Analyzing Crop Yields By Drone (in Python!)

crops.py

# Based on the Mathematica blog post: http://community.wolfram.com/groups/-/m/t/551187
# Screenshot: http://i.imgur.com/caMxnBl.png

from sklearn.cluster import KMeans
import numpy as np
import cv2

img = cv2.imread("crops.png")
img = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)

pixels = img.reshape((img.shape[0] * img.shape[1], 3))

clt = KMeans(n_clusters=10)
clt.fit(pixels)

dominant_color = clt.cluster_centers_[np.argmax(np.bincount(clt.labels_))]

distances = np.sqrt(np.sum((img-dominant_color)**2, axis=-1))

normalized = (255 - distances/np.max(distances)*255).astype("uint8")

ret, binary = cv2.threshold(normalized, 180, 255, cv2.THRESH_BINARY)

soy_pixels = cv2.countNonZero(binary)
total_pixels = len(pixels)

print "Crop yield: %.2f%%" % (float(soy_pixels) / total_pixels * 100)

cv2.imshow("Soy Pixels", binary)
cv2.waitKey(0)
cv2.destroyAllWindows()