END

V2rgb.m

@@ -13,6 +13,12 @@
 
 
 % Loop through the images selected
+
+% Initialize a matrix to store RGB values
+all_rgb = zeros(900, 3, 61, 101);
+
+% Initialize iteration
+a=0;
 for i = 100:1000
   % Set the image path
   image_path = imread(sprintf('frame2_%d.jpg', i));
@@ -23,12 +29,6 @@ for i = 100:1000
   imwrite(roi, (sprintf('frames/my_imagev2%d.jpg',i)));
 end
 
-% Initialize a matrix to store RGB values
-all_rgb = zeros(900, 3, 61, 101);
-
-% Initialize iteration
-a=0;
-
 % Loop through 900 images
 for i = 100:1000
   % Read image
@@ -51,6 +51,7 @@ for i = 100:1000
   % Display iteration
   disp(a);
 end
+
 % Compute mean RGB values for each image
 mean_rgb = squeeze(mean(mean(all_rgb, 4), 3));
 save('mean_rgb.m', 'mean_rgb');
@@ -115,7 +116,7 @@ hold off;
 
 xlabel('Frequency (Hz)');
 ylabel('Magnitude');
-legend('Red', 'Green', 'Blue');
+legend({'Red', 'Green', 'Blue'});
 
 % Find indices in f that correspond to the frequency range of interest
 idx_range = find(f >= 0.75 & f <= 4);

video to image.py

@@ -13,9 +13,6 @@ total_frames = int(video.get(cv2.CAP_PROP_FRAME_COUNT))
 frame_number = 0
 while True:
     success, frame = video.read()
-    if not success:
-        break
-    if frame_number % int(frame_rate / 24) == 0:
     cv2.imwrite("frame2_{}.jpg".format(frame_number), frame)
     frame_number += 1