I have 2 datasets of the same object but both obtained in different coordinate systems. One is in the coordinates obtained from an image [pixel data] so the coordinates are relative to the image. The other system is the WGS84 system.
I need to convert the points in the image pixel system by mapping them to their corresponding relative points in the WGS84 system using python.
The information I have is as follows:
The image data is in this format:
pixIndex X Y R G B
1 0 0 227 227 227
2 1 0 237 237 237
3 2 0 0 0 0
4 3 0 232 232 232
5 4 0 233 233 233
... ... ... ... ... ... ...
The original data:
How should I go about with calculating the mapping the points in the pixel dataset to it's equivalent in the WGS84 format? I am assuming a simple addition would do? How would the code look like? This is how I am loading my file
import pandas as pd
df = pd.read_csv("imagedata.txt", header=None, names =["pixIndex","X","Y","R","G","B"] )
print(df)
I was looking at this but not sure how to use it for my case: Convert X,Y pixel to Longitude and Latitude
From loading the 2 datasets in cloud compare, I know that the bounding box dim for the original dataset is
And for the image dataset the box dimensions are as follows:
which would give us the max and min of the coord system for each dataset, I suppose after looking at the linked article~
Need help with generating the code in python to do this mapping.
Appreciate the help! thank you!!
