Questions tagged [image-segmentation]
The image-segmentation tag has no usage guidance.
113
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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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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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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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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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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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Why do I get such a low accuracy despite having good metrics?
I'm working on an image segmentation problem. I'm fine-tuning the network, and when displaying the metrics I obtain, I have some doubts.
I am going to provide some details about the network:
Solver: ...
- 304
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123
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How can I interpret this YOLOV7 segmentation results plot?
I have the following results plot generated by train.py of YOLO-V7 segmentation:
The problem is that I am not sure how to interpret this plot. For example, to check for overfitting, I need ...
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Segmentation-models-pytorch returns black image
I tried to use Segmentation-models-pytorch first time by following guideline and using it on my task on kaggle(HuBMAP), here is link for official guide:
https://github.com/qubvel/segmentation_models....
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134
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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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Embedding vector of MaskRCNN (Resnet with FPN)
I have a MaskRCNN model for instance segmentation with Resnet 50 - FPN backbone trained in detectron2. And I want to extract the embedding/feature vectors for visualizing input and hopefully detecting ...
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How to do batch inference in pytorch on a local GPU?
I'm working on a version of SAM model which predicts the segmentation map using text prompts provided by the user. As of now, running a single image takes about 5 seconds.
I want to run about 100 ...
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Detecting scratches in car surface, may be data drift
I am trying to detect scratches on the car surface using Yolo, I have training images like the one below, and I am getting good mAP (around 0.83) on the validation and test dataset. The training image ...
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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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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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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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183
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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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1
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833
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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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737
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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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132
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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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234
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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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552
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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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Is it possible (if yes, then how) to provide the semantic segmentation results on the Original Size of the input image?
Just like this website, it does not matter what shape of image you provide them, instead of giving you a fixed size output, they'll segment your image and provide you the resulting image with original ...
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How to measure the similarity between two medical images of different imaging modalities according to similar objects in both of them?
I have two series of medical images each one from different imaging modalities.
According to that, I have been segmented the Region of interest (the object which appears in both modalities )using U-...
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Why are wavelet transforms not scale-equivariant?
One can rely on continuous wavelets to build a multi-resolution analysis that is equivariant ("covariant") under the action of a discrete subgroup of translation.
When not downsampled,
the ...
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447
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Floor plan analysis
Given an image of a floor plan, is there a known algorithm I can use to understand measurements of all apartments present ? (for example, that means in the attached picture understanding there are 4 ...
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579
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multiple images inside one large CSV file
I'm very new to data science, and was admiring how people had made these massive open-source datasets, on places like kaggle. I noticed that all of the datasets where all in CSV format. I have lots of ...
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147
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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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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:
...
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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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457
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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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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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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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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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378
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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 ...
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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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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 ...
