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Questions tagged [semantic-segmentation]

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How do transposed convolutions in CNNs reduce the channel dimensionality?

In CNNs, I understand how convolution works and how it gradually reduces spatial resolution but increases the channel dimension. E.g. an RGB image of 100x100x3 after a few convolution layers may ...
tandeg's user avatar
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Why can't I increase my GPU utilization?

I have a simple UNet model (~1M params) written in Keras 3.0.1, running with a torch backend. My CUDA version is ...
Savindi's user avatar
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1 answer
20 views

How do I ensure final output shape matches input shape for a semantic segmentation task?

I trying to replicate the semantic segmentation example https://keras.io/examples/vision/oxford_pets_image_segmentation/ but train on my own data. I have 8 labels (7 features + background). My images ...
utx7563yu's user avatar
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17 views

Trying to train a denoising autoencoder to restore missing information from a binary image

I am building a denoising autoencoder to repaint lanes from a binary image. The input is a binary image that has incomplete lanes, due to vehicles getting in the way. I repaint the lanes manually so ...
Kaif Ibrahim's user avatar
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38 views

Semantic segmentation sometimes give bad result

I'm training Unet+MobileNetV3 for semantic segmentation objects on real photos using custom dataset and get strange results. I have already accumulated pretty big dataset and constantly improve it by ...
Vladislav D's user avatar
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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.
Dmitry  Sokolov's user avatar
1 vote
1 answer
26 views

Building a CNN (with Keras for pixelwise classification)

I have a set of 120x120 input images with 3 channels. I want to build a basic CNN to predict the value of each pixel. I have 2 doubts. One is regarding the last layer - should be a Dense layer, or a ...
Filippo Nunes's user avatar
1 vote
1 answer
76 views

Why not using segmentation architectures for object detection?

Current object detection architectures like Faster-RCNN and YOLO seem to be overcomplicated in comparsion with segmentation architectures like Unet. So, why can't we just draw some rectangles around ...
Eugene's user avatar
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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 ...
Austin Capobianco's user avatar
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0 answers
10 views

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 ...
Devansh Gupta's user avatar
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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 ...
vs07's user avatar
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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: ...
th2797's user avatar
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26 views

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,...
Capdi's user avatar
  • 111
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0 answers
13 views

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 ...
The White Cloud's user avatar
1 vote
0 answers
261 views

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 ...
user48956's user avatar
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1 answer
382 views

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 ...
Shayan Daneshvar's user avatar
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1 answer
160 views

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 ...
dhananjaya's user avatar
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0 answers
37 views

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. ...
Sarath SRK's user avatar
0 votes
1 answer
21 views

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 ...
indian gamedeveloper's user avatar
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0 answers
46 views

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 ...
Vlad Timu's user avatar
0 votes
1 answer
50 views

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 ...
J. Wu's user avatar
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1 vote
1 answer
22 views

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 ...
Raghuvaran P's user avatar
0 votes
0 answers
73 views

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 ...
S_S's user avatar
  • 101
0 votes
1 answer
2k views

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 ...
Pratichhya's user avatar
0 votes
1 answer
444 views

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 ...
Aishwarya Shriniwas's user avatar
0 votes
0 answers
156 views

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 ...
canovich's user avatar
0 votes
1 answer
43 views

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 ...
Carol.Kar's user avatar
  • 187
2 votes
1 answer
712 views

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 ...
stevemeisterr's user avatar
2 votes
1 answer
2k views

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,...
Ad Ve's user avatar
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0 votes
1 answer
759 views

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 ...
Rafael Toledo's user avatar
0 votes
1 answer
2k 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 ...
Sharhad Bashar's user avatar
1 vote
1 answer
1k views

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: ...
Danial's user avatar
  • 111
1 vote
0 answers
128 views

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 ...
lennox's user avatar
  • 11
0 votes
2 answers
1k views

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 ...
BMC98's user avatar
  • 1
0 votes
1 answer
25 views

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 ...
sixtytrees's user avatar
1 vote
2 answers
3k views

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 ...
Capdi's user avatar
  • 111
0 votes
1 answer
480 views

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 ...
spb's user avatar
  • 88
1 vote
1 answer
42 views

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 ...
Silpa's user avatar
  • 11
1 vote
1 answer
496 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 ...
spb's user avatar
  • 88
0 votes
1 answer
441 views

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 ...
r1c's user avatar
  • 51
2 votes
0 answers
275 views

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 ...
JStrahl's user avatar
  • 121
0 votes
1 answer
183 views

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 &...
Panicum's user avatar
  • 111
0 votes
1 answer
1k views

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 ...
sixtytrees's user avatar
1 vote
0 answers
116 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 ...
Brans Ds's user avatar
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5 votes
2 answers
5k views

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 ...
Nicolas's user avatar
  • 244
4 votes
2 answers
385 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. ...
lo2's user avatar
  • 41
2 votes
0 answers
254 views

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 ...
Martin Ueding's user avatar
0 votes
2 answers
212 views

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 ...
SRJ577's user avatar
  • 197
0 votes
1 answer
57 views

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: ...
Math's user avatar
  • 161
0 votes
1 answer
101 views

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: ...
VansFannel's user avatar