Questions tagged [image-segmentation]
The image-segmentation tag has no usage guidance.
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Interactive image segmentation training tool
I have a bunch of 2D grayscale images for which I want to train a (multi-label) segmentation model. What is the simplest way to interactively train such a model?
I.e., I want to:
Label a (very) few ...
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How to Prepare Data for U-Net Model Training with .tif Images
I'm new to image segmentation and trying to train a U-Net model. I have a dataset consisting of .tif satellite images and their corresponding annotations. Here is a sample of my data:
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Force a single sonnected set for segmentation model using U-Net
I have a simple U-Net model for 2 classes, binary, image segmentation.
The classes are background and an single object.
The object is a connected set.
Namely the mask is a single blob of pixels with ...
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How to train and test a weed detection algorithms using drone data
I have come across a weed database with labels and annotations for cotton weeds that was captured by a drone. Now I want to train and test the dataset which can be found here (Weed database). I do not ...
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Muticlass segmentation with missing labels for some classes
I have a training data where images contain cats, dogs or both.
Segmentation masks are provided.
But for the images which contain both animals- only one class is annotated and other is ignored. Some ...
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DBScan for image segmentation and clustering: how does it work?
I think I have understood the DBScan algorithm for 2D data points. We can consider the example in scikit-learn. They generate a set of data points:
...
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How specific should I be with my region of interest in image data for training a CNN model for better accuracies?
I am trying to train a 3D CNN model for classification of cancer stages on a dataset that comprises of head to neck CT image series which is split into 5 classes corresponding to the stages of cancer....
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How does the segmentation in YOLO v8 model work?
I know how YOLO models work for object detection.
I wonder what gave the YOLOv8 the ability to apply segmentation at the pixel level.
Is there a clever trick? How does it compare to other models like ...
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Segment a spectrogram into a series of images by (constant) beats per minute to train a Deep Neural Network
I have a .csv file with information about a soundtrack and it is divided into beats (per minute), which are ordered by row. As in: the index corresponds to each beat, and the columns have info about ...
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Can a multi-task model work on conditions for each layer?
I am currently working on a multi-task model that needs to handle car detection, damage segmentation and license plate ocr.
my idea was to only run the OCR layer when there is a license plate detected ...
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HCC-TACE-datase
Is anyone worked with CT images. I am having problem in dicom images. I want to make a similar slice for all my segmentation image and liver image. Is there any tutorial or suggestion for that?
Thank ...
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What are the most important evaluation metrics for anomaly segmentation?
When people talk about anomaly segmentation models, they often mention evaluation metrics like F1 score, AP, AUROC, and AUPRO. But which one really matters most when comparing models, and why? I'm ...
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Tensorflow SegNet architecture
I was unable to find a complete description of the SegNet architecture for image segmentation (specifically, the decoder layers). Therefore, I would like to clarify the correctness of my ...
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Losing Information while resizing the image in Segmentation task using U-net
I'm using U-net architecture to build a segmentation task of image. During training I have image of size 256256 image. It works very well on the segmentation of same size 256256 or near to size 256*...
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Is there any standard or heuristic for deciding on the dimensions and filters of a convolution layer for image processing?
I reposted this from StackOverflow since it does not meet StackOverflow's guideline to focus on programming and coding questions. Link to the original question.
I want to find ways other than trial ...
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IoU metric for multi class image segmentation task
My input shape is of (168,18). I create batches of size 256 and create my dataset using timeseries_from_Array_dataset. I am visualizing this 2D snapshot of a multivariate timeseries (batch size- 256, ...
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Why is there a difference in Training Accuracy Output, when the training dataset is the same but the validation dataset is different?
I am looking at the output of a multi-class image segmentation deep learning model. I used U-Net to implement this.
I am confused about why the training accuracies are different for a different ...
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What are good ways to extend an ML model with a new class without relabeling all previous data?
I have a segmentation model trained using 1,000 images that can predict 4 classes (dog, cat, mouse, elephant). I would now like to extend the model with a 5th class (horse).
Horses are present in the ...
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K means clustering of image with k=1 vs mean of all pixels
I have relatively uniformly colored images and I extracted colors using k-means. k means 1 showed the best results for my modeling purposes, k means 2 not so much, and with k-means 3 there ceased to ...
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Is it possible to calculate mAP metric for semantic segmentation task?
I want to calculate mean average precision metric for my semantic segmentation models.
Because I want to compare metrics this models with yolov8 instance segmentation model.
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Image segmentations vs image detection
If I need to detect on an image some objects and we are only interested in counting them, between image segmentation and object detection which one would you think would yield best results in terms of ...
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CNN segmentation models: class weights specification on IoU metric
I am building a MANet model using pytorch lightning. For getting the model I use the library segmentation models. As my objective is to do binary semantic segmentation, during the test phase I ...
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48
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Can unsupervised pretraining (autoencoders) be used for u-nets?
TLDR: Will a u-net pretrained as an autoencoder be able to learn a latent representation of the data if the encoder weights are frozen (can't game the system and pass forward the unmodified image)? ...
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Using AWS Sagemaker (Ground Truth) for Labeling Jobs + Rekognition. How best to approach my project?
I'm new to ML so bear with me. I want to create an object detection model that can detect anything from flags (e.g. Israel flag) to symbols (e.g. yin-yang sign) to a giving setting (e.g. war).
I am ...
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Extracting values from a map image (jpg)
Not sure if this is the right platform but I'm in a bit of a fix here.
I'm trying to convert this image(jpg) to a raster wherein, the colormap attached shows the values. I'm aware I need to use openCV ...
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47
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How can you add additional features/attributes while doing instance segmentation?
I want to do an instance segmentation of objects in images.
Usually I would stick to something like an Mask R CNN and let it run. However additionally to the image itself and the pre-labeled images, I ...
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Pretrained computer vision models that accept as input a segmented image and the original image
My data is a set of segmented images with extra details:
there is 30 object classes
each object is labeled with its state (very old, old-fashion, modern)
and each object is also labeled with a second ...
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Discrepancy in the measured metrics in my segmentation models
I’ve trained my image segmentation models using SegmentationModelsPytorch. Three annotators marked up objects. All pixels that were voted as an object pixel by two annotators were marked as the pixels ...
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How do I get SAM to perform multi-class classification?
I want to use the Segment Anything Model(SAM) to perform multi-class segmentation on satellite images. When I tried to apply it, it ended up giving single-class outputs. Moreover, upon applying a ...
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What Deep Learning model to use in this spectroscopy task?
I have a task to be solved. There are energy measurements over the square area 40x40. One measurement consists of values : x, y and the energy. The all area is almost whole covered with data (a few ...
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Custom Loss Function in Tensorflow for UNet
I am working on a Segmentation task, where I planned to use U-Net
for the input_image of shape (224,224,3), the output should be the mask image of shape ...
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MaskRCNN.train gives 'list index out of range'
I have been trying to use MaskRCNN with a Resnet backbone on the DeepFashion2 Dataset for instance segmentation. The custom configurations are as follows:
...
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What preprocessing should I do to a multiclass segmentation mask?
I am working on a segmentation problem. My masks are tensors with a shape of (4767, 192, 192, 1) --> (num_img, height, width, number of channels). Each mask contains 13 different pixel values (0, 1,...
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Meta's SAM model: can extract semantic embedding vector?
I'm interested in finding an embedding vector for each segment found by the Facebook/Meta Segment Anything model (for classification and tracking of segments).
Can ...
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Can I use one-hot encoded output for segmentation in Pytorch, with focal and dice losses?
know that for classification using a neural network and CrossEntropy Loss, we need one-hot encoded output, but in PyTorch, the CrossEntropy loss does not accept one-hot encoded targets, and we should ...
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Train multiple models to predict subsets of classes in data
If you are aiming to predict a number of classes that may be too high for the available data, is there any merit to training multiple models to predict a subset of the classes, each, and combining the ...
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Why is my segmentation model not returning a heat map?
I have implemented two CNN architectures to perform segmentations on medical images: the classic UNet and a modified version called the Attention UNet. I have been training the models on roughly 50,...
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Obscured object segmentation in binary segmentation
I am using deep learning for building outline segmentation. I have used binary segmentation method using UNet model which runs on Tensorflow 2.0. The output is fine when there are no other object (Ex. ...
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Tensorflow Text Segmentation or Open CV Text Segmenation
I want to extract text data from the image, however not sure what approach I should take.
Steps successfully performed
Dataset collection
Image Preprocessing done
Image Augmentation done
Final Image ...
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Choosing the right Deep Learning Model for Image Segmentation
How do you choose the appropriate Deep Learning Algorithm if you wanted to do image segmentation with an image datset which consist of hispathology images of almost 10000? I'am new to deep learning ...
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Mark up text as instance segmentation or semantic segmentation?
I have data with a page of handwriting and I want to segment each word individually. If I mark each word for semantic segmentation, then the model will impose a segmentation mask on each word ...
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Is my image too low res for semantic segmentation task?
I am trying to solve a semantic segmentation task in the field of agriculture and I have some ortophoto drone images that have been acquired at the same height above the crops and in different ...
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Which deep learning model is best in terms of instance segmentation and Object detection both?
I am trying to find most efficient and robust Object detector+Segmentation model. I came to know about Mask-rcnn, Yolov5, Yolact, yolov7.
As, YOlov7 is new and i read somewhere that yolov7 surpasses ...
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Applyingv a 2D mask onto a 3D rgb color list
Problem
I have the following image data as a 3D numpy array containing rgb values of the image in a (n,n,3) shaped list (Image). I also have data of the corresponding black and white mask image in a (...
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Certain Image Augmentation Prevent Unet Model from Learning
I am training a Unet model for cell image segmentation from microscopy images. In order to help the model generalize better to different microscopes, I attempted to apply brightness augmentation to ...
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Can you use a trained image segmentation model to label more training data for itself?
Labeling images for semantic segmentation can be expensive. Is it viable to train a model (such as Unet) to a good accuracy and then use this model to label more images to be used as further training ...
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Is batch size of 1 a valid choice for a very deep neural network with high memory requirement?
I am training a very deep neural network (Panoptic-DeepLab) with a ResNet34 backbone on Google Colab on CityScapes dataset for Panoptic Segmentation, and noticed that, with a big crop size, the batch ...
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Are more target labels in a multi-label classification always better?
Context
We work on medical image segmentation. There are a lot of potential labels for one and the same region we segment. There can be different medically defined labels like anatomical regions, more ...
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how to label 3d model for segmentation task
I'm working on 3d meshes dataset, i have to label it to train my deep learning model for a segmentation task like the picture shows.
I spent days looking for a tool to label my 3d data but ...
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Post processing in medical segmentation with attemtion unet
I am doing a lesion segmentation for multiple sclerosis (MS), and at the moment I am using a attention unet for my thesis. The best validation dice score I have recieved is 0.771 and train 0.84. I am ...
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