Hi, @DaneLLL
Your solution was very helpful; thank you! I confirmed that the GStreamer was receiving the camera frames at an average of about 60.3fps when set to 60fps.
I installed the RT kernel as per the guide, but I didn’t notice a significant improvement in real-time performance compared to the regular kernel. I’m not sure in which areas the RT kernel is supposed to be more effective.
Additionally, I have one more question:
# MIT License
# Copyright (c) 2019-2022 JetsonHacks
# Using a CSI camera (such as the Raspberry Pi Version 2) connected to a
# NVIDIA Jetson Nano Developer Kit using OpenCV
# Drivers for the camera and OpenCV are included in the base image
import cv2
import time
"""
gstreamer_pipeline returns a GStreamer pipeline for capturing from the CSI camera
Flip the image by setting the flip_method (most common values: 0 and 2)
display_width and display_height determine the size of each camera pane in the window on the screen
Default 1920x1080 displayd in a 1/4 size window
"""
def gstreamer_pipeline(
sensor_id=0,
capture_width=1280,
capture_height=720,
display_width=640,
display_height=360,
framerate=60,
flip_method=2,
):
return (
"nvarguscamerasrc sensor-id=%d ! "
"video/x-raw(memory:NVMM), width=(int)%d, height=(int)%d, framerate=(fraction)%d/1 ! "
"nvvidconv flip-method=%d ! "
"video/x-raw, width=(int)%d, height=(int)%d, format=(string)BGRx ! "
"videoconvert ! "
"video/x-raw, format=(string)BGR ! appsink"
% (
sensor_id,
capture_width,
capture_height,
framerate,
flip_method,
display_width,
display_height,
)
)
def show_camera():
window_title = "CSI Camera"
prev_time = 0
# To flip the image, modify the flip_method parameter (0 and 2 are the most common)
print(gstreamer_pipeline(flip_method=2))
video_capture = cv2.VideoCapture(gstreamer_pipeline(flip_method=0), cv2.CAP_GSTREAMER)
if video_capture.isOpened():
try:
window_handle = cv2.namedWindow(window_title, cv2.WINDOW_AUTOSIZE)
while True:
ret_val, frame = video_capture.read()
current_time = time.perf_counter()
sec = current_time - prev_time
prev_time = current_time
print(1/sec)
if cv2.getWindowProperty(window_title, cv2.WND_PROP_AUTOSIZE) >= 0:
cv2.imshow(window_title, frame)
else:
break
keyCode = cv2.waitKey(16) & 0xFF
# Stop the program on the ESC key or 'q'
if keyCode == 27 or keyCode == ord('q'):
break
finally:
video_capture.release()
cv2.destroyAllWindows()
else:
print("Error: Unable to open camera")
if __name__ == "__main__":
show_camera()
I’m testing this code in Python. cv2.imshow() is affected by waitKey and updates the display every 16ms, right? I used the time.perf_counter() function to measure the time for the cv2.imshow part. When I converted this time to fps, I got an average of about 55fps. Why do you think this is happening?
I need to accurately receive real-time video data at 60fps. Can you help me with this?
