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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How to remove augmented data from test data
I am working with this dataset https://data.mendeley.com/datasets/hxsnvwty3r/1 for object classification model like CNN. In the description of the dataset, I see in the description there are "...
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Object Classification Dataset Creation
There is a problem I've faced recently which I'm not sure my approach is proper or not. There is bunch of field videos which I run a semi-supervised detection model to extract crops to train my ...
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Histogram of Oriented Gradients (HOG) - Why normalize 16x16 blocks and not the whole picture?
I'm trying to learn Histogram of Oriented Gradients (HOG)
I understand why we compute the gradient and the orientation and also map every gradient into a 9 binaries histogram that spans from 0 to 180.
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Loading large raster dataset in to tensorflow
I am building a convolutional neural network for processing air quality concentration fields and meteorological parameter distribution. The input data are in Geotiff and NetCDF formats, which I load ...
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annotation file for ham10000
I am attempting to train a Faster R-CNN model using the HAM10000 dataset. However, I have been unable to locate an annotation file specifically for this dataset. I am seeking guidance on the most ...
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how to fill null values for images
I am dealing with product features like images, color, type of product, etc and my problem is simple classification and I have nans in the images column I am thinking about filling nans with a blank ...
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Is there an unified pipeline to convert a 4D nifti noisy pet scan image to an averaged, denoised, 3D Nifti image?
What I'm looking is to do at least the step 2 of ADNI pre processing (coregistered, averaged): https://adni.loni.usc.edu/methods/pet-analysis-method/pet-analysis/
OASIS-3 dataset provides FDG PET ...
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How to remove the hotspots from given image by using Python and opencv?
In the picture below there are some regions which are very bright (i.e. more white). Some bright regions are wide and some are narrow or thin. The red box covers one such wide bright spot, and blue ...
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Different validation sets give very different results. What can be the reason?
I have ~78k microscopy images of single cells, where the task is to classify for cancer (binary classifier). The images are labeled according to which patient the data came from. I do the train-val ...
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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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Overfitting still exists using different techniques on voice classification
I have 986 voice signals which have been collected by our team. The data set includes 745 healthy and 150 unhealthy voice signals. I split the data into 70% training and 20% validation and 10% test (...
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Facing Problems in Dilation and Erosion of Segmented Images of Knee X-Rays
I am working on a project to grade the severity of Knee Osteoarthritis using X-Ray Images. Before feeding the images into the machine learning model and enhancing the features of Knee osteoarthritis i....
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How to create a custom labelled dataset for self-supervised learning on images
[SOLVED] The code has been updated: I wish to create an image dataset for self supervised learning, where I have a dataset of 1000 unlabelled images (.jpg files). I wish to create 4000 labelled images ...
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How do I represent multiple seconds of video in tensors?
I want to use ResNet-18 for image features at the head of a VAE. If I have 10 seconds of video at 30 frames per second, and if ResNet-18 gives me the features of a single frame as a 512-dimensional ...
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ReLu layer in CNN (RGB Image)
I am able to get convoluted values from RGB Image lets say for each channel.
So I have red channel with values: -100,8,96,1056,-632,2,3....
Now what I do is that I ...
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OpenCV add/subtract functions produce different results from numpy array add/subtract
Im trying to brighten and dim an image using OpenCV with two approaches.
Approach 1: Used OpenCV's add and subtract functions to ...
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How to change the color of sock images while preserving their natural texture?
In our company, we have a large number of sock images that we need to modify. We want to change the color of specific parts of the sock image, while preserving the natural texture of the socks. We're ...
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Getting error "Failed to find data adapter that can handle input" even after converting list to array
I am getting this error : ValueError: Failed to find data adapter that can handle input' I even changed the list to arrays but still the error keeps pooping up.
This is the code:
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keras model.fit() with data generator error
I want to use a DataGenerator but I get this error.
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Best practice for large size image handling/processing with neural network
I have tried some neural network architectures for object classification and recognition. Such neural networks can distinguish cats from dogs, classify numbers from MNIST dataset, and recover private ...
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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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Clustering on Raw Image Pixel Array
I have an array in the shape of (105, 105, 3). When I do plt.imshow(array) it outputs:
How can I run a clustering algorithm directly on this image? Do I need to convert the pixels to cartesian ...
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pytesseract performance for digit recognition
The sequence in the following image
is correctly recognized by pytesseract via the usual function "pytesseract.image_to_string". But the following image with a similar sequence is not ...
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Image Classification task with unevenly sized tiled images
I'm using a Tensorflow CNN in Python for Image Classification. My data consists of huge images that necessitate splitting into smaller tiles. However, the number of tiles differs per image as the ...
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Which loss function to use image generation?
What loss function we can for image generation task and colorful and large images?
Suppose if we have an auto-encoder for an image with size of (300,300,3), we will ...
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find correlation two sets of pathology pictures
I have two sets (A&B) of pictures. set A is a stress map exported from ABAQUS. Set B is a map of pathology stain (h&e) in which cell content is important. I can drive cells map with image ...
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Proper way to reshape a image for training using CNN
I am new to Keras and facing some problems figuring out how to reshape the input image data properly. I have $16 x 16$ images, each with three layers, i.e., R, G, and B. The image data is in the form ...
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How to choose the threshold for recurrence plot?
Context: I'm doing the final project for my bachelors and it's about identifying apnea in eeg signals with a CNN. I'm dividing the signal in equally sized segments and then generating images for each ...
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How to convert Torchvision image tensor to base64 directly?
I have this code that is supposed to convert an image entry of a Torchvision dataset to a base64 string. To do that, it serializes the tensor from a Torchvision dataset to a string, modifies that ...
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What is the optimal camera resolution for resnet1024x1024?
I am going to buy a camera for image inference using SSD resnet 1024x1024, I read on internet image quality will drop if resize an image bigger than its original size. In my case if I use a 1920x1080 ...
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Best Image Embeddings technique for video similarity
The problem description:
Given a large dataset of video (and growing rapidly) we are embedding every frame of every video and comparing frames to each other to find identical and near identical frames....
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What is the relationship between HOG (Histogram Of oriented spat. Grad) and HOF (Histogram Of optical Flow)?
What is the difference between those two descriptors and what is their relation? I'm asking because most of the time when I stumble into the one I also stumble into the other, it feels like they're ...
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OpenCV isn't processing all the images in a directory
I'm really trying to apply CLAHE to a directory of about 700 images. However, once I manage to get it running, for some reason the code stops before all the images are processed.
When I run it on ...
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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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Rotating and cropping scanned images with OpenCV2
I wrote a script to take scanned images and crop out the background from them as well as rotate them to the proper orthogonal orientation (my set of images were not initially scanned properly and many ...
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Converting images in a directory into a vector to calculate cosine distances?
I'm currently going through issues in terms of acquiring multiple images at once to convert them to a vector for calculating the cosine distance to get similarity between say an image from the ...
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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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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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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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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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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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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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