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| author | Saumit Dinesan <justsaumit@protonmail.com> | 2023-05-09 15:52:06 +0530 |
|---|---|---|
| committer | Saumit Dinesan <justsaumit@protonmail.com> | 2023-05-09 15:52:06 +0530 |
| commit | d6c282a733ce0a3453361973c683d251e1493b2d (patch) | |
| tree | 407ea8efecd312f428ecbdca52d9c2ab562fbacb /face-detection | |
| parent | b5a95a1456043e9f14c10ea7dc192545bcf28027 (diff) | |
face_capture_dataset: Slight refactor+comments for params & bounding box
Diffstat (limited to 'face-detection')
| -rw-r--r-- | face-detection/01_face_capture_dataset.py | 14 |
1 files changed, 8 insertions, 6 deletions
diff --git a/face-detection/01_face_capture_dataset.py b/face-detection/01_face_capture_dataset.py index a56a274..c72a14a 100644 --- a/face-detection/01_face_capture_dataset.py +++ b/face-detection/01_face_capture_dataset.py @@ -6,10 +6,11 @@ from picamera2 import Picamera2 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') +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>----') @@ -29,7 +30,7 @@ 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) + cv2.putText(frame,'Count:'+str(int(count)),pos,font,height,textcolor,weight) #Convert fram from BGR to grayscale frameGray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) @@ -42,13 +43,14 @@ while True: ) for (x,y,w,h) in faces: #create a bounding box across the detected face - cv2.rectangle(frame, (x,y), (x+w,y+h), (255,0,0), 3) #tuple + 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 + # 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 |