Python automating task related to images
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Description
Experience Level: Expert
I need help in automating my python program. I have a csv file, it contains 4 columns and 44 rows. The details are as follows:
First column: Image name
Second column: pixel coordinates
Third column is a matrix of 588 values (14 x 14 x 3) of an RGB image 1
Fourth column is a matrix of 588 values (14 x 14 x 3) of an RGB image 2
What I need is:
Step 1: Select the 588 values of image 2 (fourth column) and divide (floating point division) each pixel value by 255. We will get new matrix, having results after floating point division.
Step 2: Select 588 values of image 1 (third column) and subtract them with the result obtained after the division in step 1. We will get a new matrix of 588 values.
Step 3: Consider the pixel coordinates (second column) and go the corresponding image, by considering the image name (first column). Replace the pixel values by the result obtained in step 2. A new image is obtained.
Step 4: Give the new image obtained in step 3 to a machine learning algorithm (I already have the working code ready). If this new image (obtained in step 3) still matches to the same class as the original image, repeat step 1 to 3. Every time you repeat, increment a counter. Stop this process when the new image matches to a different class.
Note: I will explain every step in great detail, I only need your help in automation. The code is working without errors and I can do above process for individual images.
First column: Image name
Second column: pixel coordinates
Third column is a matrix of 588 values (14 x 14 x 3) of an RGB image 1
Fourth column is a matrix of 588 values (14 x 14 x 3) of an RGB image 2
What I need is:
Step 1: Select the 588 values of image 2 (fourth column) and divide (floating point division) each pixel value by 255. We will get new matrix, having results after floating point division.
Step 2: Select 588 values of image 1 (third column) and subtract them with the result obtained after the division in step 1. We will get a new matrix of 588 values.
Step 3: Consider the pixel coordinates (second column) and go the corresponding image, by considering the image name (first column). Replace the pixel values by the result obtained in step 2. A new image is obtained.
Step 4: Give the new image obtained in step 3 to a machine learning algorithm (I already have the working code ready). If this new image (obtained in step 3) still matches to the same class as the original image, repeat step 1 to 3. Every time you repeat, increment a counter. Stop this process when the new image matches to a different class.
Note: I will explain every step in great detail, I only need your help in automation. The code is working without errors and I can do above process for individual images.
Rajesh K.
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6 May 2024
United States
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