diff --git a/.vscode/settings.json b/.vscode/settings.json
deleted file mode 100644
index b26f7c4..0000000
--- a/.vscode/settings.json
+++ /dev/null
@@ -1,3 +0,0 @@
-{
-    "python.pythonPath": "/bin/python"
-}
\ No newline at end of file
diff --git a/README.md b/README.md
new file mode 100644
index 0000000..8b6999a
--- /dev/null
+++ b/README.md
@@ -0,0 +1,20 @@
+# Kestrel focusing script
+
+## Requirements
+make sure to install python 3.9.7 or better
+Install requirements with
+```pthon
+python3 -m pip install -r requirements.txt
+```
+It could also be just python depending on system naming conventions
+```pthon
+python -m pip install -r requirements.txt
+```
+
+## Description
+The script will pull from the video device described by 
+```python
+cap = cv2.VideoCapture(1)
+```
+where the number is the video device iterated by the operating system. If you have only one device it will be populated on "0". If you have two, than the second would be populated on "1". Change this according to your setup. 
+
diff --git a/main.py b/main.py
index 5b994eb..cafc64f 100644
--- a/main.py
+++ b/main.py
@@ -1,9 +1,13 @@
 import cv2
 import numpy as np
+
+# Capture device number
 cap = cv2.VideoCapture(1)
+
+# Set capture resolution
 cap.set(cv2.CAP_PROP_FRAME_WIDTH, 1280)
 cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 720)
-max_count = 0
+max_count = 1
 
 # Text
 font = cv2.FONT_HERSHEY_SIMPLEX
@@ -12,31 +16,46 @@ org2 = (50, 90)
 fontScale = 1
 color = (255, 0, 0)
 thickness = 2
+
+# Subwindow size
 scale = 6
+
+# Main loop
 while True:
+    #Grab frame
     ret, src = cap.read()
+
+    # Get sub window size
     center = (int(src.shape[0]/2),int(src.shape[1]/2))
     upper_left = (int(center[1] - src.shape[1]/scale),int(center[0] - src.shape[0]/scale))
     lower_right = (int(center[1] + src.shape[1]/scale),int(center[0] + src.shape[0]/scale))
 
+    # Color conversion
     gray = cv2.cvtColor(src[upper_left[1]:lower_right[1],upper_left[0]:lower_right[0]], cv2.COLOR_BGR2GRAY)
+    # Edge detection
     sobel = cv2.Sobel(gray, cv2.CV_8U, 1, 0, ksize=3)
+    # Thresholding operation
     t, thresh = cv2.threshold(sobel, 200, 255, cv2.THRESH_BINARY)
     count = np.sum(sobel)
     if count > max_count:
         max_count = count
 
+    # Text rendering
     src = cv2.putText(src, 'Max: {}'.format(int(max_count/10000)), org, font, fontScale,
                       color, thickness, cv2.LINE_AA)
     src = cv2.putText(src, 'Current: {:.2f}%'.format((count/max_count)*100 - 0.01), org2, font, fontScale,
                       color, thickness, cv2.LINE_AA)
+    # Subwindow Outline
     src = cv2.rectangle(src, pt1=upper_left, pt2=lower_right, color=(36,255,12), thickness=1)
+
+    #Display of results
     cv2.imshow('tresh', thresh)
     cv2.imshow('src', src)
     cv2.imshow('sobel', sobel)
-    
+
+    # Frame waiting and logic loop    
     k = cv2.waitKey(10)
-    if k == 27:
+    if k == 27: #Escape key to escape
         break
-    elif k == 32:
-        max_count = 0
+    elif k == 32: # Spacebar to reset count
+        max_count = 1