Questions tagged [image-segmentation]
For questions related to image segmentation (in computer vision and related AI fields).
128 questions
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Neural Networks for LIDAR Images
I recently encountered this blog https://ouster.com/insights/blog/the-camera-is-in-the-lidar
It seems like one can leverage lidar data as an image quite nicely and therefore use 2D vision algorithms ...
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Which computer vision model (or LLM) for segmentation?
I'm new here. I have nearly 2,000 bee images with hand annotations of masks of the full body. I want to automatically generate "head", "thorax" and "abdomen" from this ...
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Is background segmentation effective for improving action recognition model on real-time human-object interaction videos?
I am working on an action recognition task involving human-object interactions using an I3D (3D CNN-based) model. The model was trained on pre-recorded videos, and it performed well during evaluation. ...
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How to 'induce' or 'teach' pretrained model to a continous Transformer token-pruning Algorithm
I am currently looking for ways to improve Transformers performance in image processing, especially in image segmentation. I found this paper by Kong, Z., et al called "SPViT: Enabling Faster ...
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Indoor elements detect from floor image
I have a large collection of floor plans that I need to convert into indoor maps by extracting walls as lines, doors as lines, and rooms as polygons. Currently, I do this process manually.
The floor ...
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Automatic Image Annotation Based On Colour
I need to annotate a large corpus of images for image segmentation.
I can generate this corpus of images myself and I can choose to color whatever needs to be annotated with a specific colour.
I would ...
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How to fix segmentation model producing black segmentation masks?
Apologies in advance for incorrect formatting, I've been kindly sent here after posting my question on StackOverflow.
We're training a segmentation model using Snapchat's template for custom ...
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415
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Vision transformer for image segmentation
I am working with vision transformers (ViT) for the task of image segmentation, but I am unsure of which segmentation head to use.
I know I need a vision transformer as my backbone, and a segmentation ...
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Visualization of Transposed Convolutions
After reading on Transposed Convolutions and Fully Convolutional Networks in the d2l book (14.10 and 14.11), I wondered about the visualization of transposed convolutions.
As you probably know, ...
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why CAM does not use ReLU, unlike Grad-CAM?
I learned that Grad-CAM uses ReLU becuase it is only interested in positive incluence on the class of interest.
Then I think ReLU can also be used to CAM. But why they don't use ReLU?
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Uncensored auto-captioning libraries that work well for NSFW image datasets?
I have a large (>2.5 million files) dataset of NSFW images that I would like to auto-generate detailed (~100-150 token) captions for, using a visual language model similar to CogVLM or Llava.
I ...
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Realtime cuboid vs cylinder classification of a 2D mask / object from a 3D scene?
Most realtime SOTA segmentation/detection model can reliably segment an object from a 2D input, and I can get the contours/polylines describing its edges in realtime. By realtime, I'll consider ...
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57
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Advice on Moving Object Segmentation with U-Net where the target is small
I have a problem I'm trying to solve. I'd like to spot a moving object in a video sequence. "Moving Object" is very vague, but it can be roughly defined as 'here is a bright point that seems ...
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Image segmentation with noisy labels
I have a dataset which consists of satellite images and their labels which are indicated by let say class 1 and 2.
I want to perform image segmentation to detect pixels related to class 1 and 2. The ...
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Should I define my problem as image segmentation or detection?
I have a problem and have to decide wether it's an object detection or object segmentation problem. I want to use Yolov8 for training. We already have hundrets of images but they aren't labeled yet. ...
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How to accurately detect grid cell boundaries in Python image processing?
I'm working on a Python algorithm to detect individual cells of a grid passed by an image. Currently, I'm facing an issue where the values inside each cell are being selected as contours along with ...
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Binary instance segmentation - does the masks have to be complete
I am wondering if it is required or not that the masks used for binary instance segmentation are complete.
For instance, I want to find the buildings in aerial imagery. If my masks cover, let say ...
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Image segmentation with varying resolution
I am looking to create a model that is able to perform binary segmentation of images with varying resolutions. For model should be able to classify tree or not tree regardless of the resolution of the ...
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How to add engineered features to an image segmentation model
I have built a U-net model for image segmentation of 3-channel remote sensing images. I have a total of four classes; two of these classes look very similar and are hard to distinguish in the images ...
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Batch Normalization Layer is not learning the data semantics of a dataset comprised of datasets from different sources
I have built a dataset for image segmentation that is comprised of datasets from several different sources.
Almost all of my models have problems with learning the correct parameters of the ...
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Use AI/Computer Vision to detect scene changes
I'm trying to use AI and computer vision techniques to identify scene changes for a camera. Something like this:
What are some approaches to do this? Any ideas?
The scene is static. Somewhere I saw a ...
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Should I apply a min-max scale (range 0 to 1) before applying the normalisation or should I apply the z-score normalisation directly?
I want to implement a neural network in Pytorch for medical image segmentation. I should normalise my data.
Should I apply a min-max scale (range 0 to 1) before applying the normalisation or should I ...
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How can I tell a CNN to ignore nodata values in satellite images?
I'm trying to train an image segmentation model on satellite images. There are two main issues: first, not all of the images are the same size. My understanding is that by using a fully convolutional ...
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Should softmax be in the model or in the loss function?
Suppose I have an image segmentation model with an output of [ 128, 128, 2 ], segmenting an input image into 2 parts.
Commonly, loss functions have the sigmoid or ...
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Creating border around specific areas of images
I have some 1000+ image, containing data like this
Red area: Symbols
Grey area: Text describing the symbol
Note: I draw these red/grey boxes just for visualization only.
Each symbol is unique in this ...
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How does one deal with images that are too large to fit in the GPU memory for doing ML image analysis?
How does one deal with images that are too large to fit in the GPU memory for doing ML image analysis?
I am interested in detecting small structures on images which are themselves many GB in size. ...
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65
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Document Processing using AI
Deal all
I want to Build a Document Processing AI Model
1-that Identify Document Elements
Like table, Text , List , Heading , etc.
2-Sort this element in correct way if I wan to dump this data as XML
...
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What's the difference between classification and segmentation in deep learning?
What's the difference between classification and segmentation in deep learning?
In particular, can the classification loss function be used for segmentation problems?
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Latest status on stability of CNN architectures to noise and "clever hans" issues
I was working with CNN architectures for image segmentation a few years ago, and I remember there was a big concern about on the stability of the predicted masks due to the introduction of small ...
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Segmentation of x-ray images to detect Covid-19
I’m currently working on covid detection project using x-rays. I applied K -means clustering algorithm (https://www.kaggle.com/code/naim99/image-classification-clustering-step-by-step?scriptVersionId=...
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How does accuracy (for a single class of interest) of a segmentation network vary with increasing number of classes?
BACKGROUND: I have a real world problem of developing a U-net-like model for segmenting lung tumors in lung CT images.
On the one hand, I can make this a two class problem:
...
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possible to combine multiple labeled objects as one object?
So I have labeled the entire skeletal muscles in detail. For example instead of just labeling shoulders I have labeled:
Rear Delt
Middle Delt
Front Delt
but now you want all of the delts to be ...
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Are masks needed for images that don't contain the object of interest in (binary) Image Segmentation tasks?
Total Dataset :- 100 (on case level)
Training :- 76 cases (18000 slices)
Validation :- 19 cases (4000 slices)
Test :- 5 cases (2000 slices)
I have a dataset that consists of approx. Eighteen thousand ...
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Extract a document page from a photo
I am trying to extract a document as an image from another image. Let's say that we take a photo of a document on a surface. My ultimate goal is to be able to digitize this document but as an image, ...
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How to incorporate domain knowledge into a semantic segmentation network?
I'm working on a semantic segmentation project, and want to add some domain knowledge to the system. I want to ensure that for segmentation, there can only be one group of pixels that are predicted as ...
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Using pre-trained models on image dataset that is totally different for object detection?
I have been trying out various tutorials on object detection machine learning. All the tutorials so far have been to use a pre-trained model for practical reasons when detecting objects that the pre-...
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Why instance segmentation architectures using reconstruction masks but not regression?
I'm wondering why many model architectures use binary mask reconstruction for segmentational CNNs, and not regression of mask polygon coordinates? Many object detectors use regression to find ...
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133
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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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What considerations should I take to train my transformer model?
I want to train my vision transformer model on a benchmark for an image segmentation task: (LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation) (GitHub), but I don't ...
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77
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How to identify and diferentiate several edge lines of an object?
I want to create an AI to detect and identify certain edge lines on my image. The input image is a locker key, and I want to know the exact position of certain edges.
Sample input image:
Sample ...
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Use of Mask in U Net for plant disease detection [closed]
I am using U-Net for plant disease detection. I am new to deep learning and computer vision.
Currently, we are feeding the masking images generated via open cv HSV format to detect colours from the ...
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97
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Is there way to segment an image without labeling/classification, as well as supervised learning?
Is there way to segment an image without labeling/classification, as well as supervised learning?
For an illustrative example, if one considers an image with a dog and a cup (we don't particularly ...
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641
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What is exactly sparse annotation?
What is exactly sparse annotation? Is it different from labeling images?
I've been reading a paper about vessel segmentation and have some issues understanding this part.
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75
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Deep RL reward design for neuron centerline extraction task
As part of a bigger scope project, I'm training a RL agent that attempts to reconstruct, pixel by pixel, the trajectory of a neuron on a segmented image. To give a better insight on the task that I'm ...
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Mask R-CNN: how is the inference done?
According to the Mask R-CNN paper and the picture below (taken from the paper), the mask branch is computed in parallel with the bbox classification and regression branches.
However in the paper they ...
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Image segmentation when given masking information is incomplete
In my problem, there are about 5,000 training images and there are about 50~100 objects of identical type (or class) on average, per image. And for each training images, there is a partial mask ...
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Custom Tensorflow loss function that disincentivizes all black pixels
I'm training a Tensorflow model that receives an image and segments the image into foreground and background. That is, if the input image is w x h x 3, then the ...
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193
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Why is the simplest U-Net architecture giving the best (but not good enough) results on a multi-class segmentation on microscopic data?
Currently, I'm trying to optimize a training process of a neural net to improve final results. The problem I'm dealing with is multiclass segmentation on microscopic data.
The paradox is that the best ...
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277
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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-based model (deep lab v3+ with xception as the backbone) for image segmentation and removing the background. The subject of the image will be a person. And my target is to ...
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How to divide a segmented image into classes instances?
Is there a method/algorithm to generate instances of objects from image that was segmented by the use of any image segmentation models?
For example, I have an image with one class and it was segmented ...
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