corrected output from 900+ csv to 1 with all RGB traces averages // split code into 3 functions

RGB_channels.py

@@ -1,27 +1,24 @@
 import cv2
-from PIL import Image
 import csv
 import os
 import os.path
 
-#create a directory to store the RGB datas ouptut
-path_to_script = os.path.dirname(os.path.abspath(__file__))
-if os.path.exists(path_to_script + r"\RGB database") == False:
-	os.mkdir(path_to_script + r"\RGB database")
+def rep_files_init():
+	#create a directory to store the RGB datas ouptut
+	path_to_script = os.path.dirname(os.path.abspath(__file__))
+	if os.path.exists(path_to_script + r"\RGB database") == False:
+		os.mkdir(path_to_script + r"\RGB database")
+	
+	onlyfiles = next(os.walk(path_to_script + r"\frames"))[2] #get the amount of frames previously extracted
+	frames_num = len(onlyfiles)-1
 
-onlyfiles = next(os.walk(path_to_script + r"\frames"))[2] #get the amount of frames previously extracted
-frames_num = len(onlyfiles)-1
-
-face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
-eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml') 
-image = "frames/frame1.jpg"
-read_img = cv2.imread(image)
-
-#cv2.imshow('img',imRGB)
-#cv2.waitKey(0)
+	return frames_num
 
 
 def RGB_dataframe(img, itr):
+	face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
+	eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')
+
 	gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
 	faces = face_cascade.detectMultiScale(gray, 1.3, 5)
 
@@ -64,24 +61,42 @@ def RGB_dataframe(img, itr):
 	#cv2.imshow('img',imRGB)
 	#cv2.waitKey(0)
 
+	R = []
+	G = []
+	B = []
 	size_list = list(imRGB.shape[:2])
 	pixel_values = []
 	for i in range(0, size_list[0]):
 		for j in range(0, size_list[1]):
 			k = imRGB[i,j]
-			pixel_values.append(k)
-	fields = ['R', 'G', 'B'] 
-	with open('RGB database/RGB' + str(itr) + '_data.csv', 'w', newline="") as f:
+			R.append(k[0])
+			G.append(k[1])
+			B.append(k[2])
+	return R, G, B
+
+def average_and_export():
+	i = 0
+	count = 0.1
+	pixel_values = []
+	frames_num = rep_files_init()
+	while i < frames_num:
+		i += 1
+		image = "frames/frame1.jpg"
+		read_img = cv2.imread(image)
+		out_colors = RGB_dataframe(read_img, i)
+		Ravg = sum(out_colors[0])/len(out_colors[0])
+		Gavg = sum(out_colors[1])/len(out_colors[1])
+		Bavg = sum(out_colors[2])/len(out_colors[2])
+		pixel_values.append([Ravg, Gavg, Bavg])
+		if i/frames_num >= count:
+			print(str(round(count*100))+ "% of the database exported to csv")
+			count += 0.1
+	
+	with open('RGB database/RGB_data.csv', 'w', newline="") as f:
+		fields = ['R', 'G', 'B'] 
 		write = csv.writer(f)
 		write.writerow(fields)
 		write.writerows(pixel_values)
-	return
+	return	
 
-i = 0
-count = 0.1
-while i < frames_num:
-	i += 1
-	RGB_dataframe(read_img, i)
-	if i/frames_num >= count:
-		print(str(round(count*100))+ "% of the database exported to csv")
-		count += 0.1
+average_and_export()