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Last active Aug 29, 2015
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Analyzing Crop Yields By Drone (in Python!)
# Based on the Mathematica blog post:
# Screenshot:
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)
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)
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