added old file to start off with

Face_Detect with borders.py

@@ -0,0 +1,78 @@
+import cv2
+import numpy as np
+
+def check_within(imgSize, baseMultiplier, currentX, currentY, currentW, currentH):
+    
+    baseYbottom = imgSize[0] * baseMultiplier
+    baseXRight = imgSize[1] * baseMultiplier
+    upperMultiplier = 1 - baseMultiplier
+    baseYTop = imgSize[0] * upperMultiplier
+    baseXLeft = imgSize[1] * upperMultiplier
+    currentBottomY = currentY + currentH
+    currentRightX = currentX + currentW
+
+    print(str(baseYbottom) + "    " + str(currentY))
+
+    if baseYbottom > currentY:
+        return (255, 255, 255)
+    elif baseYTop < currentBottomY:
+        return (0, 0, 0)
+    elif baseXRight > currentX:
+        return (255, 0, 0)
+    elif baseXLeft < currentRightX:
+        return (0, 0, 255)
+    else:
+        return(0, 255, 0)
+
+cap = cv2.VideoCapture(0, cv2.IMREAD_GRAYSCALE) # instead of grayscale you can also use -1, 0, or 1.
+faceCascade = cv2.CascadeClassifier(r"C:\Users\Owner\Desktop\Face Detection\haar_frontface.xml") # CHECK THIS FIRST TROUBLE SHOOTING
+
+tmp, frm = cap.read()
+height, width, channels = frm.shape
+print(f"{height*.25}, {width}")
+del tmp, frm
+
+#Color is 1, grayscale is 0, and the unchanged is -1
+while(True):
+    ret, frame = cap.read()
+    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+ 
+    # Detect faces in the image
+    faces = faceCascade.detectMultiScale(
+    gray,
+    scaleFactor=1.1,
+    minNeighbors=5,
+    minSize=(30, 30)
+    )
+
+    print("Found {0} faces!".format(len(faces)))
+
+    # Draw a rectangle around the faces
+    for (x, y, w, h) in faces:
+        color = check_within([height, width], .1, x, y, w, h)
+        cv2.rectangle(frame, (int(width*.1), int(height*.1)), (int(width*.9), int(height*.9)), (150, 0 , 150))
+        cv2.rectangle(frame, (x, y), (x+w, y+h), color)
+        cv2.imshow('frame', frame)
+
+    if cv2.waitKey(1) & 0xFF == ord('q'):
+        break
+
+cap.release()
+cap.destroyAllWindows()
+
+
+# you can save the image with 
+# cv2.imwrite('watchgray.png',img)
+
+'''
+instead of the above code you can replace everything below 
+img = cv2....
+with
+
+plt.imshow(img, cmap = 'gray', interpolation = 'bicubic')
+plt.xticks([]), plt.yticks([])  # to hide tick values on X and Y axis
+plt.plot([200,300,400],[100,200,300],'c', linewidth=5)
+plt.show()
+
+for a matplotlib chart
+'''