Questions tagged [image-segmentation]
The image-segmentation tag has no usage guidance.
93
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22 views
How to measure temporal instability of a segmentation model?
I have several segmentation models, which were trained using image data (and not video).
Some of them provide higher IoU, but when applying them to video frames (one after one) - there is a lot of ...
0
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1answer
17 views
How to get the expected output shape from a unet model?
I have an image segmentation task where my input image shape is (140, 85, 95, 4) and the output label shape is (140, 85, 95). Below is my model:
...
1
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1answer
41 views
ValueError: Data cardinality is ambiguous: (Jupyter Notebook)
I'm building an OCR to read text off of water meters. I'm running into the error mentioned above when I try to fit the machine learning model. I am using the segmentation_models python library.
...
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21 views
Deep learning - edge detection
I am trying to build a model, which would be used for edge detection of the iris.
For this purpose, I have built a U-net model, which successfully works for image segmentation tasks. Also, I have a ...
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35 views
Multi-task learning for improving segmentation
I am building a multi-task model, where my main task is segmentation and my auxiliary task is either denoising or image inpainting. The goal is to try to improve the quality of the segmentation with ...
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22 views
Which model is used for document extraction (CamScanner, Microsoft Lens etc)
I want to start a small project where I'd create a model(s) that would extract document from a picture and rescale it, something like CamScanner or Microsoft Lens apps do.
I've gathered a small ...
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14 views
What is the best Panoptic Segmentation algorithm up to date?
A Cityscapes ranking would suggest that EfficientPS and Panoptic-Deeplab are the best, while the Coco ranking suggests other algorithms, more recent, like mask2former.
Which one is the best?
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10 views
Scaling the output of a segmentation model (UNet)
So, I have to solve an instance segmentation problem and I am thinking of implementing a UNet model based on Ronneberger et. al. 2015 paper. The problem I have is that the output size has to be ...
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1answer
64 views
Yolov5 image detection without segmentation?
I have read a number of papers on Yolov5 images detection techniques. But the papers don't refers to any segmentation step done by Yolov5. While I know that it is not possible to do image ...
1
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1answer
24 views
How to preprocess heavy MRI images?
I have a large MRI dataset for an image segmentation task that cannot directly fit in memory in Colab, you can access the data with the link I put at the end. They are brain MRI images:
484 training ...
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15 views
Image Segmentation with Time Information
Lets say that I have a image showing cell tissue and I hope to segment the image to outline the healthy and unhealthy areas. This image is called the current image. I also have images taken an hour ...
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1answer
50 views
resnet50 implementation for semantic segmentation
I am new to resnet models.
I want to implement a resnet50 model for semantic segmentation
I am following the code from this video, but my numclasses is 21. I have a few questions:
If i pass in any ...
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18 views
How to extract specific region from black and white image using openCV
I have been trying to learn OpenCV as I have a deep interest in Computer Vision and one of the problems I have been trying to figure out is how to extract a particular region of an image with OpenCV. ...
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1answer
103 views
Algorithms to do a CTRL+F (find object) on an image
We all know the CTRL+F "Find text..." feature in text editors / browsers.
I'd like to study the available algorithms to do something similar on an image.
Example of UI/UX: let's say you have ...
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0answers
20 views
How to break a binary image mask into multiple masks?
I have image with binary mask. I want to break the binary mask into many individual masks of same dimension, but each mask should contain only one segmentation mask.
Is there a way to do it in python, ...
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7 views
If an FCN accept rectangular image as input or has to be square?
Some say that for FCN it doesn't matter if the input image is rectangular the only thing matters that the size must be constant ...
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1answer
20 views
Determining which deep learning model architecture is better
I am solving a specific segmentation task, using two versions of U-net architecture - the first one being classic U-net and the other Attention U-net. Currently, I am trying to determine which one ...
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19 views
What is the difference between dilated convolution and bilinear interpolation?
I started studying semantic segmentation, so I read some papers about image segmentation to clinical images using as main architecture, the u-net. Maybe because I am newer on the field, but I don't ...
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16 views
Does segmentation algorithms perform better in frequency domain than spatial domain?
I am implementing a published paper, where cellular region needs to be segmented from non-cellular region in a microscopic image of human cells.
In the paper LFT coefficients of each pixel are ...
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12 views
Why my encoder-decoder based segmentation model is producing high loss, when UNet/SegNet is working fine
I have got a UNet and SegNet model implemented on a dataset, with high mean-IoU and accuracy. Now I tried to implement SegNet(not FCN, just encoder-decoder portion) on the same dataset.
But for this ...
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0answers
32 views
Is there any way to remove background of an image fully with the help of post-processor techniques(like edge detector) after deep learning based model
I'm using a deep learning model (deep lab v3+ with xception as the backbone) for image segmentation and removing the background. The subject of the image is a person. And my target is to extract the ...
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27 views
Using Object Detection or Image Segmentation without labelled input data to build a dataset to then be manually labelled?
I'm looking to build an object detection model or image segmentation model, ideally the latter, which will identify and label objects from satellite imagery but I don't currently have any labelled ...
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1answer
51 views
Segmentation 3D Unet checkerboard artifacts in slices above and below segmentation voxels
I suppose an image is worth too many words, so here is the image:
As you can see, in the middle where there are voxels to be segmented, no artifacts are present. Whereas on the top and bottom I get a ...
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13 views
Clustering 3D image voxels based on their location and value
My goal is to detect whether a MRI image contains an anomaly and the location of the anomaly.
In my dataset I have MRI brain images which contain values of electrical conductivity of brain tissues.
...
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43 views
Image segmentation with cityscapes dataset
I am a beginner in image segmentation and am trying to use the code:
from dilatednet import DilatedNet
from multiclassunet import Unet
but get the error:
...
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0answers
26 views
Lovasz Softmax loss explanation
I would like to use Lovasz softmax for foreground background semantic segmentation because of its ability to improve segmentation with Jaccard index according to paper.
I got the idea that its a ...
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0answers
12 views
Can i segment/crop out image using image processing?
I have a large dataset of bottles. I want to train a model with this dataset. But before feeding the input images to the model I want to crop out the bottle from the background. Is there a way to do ...
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7 views
What is the input to CNN in this image segmentation paper?
I am doing a project on polyp segmentation in colonoscopy images. I have recently read the paper Polyp-Net: A Multi-model Fusion Network for Polyp Segmentation provided here.
I have a few question ...
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31 views
finding the defect button
In case of a project where you are going to detect whether the image printed on a button is correct or not and given that you have only a one correct possibility of a correct image and some incorrect ...
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11 views
Attention block versus residual block in U-net architecture?
I work on a project and I intend to use autoencoder (U-net) for my problem, based on the research that I've conducted, some authors used the recurrent residual U-net but I intend to use new approaches ...
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15 views
Should training and validation patches come from different images/files for image segmentation
In the situation where we have an image segmentation problem and we feed patches (smaller parts of the images) to the model, should the training and validation patches come from different files (...
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0answers
11 views
Can Dice Similarity index be higher than Jaccard index (Mean IOU) for a segmentation task? If so why does this happen?
I am currently doing a segmentation task. DICE is 0.94 and Mean IOU (Jaccard Index) is 0.63. How can mean IOU be lesser than DICE and is this possible. Also need explanations on scenarios where ...
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1answer
43 views
Hook up PyTorch U-Net model to video
I built a U-Net model in PyTorch that is trained on medical images to detect polyps. The purpose of the model is to do semantic segmentation, so it must predict the location + class of polyps.
Now I ...
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13 views
Detection of vortex and numbering on basis of rotation
Problem Statement: I have a video of ANSYS Simulation of vortices formed due to flat plate plunging. The video contains vortices (in simpler terms blobs), which are distinguished according to their ...
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46 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 ...
1
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1answer
28 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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0answers
7 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 ...
2
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0answers
25 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. ...
2
votes
1answer
21 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 ...
1
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1answer
181 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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1answer
151 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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0answers
29 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 ...
2
votes
1answer
36 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
48 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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0answers
36 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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0answers
66 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 ...
1
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1answer
61 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
728 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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1answer
92 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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0answers
17 views
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 ...
