print path
# Get SKY REGION MASK
sky_region_mask = ImageProcess.getSkyRegion(path)
# Get Sun Orbit among three-day image stream using SUN REGION MASK
sun_orbit = []
sun_orbit = ImageProcess.getSunOrbit(path_1, path_2, path_3, sky_region_mask)
# Get Centroid of all the Detected Sun in sun_orbit.
centroid_list = []
centroid_list = ImageProcess.getCentroidList(sun_orbit)
# Fit the centroid list sample to a quadratic equation(general parabola).
theta, coeffs = ImageProcess.generalParabola(centroid_list)
# Detect sun of test image
img_centroid_radius = ImageProcess.sunDetect(filename, sky_region_mask)
# percentage = 0.0
if img_centroid_radius is not None and ImageProcess.sunDetectUsingOrbit(img_centroid_radius, theta, coeffs):
# Sun Detected!
percentage = ImageProcess.calculateCloudCoverage(filename, sky_region_mask, img_centroid_radius)
else:
percentage = ImageProcess.calculateCloudCoverage(filename, sky_region_mask)
print 'Cloud Coverage = ', percentage
cv2.imshow('final result', sky_region_mask)
cv2.waitKey(0)
l1, l2_1, l2_3, l3 = ImageProcess.findMatchingFilenameBetweenTwoDay(images_d1_filename_list, images_d2_filename_list, images_d3_filename_list)
print ("l1 length = " , len(l1))
print ("l2_1 length = " , len(l2_1))
print ('l2_3 length =', len(l2_3))
print ('l3 length = ', len(l3))
print ("l3 = ", l3)
# Get filtered file in each day
images_d1_filter = images_d1.filter(lambda x: x[0] in l1)
images_d21_filter = images_d2.filter(lambda x: x[0] in l2_1)
images_d23_filter = images_d2.filter(lambda x: x[0] in l2_3)
images_d3_filter = images_d3.filter(lambda x: x[0] in l3)
# For each filtered file, apply Sun Detect Function
images_d1_sunDetect = images_d1_filter.map(lambda x: ImageProcess.sunDetect(x[1], sky_region_mask.value))
images_d21_sunDetect = images_d21_filter.map(lambda x: ImageProcess.sunDetect(x[1], sky_region_mask.value))
images_d23_sunDetect = images_d23_filter.map(lambda x: ImageProcess.sunDetect(x[1], sky_region_mask.value))
images_d3_sunDetect = images_d3_filter.map(lambda x: ImageProcess.sunDetect(x[1], sky_region_mask.value))
# Sun Intersection Detect. (Note: coalesce to only ONE group to do this.)
images_d12_intersect = images_d1_sunDetect.coalesce(1).zip(images_d21_sunDetect.coalesce(1)).filter(lambda x: x[0] is not None and x[1] is not None and ImageProcess.intersectionDetect(x[0], x[1])).collect()
images_d23_intersect = images_d3_sunDetect.coalesce(1).zip(images_d23_sunDetect.coalesce(1)).filter(lambda x: x[0] is not None and x[1] is not None and ImageProcess.intersectionDetect(x[0], x[1])).collect()
print (images_d12_intersect)
print (images_d23_intersect)
# Get intersection sun centroid list
centroid_list = ImageProcess.getCentroidList(images_d12_intersect + images_d23_intersect)
print (centroid_list)
