Input
- Virtual Backgrounds (640x480 resolution) - From Downloaded Files
- Webcam
Output
- Processed Video Stream with Virtual Background
Run the Code:
#Created by MediaPipe
#Modified by Augmented Startups 2021
#Zoom Virtual Background in OpenCV Python
#Watch Computer Vision Tutorial at www.augmentedstartups.info/VisionStore
import cv2
import mediapipe as mp
import numpy as np
import time
mp_drawing = mp.solutions.drawing_utils
mp_selfie_segmentation = mp.solutions.selfie_segmentation
# For webcam input:
BG_COLOR = (0, 255, 196) # green screen
cap = cv2.VideoCapture(0)
prevTime = 0
with mp_selfie_segmentation.SelfieSegmentation(
model_selection=0) as selfie_segmentation:
bg_image = None
while cap.isOpened():
success, image = cap.read()
if not success:
print("Ignoring empty camera frame.")
continue
# Flip the image horizontally for a later selfie-view display, and convert
# the BGR image to RGB.
image = cv2.cvtColor(cv2.flip(image, 1), cv2.COLOR_BGR2RGB)
#print(image.shape)
# To improve performance, optionally mark the image as not writeable to
# pass by reference.
image.flags.writeable = False
results = selfie_segmentation.process(image)
image.flags.writeable = True
image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
# Draw selfie segmentation on the background image.
# To improve segmentation around boundaries, consider applying a joint
# bilateral filter to "results.segmentation_mask" with "image".
condition = np.stack(
(results.segmentation_mask,) * 3, axis=-1) > 0.1
# The background can be customized.
# a) Load an image (with the same width and height of the input image) to
# be the background, e.g., bg_image = cv2.imread('/path/to/image/file')
# b) Blur the input image by applying image filtering, e.g.,
# bg_image = cv2.GaussianBlur(image,(55,55),0)
bg_image = cv2.imread('backgrounds/1.png')
#bg_image = cv2.GaussianBlur(image, (55, 55), 0)
if bg_image is None:
bg_image = np.zeros(image.shape, dtype=np.uint8)
bg_image[:] = BG_COLOR
output_image = np.where(condition, image, bg_image)
#Get FrameRate
currTime = time.time()
fps = 1 / (currTime - prevTime)
prevTime = currTime
cv2.putText(output_image, f'FPS: {int(fps)}', (20, 70), cv2.FONT_HERSHEY_PLAIN, 3, (0, 196, 255), 2)
cv2.imshow('DIY Zoom Virtual Background', output_image)
if cv2.waitKey(5) & 0xFF == 27:
break
cap.release()
#Watch Tutorial at www.augmentedstartups.info/YouTube
