diff options
| -rw-r--r-- | face-detection/01_face_capture_dataset.py | 65 |
1 files 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() |