PiCam: Difference between revisions

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LINKS
==connecting the camera ==


* https://jawwig.wordpress.com/2013/11/19/setting-up-raspberry-pi-security-cam-on-model-a-or-b-with-minimal-armhf-image/
gently lift the black clip by pushing upward. insert the ribbon cable of the camera firmly down. the blue side goes towards the headphone jack! push the clip down again.
* http://raspberrypi.stackexchange.com/questions/10357/enable-camera-without-raspi-config


<pre language="bash">
See: https://www.raspberrypi.org/learning/getting-started-with-picamera/images/connect-camera.jpg
#!/bin/bash


set_config_var() {
== setup ==
  lua - "$1" "$2" "$3" <<EOF > "$3.bak"
local key=assert(arg[1])
local value=assert(arg[2])
local fn=assert(arg[3])
local file=assert(io.open(fn))
local made_change=false
for line in file:lines() do
  if line:match("^#?%s*"..key.."=.*$") then
    line=key.."="..value
    made_change=true
  end
  print(line)
end


if not made_change then
* Add the following to your /boot/config.txt
  print(key.."="..value)
start_x=1
end
EOF
mv "$3.bak" "$3"
}


[ -e /boot/config.txt ] || touch /boot/config.txt
== test the camera ==


set_config_var start_x 1 /boot/config.txt
  raspistill -o test.jpg
set_config_var gpu_mem 128 /boot/config.txt
 
sed /boot/config.txt -i -e "s/^startx/#startx/"
== connecting via python ==
sed /boot/config.txt -i -e "s/^fixup_file/#fixup_file/"
 
</pre>
See [https://www.raspberrypi.org/learning/getting-started-with-picamera/ this tutorial on raspberrypi.com]. The [https://www.raspberrypi.org/learning/infrared-bird-box/worksheet/ bird box] tutorial is also quite interesting relating to how the camera responds to infrared, and the fact that the "fixed focus" camera can be adapted to manually focus at various lengths.
 
<source lang="python">
from picamera import PiCamera
from time import sleep
 
camera = PiCamera()
camera.rotation=270
camera.start_preview()
sleep(10)
camera.stop_preview()
</source>
 
== using python + opencv ==
 
  apt install python-opencv python-picamera
 
This [http://www.pyimagesearch.com/2015/03/30/accessing-the-raspberry-pi-camera-with-opencv-and-python/ tutorial on pyimagesearch.com] is very useful.
Also the official [https://picamera.readthedocs.io/ picamera docs] include a [https://picamera.readthedocs.io/en/release-1.13/recipes2.html#capturing-to-an-opencv-object recipe for capturing to an opencv array].
 
Adapting the opt_flow.py opencv sample to do motion detection on the pi.
 
<source lang="python">
from picamera.array import PiRGBArray
from picamera import PiCamera
import time
import cv2
import numpy as np
 
# initialize the camera and grab a reference to the raw camera capture
camera = PiCamera()
# framesize = (640, 480)
framesize = (160, 120)
 
camera.resolution = framesize
camera.framerate = 32
rawCapture = PiRGBArray(camera, size=framesize)
# allow the camera to warmup
time.sleep(0.25)
 
prevgray = None
for frame in camera.capture_continuous(rawCapture, format="bgr", use_video_port=True):
    img = frame.array
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    if prevgray != None:
        flow = cv2.calcOpticalFlowFarneback(prevgray, gray, 0.5, 3, 15, 3, 5, 1.2, 0)
        fx = flow[:,:,0]
        fy = flow[:,:,1]
        mag = np.sqrt(fx*fx+fy+fy)
        mag = np.nan_to_num(mag)
        print mag.max()
        # print mag[0][0], mag[10][10]
    prevgray = gray
    # clear the stream in preparation for the next frame
    rawCapture.truncate(0)
</source>
 
== Sending the data from python to puredata via OSC ==
Using [https://trac.v2.nl/wiki/pyOSC Mr. Stock's classic OSC.py] module. You can simply download it and place in the same folder as your python script (no need to pip if you don't wanna).
 
( This code is for opencv's camera interface, TODO: adjust for picamera )
 
<source lang="python">
#!/usr/bin/env python
 
from __future__ import print_function
import numpy as np
import cv2, sys
from argparse import ArgumentParser
 
ap = ArgumentParser("use opencv to do optical flow on the camera input")
ap.add_argument("--show", default=False, action="store_true", help="show it")
ap.add_argument("--print", default=False, action="store_true", help="print values to stdout")
ap.add_argument("--video", default=0, help="video source")
ap.add_argument("--width", default=640, type=int, help="video width")
ap.add_argument("--height", default=480, type=int, help="video height")
ap.add_argument("--sendosc", default=False, action="store_true", help="send OSC messages")
ap.add_argument("--oschost", default="localhost", help="default: localhost")
ap.add_argument("--oscport", default=8001, help="default: 8001")
 
args = ap.parse_args()
 
if args.sendosc:
    import OSC
 
    client = OSC.OSCClient()
    client.connect((args.oschost, args.oscport))
    print ("OSC: Connected", file=sys.stderr)
 
cam = cv2.VideoCapture(args.video)
cam.set(cv2.cv.CV_CAP_PROP_FRAME_WIDTH, args.width)
cam.set(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT, args.height)
prevgray = None
 
def draw_flow(img, flow, step=16):
    h, w = img.shape[:2]
    y, x = np.mgrid[step/2:h:step, step/2:w:step].reshape(2,-1)
    fx, fy = flow[y,x].T
    lines = np.vstack([x, y, x+fx, y+fy]).T.reshape(-1, 2, 2)
    lines = np.int32(lines + 0.5)
    vis = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
    cv2.polylines(vis, lines, 0, (0, 255, 0))
    for (x1, y1), (x2, y2) in lines:
        cv2.circle(vis, (x1, y1), 1, (0, 255, 0), -1)
    return vis
 
while True:
    ret, img = cam.read()
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    if prevgray != None:
        flow = cv2.calcOpticalFlowFarneback(prevgray, gray, 0.5, 3, 15, 3, 5, 1.2, 0)
        fx = flow[:,:,0]
        fy = flow[:,:,1]
        mag = np.sqrt(fx*fx+fy+fy)
        mag = np.nan_to_num(mag)
 
        maxv = int(mag.max())
        total = int(mag.sum())
        if args.print:
            print (maxv, total)
 
        if args.sendosc:
            msg = OSC.OSCMessage("/optflow")
            msg.extend([maxv, total])
            client.send(msg)
 
        if args.show:
            cv2.imshow('flow', draw_flow(gray, flow))
            ch = 0xFF & cv2.waitKey(5)
            if ch == 27:
                break
 
    prevgray = gray
 
cv2.destroyAllWindows()
</source>
 
== UNCLASSIFIED NOTES ==
 
remember to put on udp on your pdsend (otherwise it's trying tcp and says connection refused ... annoying)
 
  pdsend 8001 localhost udp
 
[[Category: Raspberry Pi]] [[Category:Cookbook]]

Latest revision as of 17:55, 8 April 2017

connecting the camera

gently lift the black clip by pushing upward. insert the ribbon cable of the camera firmly down. the blue side goes towards the headphone jack! push the clip down again.

See: connect-camera.jpg

setup

  • Add the following to your /boot/config.txt
start_x=1

test the camera

 raspistill -o test.jpg

connecting via python

See this tutorial on raspberrypi.com. The bird box tutorial is also quite interesting relating to how the camera responds to infrared, and the fact that the "fixed focus" camera can be adapted to manually focus at various lengths.

from picamera import PiCamera
from time import sleep

camera = PiCamera()
camera.rotation=270
camera.start_preview()
sleep(10)
camera.stop_preview()

using python + opencv

 apt install python-opencv python-picamera

This tutorial on pyimagesearch.com is very useful. Also the official picamera docs include a recipe for capturing to an opencv array.

Adapting the opt_flow.py opencv sample to do motion detection on the pi.

from picamera.array import PiRGBArray
from picamera import PiCamera
import time
import cv2
import numpy as np

# initialize the camera and grab a reference to the raw camera capture
camera = PiCamera()
# framesize = (640, 480)
framesize = (160, 120)

camera.resolution = framesize
camera.framerate = 32
rawCapture = PiRGBArray(camera, size=framesize)
 
# allow the camera to warmup
time.sleep(0.25)

prevgray = None
for frame in camera.capture_continuous(rawCapture, format="bgr", use_video_port=True):
    img = frame.array
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    if prevgray != None:
        flow = cv2.calcOpticalFlowFarneback(prevgray, gray, 0.5, 3, 15, 3, 5, 1.2, 0)
        fx = flow[:,:,0]
        fy = flow[:,:,1]
        mag = np.sqrt(fx*fx+fy+fy)
        mag = np.nan_to_num(mag)
        print mag.max()
        # print mag[0][0], mag[10][10]
    prevgray = gray
 
    # clear the stream in preparation for the next frame
    rawCapture.truncate(0)

Sending the data from python to puredata via OSC

Using Mr. Stock's classic OSC.py module. You can simply download it and place in the same folder as your python script (no need to pip if you don't wanna).

( This code is for opencv's camera interface, TODO: adjust for picamera )

#!/usr/bin/env python

from __future__ import print_function
import numpy as np
import cv2, sys
from argparse import ArgumentParser

ap = ArgumentParser("use opencv to do optical flow on the camera input")
ap.add_argument("--show", default=False, action="store_true", help="show it")
ap.add_argument("--print", default=False, action="store_true", help="print values to stdout")
ap.add_argument("--video", default=0, help="video source")
ap.add_argument("--width", default=640, type=int, help="video width")
ap.add_argument("--height", default=480, type=int, help="video height")
ap.add_argument("--sendosc", default=False, action="store_true", help="send OSC messages")
ap.add_argument("--oschost", default="localhost", help="default: localhost")
ap.add_argument("--oscport", default=8001, help="default: 8001")

args = ap.parse_args()

if args.sendosc:
    import OSC

    client = OSC.OSCClient()
    client.connect((args.oschost, args.oscport))
    print ("OSC: Connected", file=sys.stderr)

cam = cv2.VideoCapture(args.video)
cam.set(cv2.cv.CV_CAP_PROP_FRAME_WIDTH, args.width)
cam.set(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT, args.height)
prevgray = None

def draw_flow(img, flow, step=16):
    h, w = img.shape[:2]
    y, x = np.mgrid[step/2:h:step, step/2:w:step].reshape(2,-1)
    fx, fy = flow[y,x].T
    lines = np.vstack([x, y, x+fx, y+fy]).T.reshape(-1, 2, 2)
    lines = np.int32(lines + 0.5)
    vis = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
    cv2.polylines(vis, lines, 0, (0, 255, 0))
    for (x1, y1), (x2, y2) in lines:
        cv2.circle(vis, (x1, y1), 1, (0, 255, 0), -1)
    return vis

while True:
    ret, img = cam.read()
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    if prevgray != None:
        flow = cv2.calcOpticalFlowFarneback(prevgray, gray, 0.5, 3, 15, 3, 5, 1.2, 0)
        fx = flow[:,:,0]
        fy = flow[:,:,1]
        mag = np.sqrt(fx*fx+fy+fy)
        mag = np.nan_to_num(mag)

        maxv = int(mag.max())
        total = int(mag.sum())
        if args.print:
            print (maxv, total)

        if args.sendosc:
            msg = OSC.OSCMessage("/optflow")
            msg.extend([maxv, total])
            client.send(msg)

        if args.show:
            cv2.imshow('flow', draw_flow(gray, flow))
            ch = 0xFF & cv2.waitKey(5)
            if ch == 27:
                break

    prevgray = gray

cv2.destroyAllWindows()

UNCLASSIFIED NOTES

remember to put on udp on your pdsend (otherwise it's trying tcp and says connection refused ... annoying)

 pdsend 8001 localhost udp