Questions tagged [image-preprocessing]
285 questions
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How to convert raster map to shapefile (raster map boundaries to vector center line shapefile)
I have a raster map in tiff format and I am trying to convert it into smooth shape file. but I guess due to pencil drawn lines its output is in the weird shape file which you can show in the screen shots.
Input tiff file (it is in greyscale):
This…
Saddam Hussain
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How to perform preprocessing steps on image dataset once, so that it can be used for training and testing the model many times
I am training different networks like VGG16, Resnet, Densenet, Squeezenet etc. on image dataset.
I am performing following steps before training.
train_dataset = torchvision.datasets.ImageFolder(
root=TRAIN_ROOT,
…
Prajakta Rathod
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How to improve performance metrics of Deep learning model (VGG 19)?
I collected this code and got great accuracy on training and validation accuracy (more than 90%). But it shows a disastrous performance metrics. Here is the collected code:
from google.colab import drive
drive.mount('/content/drive')
import numpy…
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1 answer
Ambiguous data cardinality when training CNN
I am trying to train a CNN for image classification. When I am about to train the model I run into the issue where it says that my data cardinality is ambiguous.
I've checked that the size of both the image and label set are the same so I am not…
gusifer98
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vit-base-beans preprocessing images
I'm using this code to build a new model from a pretrained model VIT, and i want to understand the pre processing of the images.
here is the code :
!pip install datasets transformers
from datasets import load_dataset
ds = load_dataset('beans',…
Rafik Frtas
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Is blur pixelated images a good practice to improve the results in a CNN or it would worse the results?
Im new at using CNN and I have some images I pretend to use like this car picture that previously I resized to be larger but as you can see, now it is a bit pixelated.
Should I blur them to improve my results? Or pixelization wont affect the final…
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converting from h5 to nifty files
i have some left atrium data that is h5 form and i was wondering if its possible to change into niftis so i can train my model
I have done this already with dicom to nifties using dicom2niftis package however i couldent find one for h5 to nifty…
Omx Elta
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OCR text line separation and characters separation
I am creating a Sanskrit OCR.
So, I just want to know how to do text line separation from image, then text line to characters separation and how to separate symbols added with characters?
I tried hough transform with a threshold of 50 but it's not…
Ankur Singh
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Image Pre-processing for OCR (pytesseract)
I'm trying to OCR image with pytesseract. Once I do the OCR for below image the result shows as "WV over"
What are the image pre-processing techniques that can be use to enhance this image by filling missing parts of text.
Enhance image OCR ability…
Chinthaka
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LIDC-IDRI Lung CT image dataset preprocessing steps and code (Python)
I am new to the lung ct image processing domain. While working with the LIDC-IDRI dataset, I found different methods/steps given on the corresponding website. The content does not share any code snippets or examples for the same.
Could anyone share…
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camera based event - how many event belongs to light system
I have a CSV file that contains: "timestamp", "x", "y", and "polarity" by a camera-based event.
For…
efrat
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divide image after convert it to grey
i have data set of images
first i read the image then i convert it to grey and i want to save it after dividing each grey image by 255
i try
files = os.listdir(path)
for file in files:
folder = os.listdir(newdir+'\\'+file)
for f in folder:
…
Ahmed Abd El-Samie
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Tesseract is detecting 1 as t
I am trying to extract emails from screenshots.
This is the image-
Image with email
You can see in this image, there is an email.
This is my code-
image = cv2.imread('image_name.jpg')
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
thresh =…
ajaygarg
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How to preprocess image better to identify number on same colored background?
I want to find a way to detect the red number 3 which is on a red background. I've tried changing the contrast on the image, as well as also trying a blur + adaptive thresholding, which both don't detect anything. What's interesting is I can't…
bigfry
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RuntimeError: Given groups=1, weight of size [32, 3, 3, 3], expected input[8, 1, 256, 256] to have 3 channels, but got 1 channels instead
I got this error RuntimeError: Given groups=1, weight of size [32, 3, 3, 3], expected input[8, 1, 256, 256] to have 3 channels, but got 1 channels instead. This is my code
I haven't found the cause for this. Can anyone help me to figure out the…
Nao
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