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Hello, I love pixellib,
I'm currently working on project that requires the background to be blacked out and the person to be in normal color,
my problem is that right now no matter what I try, there's always the segmentation overlay on top of my selection,
I have tried a few solution, but none work as well and as fast as the one below.
can anyone tell me how to make my overlay invisible
'''''import pixellib
from pixellib.torchbackend.instance import instanceSegmentation
import cv2
import numpy as np
while capture.isOpened():
ret, frame = capture.read()
if not ret:
break
# Perform the segmentation
results = segment_video.segmentFrame(frame, show_bboxes=False, segment_target_classes=target_classes)
# The segmentation result is the first element in the results tuple
result = results[0]
# Extract the mask for the person class (assuming person class ID is 0)
masks = result['masks']
if masks.shape[2] > 0:
person_mask = np.sum(masks, axis=2).astype(bool)
# Use the original frame where the mask is True, and set the background to black
frame = np.where(person_mask[:,:,None], frame, 1)
# Display the resulting frame
cv2.imshow('frame', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
capture.release()
cv2.destroyAllWindows()'''''
Thank you
The text was updated successfully, but these errors were encountered:
Hello, I love pixellib,
I'm currently working on project that requires the background to be blacked out and the person to be in normal color,
my problem is that right now no matter what I try, there's always the segmentation overlay on top of my selection,
I have tried a few solution, but none work as well and as fast as the one below.
can anyone tell me how to make my overlay invisible
'''''import pixellib
from pixellib.torchbackend.instance import instanceSegmentation
import cv2
import numpy as np
capture = cv2.VideoCapture(0)
segment_video = instanceSegmentation()
segment_video.load_model("pointrend_resnet50.pkl", detection_speed="fast")
target_classes = segment_video.select_target_classes(person=True)
while capture.isOpened():
ret, frame = capture.read()
if not ret:
break
capture.release()
cv2.destroyAllWindows()'''''
Thank you
The text was updated successfully, but these errors were encountered: