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base_bg_removal.py
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base_bg_removal.py
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import numpy as np
from ultralytics import YOLO
import cv2
def bg_removal(input_image):
"""
Performs background removal on the input image.
Parameters:
input_image (ndarray): The input image represented as a NumPy array.
Returns:
tuple: A tuple containing the modified input image with background removed and the output mask.
"""
results = bg_model.predict(input_image.copy())[0]
output_mask = np.zeros_like(input_image, dtype='float32')
if results.masks:
for i in range(len(results.boxes.boxes)):
if int(results.boxes.boxes[i, -1].item()) == 0:
output_mask = results.masks.masks.detach().cpu()[i][..., None]
input_image = np.where(output_mask, input_image, 0)
return input_image, output_mask
def run_webcam(input_webcam=0) -> None:
"""
Runs the webcam application for image processing and visualization.
Press 'q' to quit
"""
cap = cv2.VideoCapture(input_webcam)
while True:
ret, frame = cap.read()
assert ret, 'webcam does not return image!!!'
frame, _ = bg_removal(frame)
cv2.imshow('WebCam', frame)
if cv2.waitKey(1) == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
if __name__ == "__main__":
# Load YOLOv8 model for segmentation and background removal
yolov8_model_type = 'm' # Choose between "n" for nano, "s" for small, "m" for medium, "l" for large and "x" for X-large
bg_model = YOLO(f"bg_models/yolov8{yolov8_model_type}-seg.pt")
# Webcam number based on total webcams connected to your computer
webcam_number = 0
run_webcam(webcam_number)
cv2.destroyAllWindows()