Spacing and Tab Fixes in __main__.py

Renamed functions to use underscores and lowercase rather than camel case.
Made minor spacing changes.

src/__main__.py

@@ -4,20 +4,20 @@ from matplotlib import pyplot as plt
 import os
 import file_data
 
+
 def main():
+	# Read in all images
+	images = read_images()
 
-	#Read in all images
+	# Read in data from Section001_Data.txt
-	images = readImages()
-
-	#Read in data from Section001_Data.txt
 	specimen, load_disp_data = file_data.read_file("../Section001_Data.txt")
 	
-	#Keep track of Stress and Strains
+	# Keep track of Stress and Strains
 	stresses = []
 	strains = []
 
-	#Get distances using sift
+	# Get distances using sift
-	distances = getSiftDistance(images[0], images[1])
+	distances = get_sift_distance(images[8], images[9])
 
 	# These distances are coming out as zero for some reason.
 	# Still trying to figure out if it's a bug in the code I
@@ -29,7 +29,7 @@ def main():
 	print("MIN DISTANCE:")
 	print(min(distances))
 
-	#Eventually we'll find the distances, stress, strain for all images
+	# Eventually we'll find the distances, stress, strain for all images
 	"""
 	for idx in range(0, len(images)-1):
 		distances = getSiftDistance(images[idx], images[idx+1])
@@ -39,28 +39,32 @@ def main():
 	"""
 
 
-def readImages():
+def read_images():
-	image_dir = '../images/'
+	image_dir = '../Images/'
 	filenames = os.listdir(image_dir)
 
 	images = []
 	for file in filenames:
-		images.append(cv2.imread(os.path.join(image_dir,file)))
+		images.append(cv2.imread(os.path.join(image_dir, file)))
+
 	return images
 
-def getStrain(length, displacement):
+
+def get_strain(length, displacement):
 	return displacement / length
 
-def getYoungsModulus(strain, stress):
-	return strain / stress
 
-def getSiftDistance(img1, img2):
+def get_youngs_modulus(strain, stress):
+	return stress / strain
+
+
+def get_sift_distance(img1, img2):
 	""" Gets distance between matching pts in
 		img1 and img2.
 	"""
 	sift = cv2.xfeatures2d.SIFT_create()
-	original_kp, original_des = sift.detectAndCompute(img1,None)
+	original_kp, original_des = sift.detectAndCompute(img1, None)
-	new_kp, new_des = sift.detectAndCompute(img2,None)
+	new_kp, new_des = sift.detectAndCompute(img2, None)
 
 	bf = cv2.BFMatcher()
 	matches = bf.knnMatch(original_des, new_des, k=2)
@@ -69,10 +73,10 @@ def getSiftDistance(img1, img2):
 	good = []
 
 	for m, n in matches:
-	    if m.distance < 0.3 * n.distance:
+		if m.distance < 0.3 * n.distance:
-	        good.append(m)
+			good.append(m)
 
-	# Draw matches 
+	# Draw matches
 	"""
 	# Uncomment to print matches between img1 and img2.
 	# SIFT may not be the best method based off the matched
@@ -86,7 +90,7 @@ def getSiftDistance(img1, img2):
 	pts1 = np.float32([original_kp[m.queryIdx].pt for m in good])
 	pts2 = np.float32([new_kp[m.trainIdx].pt for m in good])
 
-	#convert to complex number
+	# convert to complex number
 	z1 = np.array([[complex(c[0],c[1]) for c in pts1]])
 	z2 = np.array([[complex(c[0],c[1]) for c in pts2]])
 
@@ -96,7 +100,5 @@ def getSiftDistance(img1, img2):
 	return distances
 
 
-
-
 if __name__ == '__main__':
-	main()
+	main()