Questions tagged [image-preprocessing]

Image preprocessing are the steps taken to format images before they are used by model training and inference. This includes, resizing, orienting, and color corrections. Preprocessing is required to clean image data for model input. For example, fully connected layers in convolutional neural networks required that all images are the same sized arrays. Image preprocessing may also decrease model training time and increase model inference speed.

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Auto encoder network

Is there any rule that we should use only deconvolution operations in decoder block of auto encoder network or we can use convolution in such way that it up-samples or mirrors the corresponding ...
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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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Beginner needs guidance. Machine Learning, preparing training data

i try to dip my feet into the field of computer vision and want to avoid mistakes along the way. The problem I have to solve: Classifiy images of 3D dental scans. For example: I wrote a script to ...
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How to train a form recognizer

I'm working on a project in which I need to build a form recognizer that, given a form image, returns de key - values pairs. As I just got started, I wanted to hear some opinions about what should I ...
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Convert FER2013 dataset from grayscale to RGB

I am currently working on a Human Face Emotion detection project, my goal is to use transfer learning to build my model. When I tried it's been said that I cannot instantiate the base_model which is ...
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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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Separating image signal from constant noise sources

I'm working on image signal from a sensor where the incoming signal consist of high degree of constant noise. The noise patterns are multiple, both with very low frequency and very high frequency but ...
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Help me to identify the doors and windows from this image

I am struggling to mark windows and doors from this type of images. Actually, each images are in different style, and the color thermal maps also varies. There is no ground truth as well. Would you ...
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What is meant by non-linearity in Convolutional Neural Networks? And why do we focus on removing it entirely?

I am aware of the working of ReLU that it turns every negative value to zero and does not effect any positive value, but what confuses me is this: what is actually meant by non-linearity in feature ...
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Comparing two images for similarity

Comparing two images for similarity What are the best softwares available for comparing two images having similarity and differences? Example: Margaret Thatcher & Enid Blyton.
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Image-wise vs. pixel-wise of the CT images for segmentation task

I'm working on a semantic segmentation of a lung region on a computer tomography (CT) images. CT images have only 1 channel (Hounsfield units) and can be put in one class of images (one distribution) ...
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Normalizing images with OpenCV (divide by 255)

I'm loading images from my dataset, which are all of resolution 200x200 and in RGB format. I'm loading them using OpenCV for Python, with the following code: ...
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Image normalization and reverse normalization: colors lost on image generation (GAN)

I'm working on a Gan. Based on different papers, I use a Tanh activation function on the last layer of the generator. Which produces [-1,1] outputs. To make this coherent, I use image normalization ...
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Understanding last convolution of U-NET for image segmentation

I was trying to understand the last layer of Image segmentation architecture (U-NET). For example what will be the logits-probability distribution of pixels in each case? I know that its there as ...
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How to standardize a tensor

When I have an image , I can standardize the image channel-wise as follows : ...
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global contrast normalization implementation

I'm trying to understand figure 12.1 in Goodfellow available here. I'm not able to reproduce figure 12.1, and I'm wondering what is it I'm missing. The denominator of equation 12.3 is a constant, and ...
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ImageDataGenerator for image preprocessing

I'm trying to do a superresolution network, but I am having trouble importing my own data. I have two types of images: resized images (smaller), original images. The first one is going to be used as ...
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How to retrieve flatten PCA analysed image?

I am trying to retrieve each of the images after PCA. What I have done, First, I flatten all the images and concatenate them vertically. Suppose, image size is 80 x 80, then flattening it creates 1 x ...
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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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Image size for training transfer learning model for object detection purposes

I am trying to build transfer learning model to detect objects from video streams. There will be at least two or three different objects (classes) which are quite different from each other. The ...
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How to break a binary image mask into multiple masks?

I have image with binary mask. I want to break the binary mask into many individual masks of same dimension, but each mask should contain only one segmentation mask. Is there a way to do it in python, ...
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If an FCN accept rectangular image as input or has to be square?

Some say that for FCN it doesn't matter if the input image is rectangular the only thing matters that the size must be constant ...
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Working with three types of data: numeric (integer, floats), images, and text for prediction

So I have three types of data (in title) and am wondering how I can combine the data. The target is numeric (price). My idea is to perform feature extraction on both the images and text, which would ...
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Keras ImageDataGenerator unable to find images

I'm trying to add image data to a Kaggle notebook so I can run a convolutional neural network but I'm having trouble doing this via ImageDataGenerator. This is the ...
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Central finite distance gradient simplified [closed]

I'm asked to compute central finite difference scheme (f(i+1)-f(i-1)) on an image. My attempt is something like: ...
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Pre-processing images for fine-tuning

When you are fine-tuning a CNN like ResNet, VGG, EfficientNet, etc and you want to train the model with your own images, or even when you want to do a inference with any image of your dataset, do you ...
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when depthwise separable convolution should be preferred over normal convolution?

As a novice in the realm of deep learning, I recently learned about Depthwise Separable Convolution. I have seen some tutorials and articles about it on internet, and in all of them the author ...
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Is it possible to apply pooling across the channel dimension of the input tensor?

I have an input tensor of the shape (32, 256, 256, 256). In this tensor shape, 32 is the batch size. second 256 is the number of channels in the given image of size 256 X 256. I want to do pooling in ...
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Can i segment/crop out image using image processing?

I have a large dataset of bottles. I want to train a model with this dataset. But before feeding the input images to the model I want to crop out the bottle from the background. Is there a way to do ...
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Image Preprocessing [closed]

I'm working on a use case where I need to pre process the image for my AIML model evaluation and I want to count all black pixels in RGB image. Instead of iterating rows*column, I'm looking for some ...
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Where Can I find real world gaussian, S&P, speckle black and white image

I am looking for Real world black and white images with gaussian, speckle and s&P noise dataset or images. Where can I find them?
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How are the GLCM results (matrix or singular values) applied to an image?

I am doing some basic texture analysis and have noticed a lot of examples and tutorials showing original images altered with entropy,variance, etc... When running greycomatrix, I get out the levels x ...
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Cannot reshape array of size 12288 into shape (64,64)

I have an image I loaded with the image.load_img() function but when I try to reshape it I get this error: ...
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finding the defect button

In case of a project where you are going to detect whether the image printed on a button is correct or not and given that you have only a one correct possibility of a correct image and some incorrect ...
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Doubt with Imagedata generator

I have a total of 500 images in one class. And below are my parameters passed for image argumentation from image data generator,now I am confused with the amount of images produced in total. I have ...
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Checking if an image has an noise in it or not using psnr signal value

I basically want to check if an original image has noise in it or not. To do this, I came up with an approach where the original image is filtered first like using Gaussian filter. And then I ...
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Advices to create a data set from dictionnary's screenshot

I have six thousand screenshots like the one below. I would like to create a date set to do some deep learning. My goal in the end is to create the next word prediction using only my own word data set....
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Image Classification using ML and Image processing

I'm doing a project in ML and Image processing where I try to classify cats and dogs! dataset: https://www.kaggle.com/chetankv/dogs-cats-images The models I'm using: KNN, Random Forest, SNM, and ...
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Algorithm for learning image distortion?

I'm looking for tools to characterize relationships between gridded outputs of multiple physical models as image distortions. For instance, given a 2-d picture of the temperature distribution in two ...
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Handling classification DNN of high defintion video (beyond 12MP) on the edge

Currently I'm investigating DNN on the edge. I saw several models that runs pretty well (BNN) on MCU, but I wonder which techniques should I use in order to proccess much bigger video stream for HW ...
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Can we use only one autoencoder for removing noise and converting a greyscale image to color image?

I am new to deep learning. out of curiosity, I have doubt about autoencoders. I want to construct a greyscale image by removing noise in it and converting it into a colour image. We can do this by ...
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How to design a model for contour recognition? In particular, how to shape the output layer?

I want to design and train a neural network for the automatic recognition of the edges, in some microscopic images. I am using Keras for a start, I may consider PyTorch later. The structure of the ...
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Best approach to clustering images

I am new to unsupervised clustering and I wish to perform clustering on a dataset of 512 images. I want to output n clusters where each cluster holds images that are similar to each other. I do not ...
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Why training loss is decreasing down too fast?

I have a dataset of video sequences, I have trained them, and calculated the training loss using mean square error, but my training loss is decreasing down very fast. Like 0.06-0.02. Is it just fine ...
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How to feed high resolution images to the model?

I want to do object detection , normally we have a size of image 256 x 256 or 128 x 128 but what if we want to feed high ...
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What is the explanation of convLSTM 3x3-256-2?

I have read it in a paper, convLSTM 3x3-256-2 means convLSTM with 3x3 filter size, 256 hidden states, and 2 layers. But the original LINK do not show any argument regarding hidden states and layers. ...
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What is the impact of changing image sources on an image recognition?

I have a fairly general question pertaining to an image recognition ML model. I’ve recently developed an image recognition model using a single camera collecting more than 5000 images and then trained/...
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reprocessing steps for images before training classification models

I have a data set of images for classification task. I read some articles about image reprocessing (before training CNN models) ...
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is padding input images better than resizing image?

I am working with images and was thinking of pre-training VGG19 and EffecientNETB0 model on my dataset. However, a query:- Is ...
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Is it possible to do Robust PCA on Images

I have a task to perform outlier detection on a medical image data set (CheXpert), but with more „classical“ techniques (i.e. not use a DL approach like GANs or AEs) and I was wondering whether robust ...
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