From 4205181c6b5a3ae2b878a27621565e0c59190b83 Mon Sep 17 00:00:00 2001
From: Saumit Dinesan <justsaumit@protonmail.com>
Date: Tue, 9 May 2023 14:16:15 +0530
Subject: face_capture_dataset: Migration to picamera2

---
 face-detection/01_face_capture_dataset.py | 65 ++++++++++++++++++++++---------
 1 file changed, 47 insertions(+), 18 deletions(-)

diff --git a/face-detection/01_face_capture_dataset.py b/face-detection/01_face_capture_dataset.py
index 7860210..ef40a82 100644
--- a/face-detection/01_face_capture_dataset.py
+++ b/face-detection/01_face_capture_dataset.py
@@ -1,30 +1,59 @@
 import cv2
 import os
-cam = cv2.VideoCapture(0)
-cam.set(3, 640) # set video width
-cam.set(4, 480) # set video height
+from picamera2 import Picamera2
+
+#Parameters
+count = 0
+pos=(30,60) #top-left
+font=cv2.FONT_HERSHEY_COMPLEX
+height=1.5
+color=(0,0,255) #BGR- RED
+weight=3
 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!")
+
+# Create an instance of the PiCamera2 object
+cam = Picamera2()
+## Set the resolution of the camera preview
+cam.preview_configuration.main.size = (640, 360)
+cam.preview_configuration.main.format = "RGB888"
+cam.preview_configuration.controls.FrameRate=30
+cam.preview_configuration.align()
+cam.configure("preview")
+cam.start()
+
 # Initialize individual sampling face count
-count = 0
-while(True):
-    ret, img = cam.read()
-    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
-    faces = face_detector.detectMultiScale(gray, 1.3, 5)
+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,color,weight)
+
+    #Convert fram 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(frameGray, 1.3, 5) # 3 parameters- frame,scale-factor,
     for (x,y,w,h) in faces:
-        cv2.rectangle(img, (x,y), (x+w,y+h), (255,0,0), 2)     
-        count += 1 # increment
-        # Save the captured image into the datasets folder
-        cv2.imwrite("dataset/User." + str(face_id) + '.' + str(count) + ".jpg", gray[y:y+h,x:x+w]) #req os
-        cv2.imshow('image', img)
-    k = cv2.waitKey(100) & 0xff # Press 'ESC' for exiting video
-    if k == 27:
+        #create a bounding box across the detected face
+        cv2.rectangle(frame, (x,y), (x+w,y+h), (255,0,0), 3) #tuple
+        count += 1 # increment count
+        # 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
+    # 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
+    if key == 27:  # ESCAPE key
+        break
+    elif key == 113:  # q key
         break
-    elif count >= 100: # Take 30 face sample and stop video capture
+    elif count >= 30: # Take 30 face sample and stop video capture
          break
-# Do a bit of cleanup
+# Release the camera and close all windows
 print("\n [INFO] Exiting Program and cleaning up stuff")
-cam.release()
+cam.stop()
 cv2.destroyAllWindows()
-- 
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