nanocamera 0.1.5

A Python camera interface for the Jetson Nano

NanoCamera

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:

• Works with CSI Cameras (Tested and Works)
• Works with various USB cameras (Tested with Logitech USB camera)
• Works with RTSP streaming camera and video with hardware acceleration (only supports H.264 video codec)
• Works with IP Cameras(JPEG codec) or any MJPEG streaming source (Currently, supports CPU acceleration. TODO: Hardware acceleration)

If you like NanoCamera library - give it a star, or fork it and contribute!. Updates are always welcomed.

Features

• It is OpenCV ready. The image file can be called directly with OpenCV imshow
• Image file is a NumPy RGB array.
• Support different Camera Flip Mode (Counterclockwise, Rotate 180 degrees, Clockwise - 90 degrees, Horizontal Flip, Vertical Flip)
• Can be used with multiple cameras.
• Support Frame rate enforcement. *Only available for USB, RTSP, and IP/MJPEG cameras.
• Frame rate enforcement ensures the cameras work at the given frame rate using GStreamer video rate plugin
• It is based on Accelerated GStreamer Plugins
• Should work with other Jetson boards like Jetson TX1, TX2 and others (Not tested)
• Support both Hardware and CPU acceleration.
• Easily read images as numpy arrays with image = camera.read()
• Supports threaded read - available to all camera types. To enable a fast threaded read, you will enable the enforce_fps: enforce_fps = True
• Check the status of the camera after initialization with isReady() function. Returns True if ready and False if otherwise.
• Provide debugging support. Added error codes and an optional exception handling. See example in Debugging. Now you can restart the camera if something goes wrong or send an admin notice if your camera goes down.
• Support multiple CSI cameras using the device_id parameter. See examples.

Requirements

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 

Install

Installation is simple. Can be installed in two ways with Pip or Manually.

Pip Installation

pip3 install nanocamera 

Manual Installation

git clone https://github.com/thehapyone/NanoCamera
cd NanoCamera
sudo python3 setup.py install

Usage & Example

Using NanoCamera is super easy. Below we show some usage examples. You can find more in the examples.

Working with CSI Camera

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

Multiple CSI Camera support.

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)

Working with USB Camera

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

Working with RTSP streaming camera or streaming video

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)

Working with IP or any MJPEG streaming camera or video

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)

Frame Rate Enforcement

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)

Reading Camera

Call read() to read the latest image as a numpy.ndarray. The color format is BGR.

frame = camera.read()

Camera isReady?

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

Debugging

The library has some debugging builtin for managing expected, unexpected errors, and exceptions that might occur during the camera acquisition or initialization.

• Using the 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.
• Using the hasError() to read the current error state of the camera with or without debug enabled.

Errors and Exceptions Handling

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.

Thanks! & Give it a Star

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.

License

This project is released under the MIT License.

See also

• Platooning Robot - Resources for building collaborative robots