77c2354c00
added vision daemon which runs in the background added more documentation to vision module now including opencv dependencies in complib package
102 lines
2.7 KiB
ReStructuredText
102 lines
2.7 KiB
ReStructuredText
.. _lib_vision:
|
|
|
|
Vision
|
|
=====
|
|
|
|
This module provides an interface for grabbing an rtmp stream and using the images to do some processing in opencv.
|
|
|
|
How do I use this module?
|
|
|
|
1. Get frames from the raspberry pi camera
|
|
2. -- here comes your own processing --
|
|
3. Publish the processed frames on an http server
|
|
4. You can view the http stream of your processed images in a web browser
|
|
|
|
Opencv Stream
|
|
*************
|
|
|
|
Because of the rtmp stream needing to buffer some frames and waiting for P-Frames, importing this module might take up
|
|
to 5 Seconds.
|
|
|
|
.. autoclass:: compLib.Vision.__Streaming
|
|
:members:
|
|
|
|
Examples
|
|
*********
|
|
|
|
Using the Vision Module
|
|
---------------------
|
|
|
|
.. code-block:: python
|
|
|
|
import cv2
|
|
from compLib import Vision
|
|
|
|
# get newest opencv frame from camera
|
|
frame = Vision.Streaming.get_frame()
|
|
|
|
# do some processing with the frame.....
|
|
|
|
# publish frame to streaming server
|
|
Vision.Streaming.publish_frame(frame)
|
|
|
|
Connect the raspberry pi to your internet and view the stream at: "http://your_raspi_ip:9898/". This should display
|
|
your raspberry pi camera. Note: the stream will lag a little bit BUT the processing of the image will be done in
|
|
realtime.
|
|
|
|
The output on the website should show whatever your raspberry pi cam records:
|
|
|
|
.. image:: images/opencv_http_stream.png
|
|
:width: 680
|
|
:alt: Processed frames from opencv
|
|
|
|
|
|
Chessboard Detection
|
|
------------------------------------------
|
|
|
|
In this example we process the captured stream of images and want to detect chessboards. Run this example and
|
|
point your raspberry pi camera to a chessboard and it should be detected.
|
|
|
|
For testing you can point it at this image:
|
|
|
|
.. image:: images/chessboard.jpg
|
|
:width: 680
|
|
:alt: Chessboard for opencv processing
|
|
|
|
.. code-block:: python
|
|
|
|
import cv2
|
|
from compLib import Vision
|
|
|
|
# get newest opencv frame from camera
|
|
frame = Vision.Streaming.get_frame()
|
|
|
|
criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
|
|
|
|
# convert image to grayscale image
|
|
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
|
|
|
|
# find the chessboard corners
|
|
ret, corners = cv2.findChessboardCorners(gray, (6, 9), None)
|
|
|
|
# draw detected chessboard position onto the image
|
|
cv2.drawChessboardCorners(frame, (6, 9), corners, ret)
|
|
|
|
# publish frame to streaming server
|
|
Vision.Streaming.publish_frame(frame)
|
|
|
|
Connect the raspberry pi to your internet and view the stream at: "http://your_raspi_ip:9898/".
|
|
|
|
The output image should look like this:
|
|
|
|
.. image:: images/chessboard_detected.jpg
|
|
:width: 680
|
|
:alt: Processed frames from opencv
|
|
|
|
Here is a screenshot of the stream website while viewing the chessboard in this documentation.
|
|
|
|
.. image:: images/opencv_processed.png
|
|
:width: 680
|
|
:alt: Processed frames from opencv
|
|
|
|
|