Questions tagged [semantic-segmentation]
The semantic-segmentation tag has no usage guidance.
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For a fine-tuning a transformer to type like a specific person, should I use sentence semantic embeddings or word semantic embeddings
I'm not clear on the pros and cons of each one for this particular task. Is there even a meaningful difference?
My guess is using semantic embeddings for words will be better in nearly all cases ...
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Segregation of a finance interview based on topic discussed
I have a video interview of 5 people, which i have transcribed to text (example corpus given below). Considering the fact that we know SPEAKER_00 is the interviewer and rest are guests. I want to know ...
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Why does my video segmentation model predict only one value across the entire output array?
I'm working on a video segmentation model, inspired by UNet and VNet. I'm trying to benchmark the model by overfitting it on a single video (done with a 5e-4 learning rate on 5 epochs of 8 steps, with ...
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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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Different size of deep learning models but similar inference-time
I have three different semantic segmentation models with large differences in size. The first one includes 30,000,000 trainable parameters, the second one about 20,000,000 and the third one about 200,...
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Can segmentation algorithms like U_Net segment dents in bullets?
I have a dataset of images of bullets. These bullets are to be classified as OK and Not-OK based on the segmentation of defects on the surface of bullets and any dents in the body of bullets.
I am ...
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156
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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 ...
- 111
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250
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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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What is an appropriate output layer for a transformer based model for semantic segmentation of OCT images?
I am trying to use a transformer (not the vision transformer variation) for semantic segmentation of OCT images (grayscale images of the layers of the retina) of size h x w. The idea is to interpret ...
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Can invariance in CNNs hamper semantic segmentation?
As far as I understand, invariance is a property that is desirable for the CNN-based models. It helps us detect various objects even in different scale, position, rotation, etc. depending upon the ...
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Why can a 3x3 depth-wise convolution replace positional encoding in SegFormer?
Context
In the SegFormer Paper, the authors use 3x3 depth-wise convolutions instead of positional encodings with the following reasoning: "We instead
introduce Mix-FFN where we consider the ...
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Unsupervised vine trunk foreground segmentation
I'm currently working on a computer vision project for a vineyard robot. I trained a robust object detection for the vine trunks but now I need to apply semantic segmentation on the trunks so I can ...
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115
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What should the input be to an image segmentation model?
I have come across articles about different image segmentation models. Few of them mention to use the masked version of the image to get semantic segmentation. I wanted to know, is masking necessary ...
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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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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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Reusing a model, pretrained on 19 classes, for just one of those classes
I have a pretrained net for semantic segmentation, which has been trained on the cityscapes dataset and its 19 classes (Person, car, traffic sign, …). One of those is "Person". I am only ...
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Does Field of View in Camera affects the performance of Keypoint detection and semantic segmentation model?
I have two cameras to capture images for training keypoint detection and semantic segmentation model. One camera has smaller field of view and the other has larger field of view. Let's say, I capture ...
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Tensorflow 2 Semantic Segmentation - loss function for two classes
I am trying to implement a U-net for semantic segmentation with two classes (foreground=1 and background=0) in the segmentation mask images, following this tutorial.
They have used ...
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Do I have to set same batch size for training, validation and testing?
I was performing segmentation task and have set my batchsize to 16 for all train, validation and inferencing. In my observation, I got better result in inferencing when setting batch size to 1. How ...
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353
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how to visualize segmented labels in a already existing graph?
I am working on a project where I have to segment the image using multi-class segmentation (3 classes) on microscopic images.
Now let's say that I am segmenting solid, liquid and gas images (this is ...
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Image segmentation with U-net
I am trying to understand if Semantic segmentation with U-NET. Are we training kernels to extract features or are we training a fully connected layer at the end? Or both? If so, how are we training ...
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41
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Remove frame from background
I am having 400 images that look like the following:
I would like to remove the frame and only get the image in the middle:
I tried the MODNet model ...
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542
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How do you train a semantic segmentation model to optimize for IoU rather than accuracy?
I am currently building a U-NET semantic segmentation model on Tensorflow Keras to classify pixels as belonging to or not belonging to a class.
For this problem, I've isolated the masks for only one ...
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Why is my training loss not changing?
I'm trying to train a semantic segmentation model based on this architecture, using this one as a base.
The base model uses about 10 ReLU activations, and when implemented according to the first paper,...
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Is there an official procedure to compute mIoU?
Although it sounds silly, I'm not finding an official source to compute mIoU.
I'm realizing a semantic segmentation task, and I want to compute the mIoU over a dataset. My doubt is, should I compute ...
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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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The channel dimension of the inputs should be defined. Found `None`
Hello I'm trying to use SegNet in my project with tensorflow, for educational purpose. And I'm surely following someone else's code on GitHub:
...
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Pre-trained models for semantic segmentation of satellite images
I'd like to use semantic segmentation of satellite images but I don't have the processing power to train existing models or producing one my own.
Ideally, I'm looking for a U-Net CNN model that can be ...
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My semantic segmentation model classifies everything as background
So, I am working on a semantic segmentation task using U-Net. The dataset is very unbalanced, with the background being by far the most common, and the last class being very scarce. First I trained it ...
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Suitable instance counting CNN for training on polygonal masks
I have a medical dataset labeled with polygonal masks (rather than rectangle boxes). It works well for pixel annotation with UNet to generate masks of healthy vs damaged skin. Now I need to do ...
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High image segmentation metrics after training but poor results in prediction
I'm trying to build a model with Keras that predicts four classes of features from microscopy noisy images which cover about 10 - 30 % of the image. I'm using U-net because my dataset is small (150 ...
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Criteria for saving best model during training neural network?
I am doing 4-class semantic segmentation with U-net using generalised dice loss as loss function.
General approach to save best model during training is to monitor validation loss at each epoch and ...
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42
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Pixel labelled image is must for semantic segmentation using deep learning in matlab?
I have large set of CT images containing lung regions. But I don't have corrosponding pixel labelled images. So how I could do semantic segmentation using DL in matlab. Like a test program I created 6 ...
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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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406
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Multiclass semantic segmentation with some classes possibly not present in some of the images
Let's assume we have a large annotated dataset with 4 classes. In this dataset, there might be annotated images with less than 4 classes, where the remaining classes might or might not be present. As ...
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What is the difference in computational cost at inference time between object detection and semantic segmentation?
I am aware that YOLO (v1-5) is a real-time object detection model with moderately good overall prediction performance. I know that UNet and variants are efficient semantic segmentation models that are ...
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Which F1-score is used for the semantic segmentation tasks?
I read some papers about state-of-the-art semantic segmentation models and in all of them, authors use for comparison F1-score metric, but they did not write whether they use the "micro" or &...
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962
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Semantic segmentation of an image with multiple labels per pixel
I am building a model for a multiclass sematic segmentation of a skin disease. At a moment I am using U-Net for binary classifications.
In this multiclass problem I have the following cases. There are ...
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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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What is Deep supervision?
I'm interested in segmentation models for medical imaging purposes.
When I looked at the state of the art, I fell on a paper on a new architecture, Unet++:
UNet++: A Nested U-Net Architecture for ...
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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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Image segmentation with large class imbalance leads to zero precision/recall
I have a binary semantic image classification problem where only very small parts of the images are positive, most of it is negative. In the training data I have a positive rate of around 0.023, which ...
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How to extract contents by topic from a document?
I am trying to extract information from resumes. I tried the pdfminer for the text extraction. But I need to extract the contents from a resume with respect to its title.
For example:
I will be giving ...
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Semantic networks: word2vec?
I have some doubts on how to represent the relationships between words in texts.
Let’s suppose I have two sentences like these:
...
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For semantic sementation, why am I getting better loss values with binary cross entropy than dice coef?
I'm learning all related to data science and how to train U-Net to do semantic segmentation.
I have a U-NET with this loss function:
...
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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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