A simple to use camera interface for the Jetson Nano for working with USB, CSI, IP and also RTSP cameras or streaming video in Python 3.
It currently supports the following types of camera or streaming source:
If you like NanoCamera library - give it a star, or fork it and contribute!. Updates are always welcomed.
numpy arrays with image = camera.read()enforce_fps = TrueisReady() function. Returns True if ready and False if otherwise.device_id parameter. See examples.This library requires OpenCV to be installed to work. If you don't have OpenCV, you can install one with pip:
pip3 install opencv-python
Installation is simple. Can be installed in two ways with Pip or Manually.
pip3 install nanocamera
git clone https://github.com/thehapyone/NanoCamera
cd NanoCamera
sudo python3 setup.py install
Using NanoCamera is super easy. Below we show some usage examples. You can find more in the examples.
For CSI Cameras, the camera_type = 0.
Find here for full CSI camera example
Python Example - Create a CSI camera using default FPS=30, default image size: 640 by 480 and with no rotation (flip=0)
import nanocamera as nano
# Create the Camera instance for 640 by 480
camera = nano.Camera()
Customizing the width and height
import nanocamera as nano
# Create the Camera instance for No rotation (flip=0) with size of 1280 by 800
camera = nano.Camera(flip=0, width=1280, height=800, fps=30)
if the image is inverted, set flip = 2
For Multiple CSI Cameras, set the device_id to the ID of the camera.
import nanocamera as nano
# Create the Camera instance for No rotation (flip=0) with size of 1280 by 800
# Connect to CSI camera with ID 0 (Default)
camera_1 = nano.Camera(device_id=0, flip=0, width=1280, height=800, fps=30)
# Connect to another CSI camera on the board with ID 1
camera_2 = nano.Camera(device_id=1, flip=0, width=1280, height=800, fps=30)
For USB Cameras, set the camera_type = 1, and set the device_id as well.
Find here for full USB camera example
Python Example -
Create USB camera connected to /dev/video1
import nanocamera as nano
# Create the Camera instance for No rotation (flip=0) with size of 640 by 480
camera = nano.Camera(camera_type=1, device_id=1, width=640, height=480, fps=30)
You can see connected USB cameras by running :
ls /dev/video*
# for USB camera /dev/video2, the device_id will be 2
For RTSP source, set the camera_type = 2, and set the source as well.
Find here for full RTSP camera example
Python Example -
Create RTSP receiving camera client. RTSP location example: rtsp://192.168.1.26:8554/stream
# a location for the rtsp stream. Stream location without "rtsp://"
rtsp_location = "192.168.1.26:8554/stream"
# Create the Camera instance
camera = nano.Camera(camera_type=2, source=rtsp_location, width=640, height=480, fps=30)
For IP/MJPEG Cameras, set the camera_type = 3, and set the streaming source as well.
Find here for full MJPEG camera example
Python Example -
Create an IP camera client connected to a camera streaming to http://192.168.1.26:80/stream
# a location for the camera stream. Stream location without "http://"
camera_stream = "192.168.1.26:80/stream"
# Create the Camera instance
camera = nano.Camera(camera_type=3, source=camera_stream, width=640, height=480, fps=30)
Enable frame rate enforcement i.e force the camera to work at the given frame rate
import nanocamera as nano
# enforce the capture frame rate with the enforce_fps=True
camera = nano.Camera(camera_type=1, device_id=1, width=640, height=480, fps=30, enforce_fps=True)
Call read() to read the latest image as a numpy.ndarray. The color format is BGR.
frame = camera.read()
You can check if the camera is ready for streaming using isReady()
status = camera.isReady()
A Simple program to read from the CSI camera and display with OpenCV
import cv2
#from nanocamera.NanoCam import Camera
import nanocamera as nano
if __name__ == '__main__':
# Create the Camera instance
camera = nano.Camera(flip=0, width=640, height=480, fps=30)
print('CSI Camera ready? - ', camera.isReady())
while camera.isReady():
try:
# read the camera image
frame = camera.read()
# display the frame
cv2.imshow("Video Frame", frame)
if cv2.waitKey(25) & 0xFF == ord('q'):
break
except KeyboardInterrupt:
break
# close the camera instance
camera.release()
# remove camera object
del camera
A Simple program to read from the IP/MJPEG camera and display with OpenCV
import cv2
# from nanocamera.NanoCam import Camera
import nanocamera as nano
if __name__ == '__main__':
# requires the Camera streaming url. Something like this: http://localhost:80/stream
# For IP/MJPEG camera, the camera_type=3.
# This works with only camera steaming MJPEG format and not H.264 codec for now
# a location for the camera stream
camera_stream = "192.168.1.26:80"
# Create the Camera instance
camera = nano.Camera(camera_type=3, source=camera_stream, width=640, height=480, fps=30)
print('MJPEG/IP Camera is now ready')
while camera.isReady():
try:
# read the camera image
frame = camera.read()
# display the frame
cv2.imshow("Video Frame", frame)
if cv2.waitKey(25) & 0xFF == ord('q'):
break
except KeyboardInterrupt:
break
# close the camera instance
camera.release()
# remove camera object
del camera
The library has some debugging builtin for managing expected, unexpected errors, and exceptions that might occur during the camera acquisition or initialization.
debug parameter to enable raising of exceptions when an error occurred. This is disabled in the default mode so you won't get any error if something goes wrong.hasError() to read the current error state of the camera with or without debug enabled.Calling camere.hasError() at any point in time returns a list of error codes and a boolean value:
# status holds a list.
status = camera.hasError()
print (status)
>> ([0, 3], True)
print ("Error codes list : ", status[0])
>> Error codes list : [0, 3]
print ("Error State : ", status[1])
>> Error State: True
Error codes are
'''
-1 = Unknown error
0 = No error
1 = Error: Could not initialize camera.
2 = Thread Error: Could not read image from camera
3 = Error: Could not read image from camera
4 = Error: Could not release camera
'''
For example:
error_status = camera.hasError()
if error_status[1] == False: # means no error detected so far
# read the camera image
frame = camera.read()
# print the current error codes
print (error_status[0])
# display the frame
cv2.imshow("Video Frame", frame)
if cv2.waitKey(25) & 0xFF == ord('q'):
break
else:
# an error has occured.
print ("An error with the camera. Error code : ", error_status[0])
Enabling the debug = True parameter allows raising an exception to the main program. This might be useful for parallel computing if you running multiple threads. Without the debug enabled, your program will continue as normal, and worse if you're enabled the frame rate enforcement which uses the thread read function, you will keep getting image data but those images are old/static images.
See an example using the debug parameter and handling exceptions at different levels. Find here for full debugging example
if __name__ == '__main__':
# with debug=True. An Exception will be raised if something goes wrong.
# Create the Camera instance
try:
# Create the Camera instance
print("camera stream")
camera = nano.Camera(camera_type=1, device_id=0, fps=30, debug=True)
except Exception as e:
# handle the exception from opening camera session
else:
print('USB Camera ready? - ', camera.isReady())
while True:
try:
# read the camera image
frame = camera.read()
# do something with frame like: send_to_cloud(frame)
except KeyboardInterrupt:
break
except Exception as e:
# handle the exception from reading
break
print("done here")
try:
# close the camera instance
camera.release()
except Exception as e:
# handle the exception from releasing the camera
If an error occurred, a Runtime Error will be raised catching the following exceptions:
The except cause might catch the following exceptions:
>> Exception Type - Error: Could not initialize USB Camera
>> Exception Type - An error as occurred. Error Value: [0, 3]
>> Exception Type - Unknown Error has occurred
>> Exception Type - Error: Could not release camera
Without debug and even if there is error the program runs as nothing happened. The error can still be detected with the hasError() function.
Thank you for downloading and enjoying the NanoCamera library. I hope you find it useful. Heck, I wrote it for you- yeah, that's right- you.
Contributing to this software is warmly welcomed. Don't forget to give it a star.
This project is released under the MIT License.
FAQs
A Python camera interface for the Jetson Nano
We found that nanocamera demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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