facedetection: Constants formatting + FixingTypos + AddingComments

1 files changed, 24 insertions, 20 deletions

diff --git a/face-detection/01_face_capture_dataset.py b/face-detection/01_face_capture_dataset.py
index c72a14a..edf271e 100644
--- a/face-detection/01_face_capture_dataset.py
+++ b/face-detection/01_face_capture_dataset.py
@@ -2,19 +2,19 @@ import cv2
 import os
 from picamera2 import Picamera2
 
-#Parameters
-count = 0
-pos=(30,60) #top-left
-font=cv2.FONT_HERSHEY_COMPLEX
-height=1.5 #font_scale
-textcolor=(0,0,255) #BGR- RED
-boxcolor=(255,0,255) #BGR- BLUE
-weight=3   #font-thickness
-face_detector=cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
+# Constants
+COUNT_LIMIT = 30
+POS=(30,60)  #top-left
+FONT=cv2.FONT_HERSHEY_COMPLEX #font type for text overlay
+HEIGHT=1.5  #font_scale
+TEXTCOLOR=(0,0,255)  #BGR- RED
+BOXCOLOR=(255,0,255) #BGR- BLUE
+WEIGHT=3  #font-thickness
+FACE_DETECTOR=cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
 
 # For each person, enter one numeric face id
 face_id = input('\n----Enter User-id and press <return>----')
-print("\n [INFO] Initializing face capture. Look the camera and wait!")
+print("\n [INFO] Initializing face capture. Look at the camera and wait!")
 
 # Create an instance of the PiCamera2 object
 cam = Picamera2()
@@ -26,42 +26,46 @@ cam.preview_configuration.align()
 cam.configure("preview")
 cam.start()
 
+count=0
+
 while True:
     # Capture a frame from the camera
     frame=cam.capture_array()
-    #Display count of images taken
-    cv2.putText(frame,'Count:'+str(int(count)),pos,font,height,textcolor,weight)
+    # Display count of images taken
+    cv2.putText(frame,'Count:'+str(int(count)),POS,FONT,HEIGHT,TEXTCOLOR,WEIGHT)
 
-    #Convert fram from BGR to grayscale
+    # Convert frame from BGR to grayscale
     frameGray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
-    #Create a DS faces- array with 4 elements- x,y coordinates top-left corner), width and height
-    faces = face_detector.detectMultiScale(
+    # Create a DS faces- array with 4 elements- x,y coordinates (top-left corner), width and height
+    faces = FACE_DETECTOR.detectMultiScale( # detectMultiScale has 4 parameters
             frameGray,      # The grayscale frame to detect
             scaleFactor=1.1,# how much the image size is reduced at each image scale-10% reduction
             minNeighbors=5, # how many neighbors each candidate rectangle should have to retain it
             minSize=(30, 30)# Minimum possible object size. Objects smaller than this size are ignored.
             )
     for (x,y,w,h) in faces:
-        #create a bounding box across the detected face
-        cv2.rectangle(frame, (x,y), (x+w,y+h), boxcolor, 3) #5 parameters - frame, topleftcoords,bottomrightcooords,boxcolor,thickness
+        # Create a bounding box across the detected face
+        cv2.rectangle(frame, (x,y), (x+w,y+h), BOXCOLOR, 3) # 5 parameters - frame, topleftcoords,bottomrightcooords,boxcolor,thickness
         count += 1 # increment count
+
         # if dataset folder doesnt exist create:
         if not os.path.exists("dataset"):
             os.makedirs("dataset")
         # Save the captured bounded-grayscaleimage into the datasets folder
-        cv2.imwrite("dataset/User." + str(face_id) + '.' + str(count) + ".jpg", frameGray[y:y+h,x:x+w]) #req os
+        cv2.imwrite("dataset/User." + str(face_id) + '.' + str(count) + ".jpg", frameGray[y:y+h,x:x+w])
 
     # Display the original frame to the user
     cv2.imshow('FaceCapture', frame)
     # Wait for 30 milliseconds for a key event (extract sigfigs) and exit if 'ESC' or 'q' is pressed
     key = cv2.waitKey(100) & 0xff
-    #Checking keycode
+    # Checking keycode
     if key == 27:  # ESCAPE key
         break
     elif key == 113:  # q key
         break
-    elif count >= 30: # Take 30 face sample and stop video capture
+    elif count >= COUNT_LIMIT: # Take COUNT_LIMIT face sample and stop video capture
          break
+
 # Release the camera and close all windows
 print("\n [INFO] Exiting Program and cleaning up stuff")
 cam.stop()