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.
159 questions
0
votes
1
answer
25
views
flow_from_directory returns no image eventhough os.listdir() gives the count of files present correct
I am new to DL in terms of Image tasks. Here is the snippet I am using for Data generators for training and testing
...
- 5
1
vote
1
answer
35
views
PyTorch noise estimator model not learning - converges to same output regardless of input
I'm implementing a simple noise estimator using PyTorch. The model consists of a few convolutional layers followed by a small fully connected network, ending with a single neuron that outputs the ...
1
vote
1
answer
271
views
Downsampling an image in the right way
I was not shure where to ask this question, but SE Data Science seems to be the best place for it.
So I tried to build a CNN based super resolution model. Unfortunately I have only high-res images but ...
- 133
0
votes
0
answers
16
views
I want to create a system for classifying bone fractures What pre-processing steps can I use to process images?
I want to know where I should put the image preprocessing code in the decision tree code
How to extract features from images and classify them
0
votes
0
answers
7
views
What's the intuitively best option for preprocessing images of varying aspect ratios and resolutions?
We've got a complex pipeline that produces a crop of the minimum possible subset image that includes all useful information. We've got a number of customers using various models on these images, and ...
- 101
0
votes
0
answers
12
views
what are Non-AI methods in detecting how much brown pixels an image have
looking for a non-AI approach on how to find how much "brown" color a 256x256 px image have. I am making a dataset that will be used as training data for AI later on. There are several ...
- 101
1
vote
1
answer
59
views
Find closest color class to an RGB value
I have a module that estimates the color of an object and returns an RGB value in this format: (40, 48, 68) which corresponds to this color:
Now I have to classify ...
- 227
0
votes
1
answer
33
views
Image Classification when image is a plot of two functions
My goal is to perform a supervised classification of a number of objects. Each object is described by a plot of two functions, f(t) and g(t).
The plot dimensions, (b - a) and T, are about the same ...
- 133
0
votes
0
answers
26
views
Should I remove the watermarks of my images before training Yolov8?
I would like to train a Yolov8 network in an animal detection task using camera trap images. Some camera trap images have information added to them such as date, time, day of the week, camera brand, ...
- 1
2
votes
2
answers
135
views
Seeking Guidance on Constrained Input Modeling for Soil Moisture Correction Using Rainfall Observations
I find myself immersed in the intricacies of working with 2D modeled fields (images) representing soil moisture in regions where direct observations are unfortunately absent. However, there is a ...
0
votes
0
answers
19
views
How can i create model to match nested geometric image with child geometric images
image1 is a nesting file and image2 is child file ,i want to find child file is contain in nesting file or not.We tried using random forest but it did not work.can you suggest some good image matching ...
0
votes
1
answer
32
views
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 ...
- 38
0
votes
1
answer
353
views
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.
...
- 115
1
vote
0
answers
53
views
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 ...
- 111
0
votes
1
answer
45
views
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 ...
0
votes
0
answers
31
views
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 ...
- 143
6
votes
2
answers
2k
views
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 ...
- 155
1
vote
1
answer
138
views
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 ...
0
votes
1
answer
93
views
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 (...
- 1
0
votes
1
answer
114
views
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 ...
- 103
0
votes
1
answer
672
views
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 ...
- 103
0
votes
0
answers
179
views
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:
...
0
votes
1
answer
71
views
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 ...
1
vote
1
answer
728
views
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 ...
0
votes
1
answer
457
views
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 ...
- 111
0
votes
1
answer
881
views
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 ...
2
votes
0
answers
1k
views
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 (...
0
votes
0
answers
152
views
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 ...
- 1
0
votes
1
answer
103
views
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 ...
- 11
1
vote
2
answers
1k
views
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 ...
- 11
0
votes
1
answer
438
views
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-...
- 1
0
votes
0
answers
3k
views
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:
...
- 1
0
votes
1
answer
498
views
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 ...
- 103
1
vote
0
answers
83
views
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 ...
- 113
1
vote
1
answer
428
views
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 ...
- 13
0
votes
0
answers
568
views
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, ...
- 11
1
vote
0
answers
23
views
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 ...
- 11
0
votes
1
answer
44
views
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 ...
1
vote
1
answer
2k
views
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 ...
- 135
1
vote
0
answers
20
views
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:
...
1
vote
1
answer
156
views
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 ...
- 27
3
votes
0
answers
312
views
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 ...
- 131
1
vote
2
answers
1k
views
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 ...
- 157
0
votes
1
answer
41
views
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 ...
- 1,282
4
votes
2
answers
11k
views
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:
...
- 41
0
votes
0
answers
34
views
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 ...
- 1
0
votes
1
answer
21
views
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....
- 61
1
vote
1
answer
243
views
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 ...
- 113
0
votes
0
answers
3k
views
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 ...
- 21
0
votes
1
answer
568
views
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 ...
- 240