The use of Python classes is a level of abstraction that allows us to store functions and variables in an effective way. With a Python class we can modify/repeat our analysis in Python without much effort.

We have done an applied example of crop line recognition using a Python class. The procedure uses a drone orthophoto and a shapefile of an area of interest, has options for the filter and creates a shapefile from the recognized lines. 

Tutorial

Input data

You can download the input data from this link.

Code

from workingFunctions import cropRecognition
import geopandas as gpd

# create a crop recognition object
cropLines = cropRecognition('Data/Rst/Ortho-DroneMapper_Clipped2.tif')

# refine band red=1 green=2 blue=3
cropLines.band = 2

#plot selected band
cropLines.plotBand()

#define canny filter sigma to represent
cropLines.cannyMin, cropLines.cannyMean, cropLines.cannyMax = 4,5,6 #1,2,3

#display different canny filters
cropLines.cannyFilterDisplay()

#define selected canny filter
cropLines.cannySigma = 6

#show canny filter array
cropLines.cannyFilter

array([[False, False, False, ..., False, False, False],
       [False, False, False, ..., False, False, False],
       [False, False, False, ..., False, False, False],
       ...,
       [False, False, False, ..., False, False, False],
       [False, False, False, ..., False, False, False],
       [False, False, False, ..., False, False, False]])

#perform hough transform for crop line recornition
cropLines.displayHoughTransform()

#define the geometry of the area of interest
aoi = gpd.read_file('Data/Shp/aoi.shp')
cropLines.aoiGeom = aoi.iloc[0].geometry
cropLines.aoiGeom

#create lines in the area of interest extension
cropLines.linesToAoi()

#export interpreted data to shapefile
cropLines.createShapefile('Data/cropRows.shp')

#plot crop lines 
import rasterio
import matplotlib.pyplot as plt
from rasterio.plot import show

df = gpd.read_file('Data/cropRows.shp')
image = rasterio.open('Data/Rst/Ortho-DroneMapper_Clipped2.tif')
fig, ax = plt.subplots(figsize=(12,8))
lineShow = df.plot(column='angle', cmap='RdBu', ax=ax)
rasterShow = show(image, ax=ax, alpha=0.5)
plt.show()

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