Questions tagged [image-preprocessing]

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Differentiate twins, triplets images in Computer vision field

https://en.wikipedia.org/wiki/Computer_vision https://en.wikipedia.org/wiki/Twin https://en.wikipedia.org/wiki/List_of_triplets Will there be challenges in Computer vision field to differentiate ...
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Does Object detection belong to Photogrammetry or image processing?

I often get confused in categorising object detection task among several computer vision fields. So my question literally is, under which category does object detection task come?
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How can I plot a bunch of images, given their centre coordinates?

The points here represents centre coordinates of images with unique names. I want to plot all the images on the same 2d space to get a final representation of all the images merged into sort of a ...
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Image multi class classifier CNN

I have a problem, im designing a multiclass classifier to classify medic images, I have to classify in which grade of desease is it, this are 6 grades , each time the joint deforms a little, so, mi ...
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How to generate custom image dataset for object-detection?

I have to build a custom logo detector from e-commerce images. I am aware of object detection techniques like YOLO, SSD etc and could find many resources on how to annotate a custom object detection ...
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Unsupervised Defect Detection on Any Images

Everyone. I want to ask that Is there any way to do unsupervised defect detection(without labeled data) or without knowing the possible defects that will arrive in future. Means that I train my model ...
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Can I predict different size of test image on my trained Unet model

I have one image,where top left corner of the image (784,448,3) is used for test image and remaining area is used for training where overlapping patches of size (112,112,3). I have trained my Unet ...
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52 views

Cable angle measurement (rotation)

I need to detect the rotation of a cable (degree) in the x-axis with high precision [0.2 (or more) degree detection] from its original state. Detailed description: I have a cable that is set in its ...
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1answer
22 views

How do reshape an image to fit my Mnist Convolutional model?

I have done research but cannot seem to find what's wrong here I have created this model for Mnist digit clasification : ...
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Classifying Live Images From Camera Feed with bunch of objects in Background?

I can successfully run image classification if I feed examples from Google image to mobilenet model on Raspberry pi with Google Coral Edge TPU. However, if I feed live images from camera in my living ...
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62 views

How imagenet mean and std derived?

To use pre-trained models it is a preferred practice to normalize the input images with imagenet standards. mean=[0.485, 0.456, 0.406] and ...
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Varying Image sizes in Tensorflow Malaria dataset | Dealing with unclean tensorflow data

I am trying to build a CNN based image recognition system for the Tensorflow malaria dataset. I loaded the dataset (~27k RGB images) using conventional tensorflow_datasets syntax. After some data ...
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Load data from multiple dataframes containing both path and labels in keras

I am aware that there exists a function in keras.preprocessing.image.ImageDataGenerator called flow_from_dataframe. But this ...
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48 views

Canny edge detection not working on Gaussian blurred images

I am trying to detect edges on this lane image. First blurred the image using Gaussian filter and applied Canny edge detection but it gives only blank image without detecting edges. I have done like ...
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Digitize graphs. Pull out data from points in a scatter plot

I have a project where I would like to extract data from a series of scatter plots that are image files (Jpeg or png). The plots are similar but the axes scales are not always exactly the same. I have ...
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Comparision between SSIM and MAD Image Quality Assessment Algorithms

I have been working on Most Apparent Distortion(MAD) tool to evaluate the quality of images. I have read a paper that compares SSIM, PSNR, FSIM, etc. with MAD. I am uncertain about some calculations ...
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Batch Normalization as input layer to learn an optimal scaling?

We all know that Batch Normalization reduces "Internal Covariance Shift" and therefore helps Neural Networks to train faster (Batch Normalization: Accelerating Deep Network Training by Reducing ...
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Can I plug models like Linear Regression into a CNN feature map result?

I was learning about image recognition on the Orange Software and I saw that I can feed my image database into a CNN(they call image embedding) that has as output a feature map of the image and then I ...
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ValueError: Shapes are incompatible when fitting using ImageDataGenerator

I got this error ValueError: Shapes (None, 1) and (None, 3) are incompatible when training my Sequential model. I could not figure out which shapes are actually ...
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Brightness Adjustment During Pre-Processing and Model Accuracy

I have image datasets that consists of multiple level of brightness. Usually darker are more than the bright. All these images are collected from different places. Some of the images too dark that to ...
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image processing, remove line pattern

(This might not be the right forum, but I can't find a computer-vision stackexchange). I have an image which contains some numbers overlaying a fixed line pattern (the second pix, zoomed in). The ...
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how to detect multiple characters in image using CNN

I'm trying to extract one word (sequence of chars) from image (fixed length of text). when i use CNN i can detect the presence of a char using multiple CNN networks each trained for one of chars. ...
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1answer
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How to save multi-output predicted masks into two different folders after using model.predict_generator

I have a multi output segmentation task, the training process went well, but when Im trying to get the prediction I found difficulties to separate the two output into two different folders, in my ...
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CycleGAN vs. AutoEncoder for transforming sketches into images

I'm playing around with the use of deep learning on images and done quite works : colorizing black and white images for example, or maybe fixing old damaged photos. Today I want to tackle a new ...
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24 views

how to compare two images and show the difference in a new image?

I want to compare two web pages images using computer vision techniques. show what are non-unique portions comparing both images. which part image1 not exist in image2 vice versa.
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Paragraph extraction from text

I am trying to separate scanned pages of a 3 column book into paragraphs. On the pages there can be images located in an arbitrary location, occupying part of one, two or all three of the columns. ...
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38 views

Clustering of unlabeled ship images

I want to create a ship detection classifier from a dataset that is formed by 4000 photos(3072*2048). But the dataset that i currently have is not labeled so i can feed it to a cnn.So i want to ...
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How to add jpg images information as a column in a data frame [closed]

I have jpg images stored in a folder. For ex: 11_lion_king.jpg,22_avengers.jpg etc. I have a data frame as below: ...
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Strange out of memory while loading lots of pictures before input CNN for deep learning

I’m using the TFlearn, and want to classify pictures to two category. But the strange out of memory while loading lots of pictures before input CNN for deep learning. The RAM is 64 G in my deep ...
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I Have Issues Installing Basemap

I tried to install Basemap and it gives me this: preparing transaction: done verifying transaction: done executing transaction: failed ERROR conda.core.link:_execute(507): An error occurred while ...
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1answer
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Why do we use different image processing at train and test time for an image classification tasl

I would like to ask why we use different image processing at train and test for an image classification task. For example, this pytorch tutorial uses RandomResizedCrop at train time and then Resize + ...
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175 views

Keras CNN model gives no gradients error during training

I’m trying to create a Convolutional Neural Network model, using an 824 image dataset, for predicting an output value. Problem is that the dataset is quite unstructured, as there are plenty of RGB and ...
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107 views

Getting a bounding box mask given coordinates of an object in the image

In the paper See the Glass Half Full: Reasoning about Liquid Containers, their Volume and Content, one of the inputs to the model is "a bounding box mask smoothed by a Gaussian kernel". I'm not sure I ...
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How to remove background (watermark) logo from image

I have been scratching my head for a while. What I have is a scanned PDF document with text and water marked logo at the back as in the below image. I want to do OCR over this, which becomes very ...
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Can we use RNN or LSTM for prediction and not forecast

I know RNN and LSTM learn from past data, and can forecast next data. In my situation, I have a learning data-set that hide other information I wish to discover or approximate.(This seems rather an ...
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Intensity image to RGB for transfert learning

My goal is to use a pre-trained model with intensity based image. Most pre-trained model expect RGB (int) format as input image. An easy workaround is to dupplicate the intensity channel 3 times in ...
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What is mAP in object detection?

I have been reading through this blog in order to find what mAP is .In the sub heading of AP, they give the example of 5 apple images and finding out the average precision.As far I understand false ...
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Guidance required on image segmentation

I am new to deep learning. Specifically to image segmentation. I am trying to localise object from satellite images (screen grab from google maps). When I am going through articles/blogs in the ...
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Finding the appropriate CNN Model Architecture and Parameters

I am currently creating a CNN model that classifies whether the font is Arial, Verdana, ...
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Precision Recall using Distance Matrix

Given a Pre-trained CNN model, I extract feature vectors for 3450 Reference (Winter) and 3450 Query images (Spring) and compare features with euclidean distance to plot the distance matrix besides ...
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1answer
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How to label images for CNN use as classifier

I have theorical question that I couldnt decide how to approach. I have tons of grayscaled shape pictures and my goal is seperate these images to good printed and bad printed. For this, I look at ...
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Clarification of image reverting

I am a newbie to deep learning. Could someone please explain why (img)*0.5 + 0.5 line and img = img*255 will be there for ...
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Filters to imitate mobile camera noise

I want to train a super-resolution model that I will further apply to text images. The goal is to work with camera-captured images of text, increase the resolution so that the quality of OCR increases....
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Facing memory error while converting Dicom data into array

I am building a disease classifier using Dicom scans for many patients. Different patient's scans have different number of slices. For example: Patient1's scan : 100 slices Patient2's scan : 500 ...
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Using a neural network to learn regression in image processing

I have a camera system with some special optics that warp the field of view of the camera, dependent on two variables, $\theta_1$ and $\theta_2$. Given a specific configuration of these two variables, ...
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orientation detection - images of govt. issued documents

Trying to figure out a macro approach to detecting orientation of documents that works across document types (maybe a pipe dream). We successfully used SIFT to detect orientation in documents where we ...
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How to process Dicom Images for CNN?

I am building a disease classifier. I have Dicom scans for many patients. The scans have different slice thickness, and different scans have different number of slices. However, the slice thickness ...
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Data Quality Assessment in Image Data

I'm working on a CNN model that classifies images. After scraping image files from the Internet, I found that many of them didn't look this way as described by the searching keyword (for example ...
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How to recognize product based on image using neural network?

Company has many products in their offer (some about 100,000), some of these are very similar to each other. In database there is available only one image per product. Company want to make possible ...
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illumination problem for face landmark detection

I trained dlib face landmark detection model using ibug and yaleB datasets. Accuracy of the model is dropping when a bright light or a shadow appears on the side face. Used default parameters and ...