 1935x1481. I am using labelme to annotate the images. I am creating polygons on the original image. Is there a way to resize the image along with their mask? I am ...
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6 views

How to check if 2 images where splitted?

There is an original data-set of images. Each image was splitted into 2 parts (left-right). I want to run on all those splitted images and check if each 2 images are spliited from same image. Is ...
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1answer
75 views

How can I create .nii (nifti) file from 3D Numpy array

I have a prediction numpy array. How can I make a .nii or .nii.gz mask file from the array?
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23 views

Transfer Deep Learning from one aerial imagery datset to many others

I am new to Deep Learning but have been able to use RasterVision successfully to predict building footprints within a set of aerial imagery. This aerial imagery data set is for a province of New ...
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1answer
14 views

Segmentation model to predict face forward and profile parts of the face

I am developing a model for feature counting on a person's face that consumes three photos (one face forward and two profile pictures). My model can already detect features, but it counts some ...
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1answer
26 views

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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428 views

How can I use my own dataset for Image segmentation using Tensorflow

I have a huge problem using my own created dataset for image segmentation using Tensorflow. The dataset that I've build contain images like the one shown below: The problem that I have is: How do I ...
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17 views

Instance Segmentation using the predefined bounding boxes

I want to do Instance Segmentation using the images in my dataset which are already annotated and I don't want to train the model but use the pre-trained model. I was following this colab notebook. ...
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1answer
74 views

Tool for annotation of images for semantic segmentation

I have been searching around for a software tool, that I can use for annotating images. More specifically I want to do annotation to be used for semantic segmentation, meaning I want to create masks. ...
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1answer
129 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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1answer
12 views

Why do we need to concatenate in a U-Net?

You might be familiar with the U-Net, a machine learning network deceived for image segmentation. It's basically an encoder/decoder network with some direct links between encoder and decoder segments: ...
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21 views

Beginner level: how to interpret LIME and classification result

I am new to the concept of model interpretability using LIME method. I am following the tutorial LIME for spectrogram classification. I am finding hard to understand the color coding -- before using ...
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1answer
349 views

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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24 views

How to use mean IoU for RGB mask (keras implementation)?

I am training pix2pix GAN for converting SAR satellite images to segmentation mask. But I am not aware about how to use the mean IoU to evaluate my model. My output is of ...
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44 views

Best algorithm for real-time instance segmentation in videos?

I want to do object detection in real-time (meaning localization and classification) on videos (25 FPS), but with the added constraint that my training data is labelled using binary masks, rather than ...
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1answer
18 views

3 images as one input in CNN (U-Net) [closed]

I have been advised by my supervisor that if my U-Net segmentation network has RGB images at the input then I could use the channels for different images - median filter for R, normalization for G, ...
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1answer
37 views

Ways of calculating the area of colored regions in a map

Background I am a PHD student trying to improve my data science. One of my research projects, has me tasked with determining the size of the clusters in a colored image of regions. Here is an example ...
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1answer
19 views

Semantic segmentation in high-resolution images with high variance - cannot avoid underfitting

I am working on a dataset of 2K images for a semantic segmentation problem. I want to detect and localize small objects, with the smallest mask to be 5x5 pixels. The images include 5 different ...
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1answer
607 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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1answer
57 views

Modifying U-Net implementation for smaller image size

I'm implementing the U-Net model per the published paper here. This is my model so far: ...
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1answer
89 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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1k views

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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U-Net doesn't work with images different from the dataset

I have implemented a very similar U-Net code from github, but for a different dataset, this one, to segment roads, it works fine using the test folder images, but when i for example, pick a print from ...
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1answer
27 views

Implementing U-Net segmentation model without padding

I'm trying to implement the U-Net CNN as per the published paper here. I've followed the paper architecture as closely as possible but I'm hitting an error when trying to carry out the first ...
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8 views

Instance segmentation mask creation for adjacent objects within the same class

How are instance segmentation masks created for adjacent objects from the same class ? If for example we have different objects, we can distinguish between them using the labels, but how to ...
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1answer
19 views

Photorealistic synthetic data for object segmentation

Let's say that we have a very small labelled dataset for instance segmentation and there is a photorealistic physics engine available that can produce synthetic data for us. Looking on the web I haven'...
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7 views

Boundary segmentation

I have one problem regarding segmentation. I would like to put more concentration on the boundary instead of the interior of segmented part. Is that possible to do using Tensorflow 2? For example, if ...
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1answer
35 views

Comparing two images and showing the difference in a new image?

I would like 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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1answer
135 views

Normalization of CT scans

I trained an infection segmentation models on a large dataset of CT scans, and want to extend it to other datasets to show the ability of the model to generalize. What I found though, is that CT scans ...
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15 views

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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10 views

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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197 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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95 views

How do you deal with variable input sizes with an encoder-decoder net with skip connections in Keras?

I am currently getting into image segmentation with Keras, and I am using an encoder-decoder type as in the image below. My problem is that applying a MaxPooling2D ...
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1answer
67 views

Creating parallel keras layers

I am new to Keras and ML and I want to create a NN that can seperate a bitmap-like image into its visual components. My approach is to feed a two dimensional image (lets say 8 by 8 pixels) into a NN, ...
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1answer
88 views

What is Deep learning approach to count the number of Diamonds in an image?

I am working on a project which involves counting the number of diamonds in the provided image. I have a set of images and a VIA annotated .json file which has all the annotations. How do I proceed ...
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17 views

Changing order of input dimension in Tensorflow 3-D Layers

According to the official documentation of tf.keras.layers.Conv3D 5+D tensor with shape: batch_shape + (channels, conv_dim1, conv_dim2, conv_dim3) if data_format='channels_first' or 5+D tensor with ...
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1answer
17 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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31 views

Agglomerative Hierarchical Clustering on Images

My goal is to implement the agglomerative hierarchical clustering algorithm on an RGB image to cluster every pixel until some stopping criteria is reached. In order to do so, I assumed that each pixel ...
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12 views

Semantic segmentation to instance segmentation

Having a mask from semantic segmentation I want to split it to list of non-overlapping instances masks(like an output from instance segmentation). Do you know some fast algorithm, approach, tool or ...
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1answer
25 views

What do the parameters used in crop mean?

When we have an image to be used as an input to a CNN and we want to classify only part of the image, we usually feed the classifier with a crop of the image. Lets say my image is called frame and <...
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11 views

I have no access to gpu due to usage limits?

I start running my code using google colab I first set the execution to GPU and then I run my code for a training task using keras !after 1 hour I got a message saying I can't use GPU due to usage ...
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135 views

Implementing Multiclass Dice Loss Function

I am doing multi class segmentation using UNet. My input to the model is HxWxC and my output is, ...
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14 views

Satellite Change Segmentation using Unet

Hi StackExchange community I am working on to train a Unet for satellite change segmentation. My dataset consists of images(before change),images(after change) and the corresponding change ...
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11 views

How to generate fixed number of superpixels?

A lot of work regarding Graph Neural Networks require fixed number of nodes. In the case of image processing using graph, the image representation is often super pixels (like in this work https://...
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16 views

Loss function to compare non binary segmentation

I need to compare two images corresponding to landmark locations. I was thinking of something related to Dice loss. I cannot use dice loss since the image is not binary. The background is black but ...
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1answer
171 views

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 ...