I got a Huion tablet for Santa Claus. I’m having a lot of fun animating the characters of a comic I used to draw back at university: cat art>/dev/null
I feel this could be the piece I was missing to keep crawling forward on my years-long intention of creating my own videogame. A graphic adventure based on the games I loved when I was a kid: Monkey Island, Indiana Jones, Kings Quest.. 😀
Take this
My wife’s PiboyDMG stopped working and wouldn’t boot. After some investigation it was due to the SD card being fried (no surprise there, SD cards are horribly unreliable) so I tried setting it up to boot from a 128GB mini usb drive. I followed the same steps I would have with an sd drive:
#include<stdio.h>
char * strcat (char *,char *);
void main(void){
char *s = "Pointer powers\n";
char *t = " activate\n";
char *z=strcat(s,t);
}
char * strcat(char *s, char *t){
//return the concatenation of s and t
char concatenation[255];
int i=0;
while (*s != '\0'){
concatenation[i]=*s;
*s++;
i++;
}
while (*t != '\0'){
concatenation[i]=*t;
t++;
i++;
}
concatenation[i]='\0';
return concatenation;
}To build this cluster you will need the following hardware parts:
sudo apt install tmuxvi multi-ssh.sh#!/bin/bash
ssh_list=( user1@server1 user2@server2 ... )
split_list=()
for ssh_entry in "${ssh_list[@]:1}"; do
split_list+=( split-pane ssh "$ssh_entry" ';' )
done
tmux new-session ssh "${ssh_list[0]}" ';' \
"${split_list[@]}" \
select-layout tiled ';' \
set-option -w synchronize-panessudo apt-get update && sudo apt-get upgrade
curl -fsSL https://get.docker.com -o get-docker.sh
sudo sh get-docker.sh
sudo usermod -aG docker pi
sudo reboot2. Install kubeadm, kubelet and kubectl on each raspberry pi (link)
sudo apt-get update
sudo apt-get install -y apt-transport-https ca-certificates curl
sudo curl -fsSLo /usr/share/keyrings/kubernetes-archive-keyring.gpg https://packages.cloud.google.com/apt/doc/apt-key.gpg
echo "deb [signed-by=/usr/share/keyrings/kubernetes-archive-keyring.gpg] https://apt.kubernetes.io/ kubernetes-xenial main" | sudo tee /etc/apt/sources.list.d/kubernetes.list
sudo apt-get update
sudo apt-get install -y kubelet kubeadm kubectl
sudo apt-mark hold kubelet kubeadm kubectl
3. disable swap on each raspberry pi (link)
sudo dphys-swapfile swapoff && \
sudo dphys-swapfile uninstall && \
sudo systemctl disable dphys-swapfile4. Add cgroup parameters to /boot/cmdline.txt on each raspberry pi (link)
sudo vi /boot/cmdline.txt
cgroup_enable=cpuset cgroup_enable=memory cgroup_memory=15. Configure docker to use systemd on each raspberry pi
sudo mkdir /etc/docker
cat <<EOF | sudo tee /etc/docker/daemon.json
{
"exec-opts": ["native.cgroupdriver=systemd"],
"log-driver": "json-file",
"log-opts": {
"max-size": "100m"
},
"storage-driver": "overlay2"
}
EOF
sudo systemctl enable docker
sudo systemctl daemon-reload
sudo systemctl restart docker
sudo kubeadm init --pod-network-cidr=10.244.0.0/16
rm -rf .kube/
mkdir -p $HOME/.kube
sudo cp -i /etc/kubernetes/admin.conf $HOME/.kube/config
sudo chown $(id -u):$(id -g) $HOME/.kube/config
vi $HOME/.bashrc
# Add the below line to the end of .bashrc
export KUBECONFIG=$HOME/.kube/config2. Set up the kubernetes network (I am using flannel) on the master node.
kubectl apply -f https://raw.githubusercontent.com/coreos/flannel/master/Documentation/kube-flannel.yml
cat > /run/flannel/subnet.env
FLANNEL_NETWORK=100.96.0.0/16
FLANNEL_SUBNET=100.96.1.1/24
FLANNEL_MTU=8973
FLANNEL_IPMASQ=true3. Get the tokens to connect the different nodes. Run this command on the master node and take note of the output.
kubeadm token create --print-join-commandIn each raspberry pi that you want to add as a node to the cluster run the following commands.
cat > /run/flannel/subnet.env
FLANNEL_NETWORK=100.96.0.0/16
FLANNEL_SUBNET=100.96.1.1/24
FLANNEL_MTU=8973
FLANNEL_IPMASQ=true2. Use the output you obtained previously from command “kubeadm token create –print-join-command” it will look something like this
sudo kubeadm join 192.168.1.102:6443 --token 5aotn8.ab493943zf9zf9nm \
--discovery-token-ca-cert-hash sha256:396a8a8b28b11c8caa8474384398493482034320947090766366bff9d1516699acde3. If all went well you should see all your nodes ready with command kubectl get nodes. You are now ready to create deployments, pods and services.
After you are done playing, or in case things stop working and you want to start from scratch you can use the below instructions to destroy your kubernetes infrastructure.
kubectl drain raspicluster1 --delete-emptydir-data --force --ignore-daemonsets
kubectl drain raspicluster2 --delete-emptydir-data --force --ignore-daemonsets
kubectl drain raspicluster3 --delete-emptydir-data --force --ignore-daemonsets
kubectl drain raspicluster4 --delete-emptydir-data --force --ignore-daemonsets
kubectl delete node raspicluster1
kubectl delete node raspicluster2
kubectl delete node raspicluster3
kubectl delete node raspicluster4
kubectl get nodes2. SSH to each machine and run the below code
sudo rm /etc/kubernetes/kubelet.conf /etc/kubernetes/pki/ca.crt /etc/kubernetes/bootstrap-kubelet.conf
sudo kubeadm resetToday I “did a box” for the birdfeederAI and set it up to work in the garden. Within a couple hours it had detected and tweeted it’s first real life bird video! 🙂
Found this beauty second hand (link). The kids and I had a lot of fun building and grabbing things with it. 🙂
Create a bird watching Artificial Intelligence that runs on a raspberry and tweets short videos every time it detects a bird. You can find mine at https://twitter.com/birdfeederAI
To build this bird watcher you will need the following hardware parts. Total cost EUR 255
mkdir -p /home/pi/dev/birdfeederAIcd /home/pi/dev/birdfeederAIpython3 -m venv ./venvsource ./venv/bin/activatewhich pythonwhich pipwhich pip3pip listpip install --upgrade pippip install opencv-python twython sudo apt install apt-filesudo apt-file updatefor i in find /home/pi/dev/birdfeederAI/venv/lib |grep so$|xargs ldd|grep "not found"|awk '{print $1;}'; do apt-file search $i|awk 'BEGIN{FS=":"};{print $1;}'; done|sort|uniq|xargs apt installcd /home/pi/dev/birdfeederAIgit clone https://github.com/chuanqi305/MobileNet-SSD.gitraspistill -o mypicture.jpgraspivid -t 5000 -o myvideo.h264
import cv2
cv2.namedWindow("TestCV2")
vc = cv2.VideoCapture(0)
if vc.isOpened():
rval,frame = vc.read()
else:
rval = False
while rval:
frame = cv2.flip(frame,-1)
cv2.imshow("TestCV2", frame)
rval, frame = vc.read()
key = cv2.waitKey(20)
if key ==27:
break
vc.release()
cv2.destroyWindow("TestCV2")
/home/pi/dev/birdfeederAI/auth.pycat>/home/pi/dev/birdfeederAI/auth.pyconsumer_key = 'puthereyourconsumerkey'consumer_secret = 'puthereyourconsumersecret'access_token = 'puthereyouraccesstoken'access_token_secret = 'puthereyouraccesstokensecret'Ctrl-Cgit clone https://github.com/Rogeman/birdfeederAI.git
import numpy as np
import cv2
import random
import os
import logging
from twython import Twython
from twython import TwythonError
from auth import (
consumer_key,
consumer_secret,
access_token,
access_token_secret
)
twitter = Twython(
consumer_key,
consumer_secret,
access_token,
access_token_secret
)
confidence_thr = 0.5
CLASSES = ["background", "aeroplane", "bicycle", "bird", "boat",
"bottle", "bus", "car", "cat", "chair", "cow", "diningtable",
"dog", "horse", "motorbike", "person", "pottedplant", "sheep",
"sofa", "train", "tvmonitor"]
COLORS = np.random.uniform(0, 255, size=(len(CLASSES), 3))
birdfeeder_dir=os.path.dirname(os.path.abspath(__file__))
logging.basicConfig(filename=birdfeeder_dir+'/log/birdfeederAI.log', level=logging.DEBUG, format='%(asctime)s %(message)s')
mobilenet_dir=birdfeeder_dir+'/MobileNet-SSD/'
net = cv2.dnn.readNetFromCaffe(mobilenet_dir+ 'deploy.prototxt' , mobilenet_dir+ 'mobilenet_iter_73000.caffemodel')
blob=None
def applySSD(image):
global blob
mybird = bool(False)
blob = cv2.dnn.blobFromImage(cv2.resize(image, (300, 300)), 0.007843, (300, 300), 127.5)
# pass the blob through the network and obtain the detections and
# predictions
net.setInput(blob)
detections = net.forward()
# loop over the detections
for i in np.arange(0, detections.shape[2]):
# extract the confidence (i.e., probability) associated with the
# prediction
confidence = detections[0, 0, i, 2]
if confidence > confidence_thr:
idx = int(detections[0,0,i,1])
if CLASSES[idx]=="bird":
mybird=bool(True)
return mybird
def birdRatio(videoName):
totalBirdFrames = 1
totalFrames = 1
vc2 = cv2.VideoCapture(videoName)
if vc2.isOpened():
rval2,frame2 = vc2.read()
else:
rval2 = False
while rval2:
birdinFrame = applySSD(frame2)
rval2, frame2 = vc2.read()
if (birdinFrame):
totalBirdFrames = totalBirdFrames + 1
totalFrames = totalFrames + 1
vc2.release()
return totalBirdFrames/totalFrames
videoLength=8*60*60*1000
randomsec=random.randint(0,videoLength)
#vc = cv2.VideoCapture(birdfeeder_dir+"/birds_video.mp4")
# If you want to record birds using your camera comment the above line and uncomment the below line. If you want to find birds in a video uncomment the line above and comment the line below 🙂
vc = cv2.VideoCapture(0)
vc.set(cv2.CAP_PROP_POS_MSEC, randomsec)
if vc.isOpened():
width = vc.get(cv2.CAP_PROP_FRAME_WIDTH)
height = vc.get(cv2.CAP_PROP_FRAME_HEIGHT)
fps = vc.get(cv2.CAP_PROP_FPS)
fcount = vc.get(cv2.CAP_PROP_FRAME_COUNT)
else:
logging.error('Can\'t open video')
exit()
recording= False
framerecorded = 0
framecounter = 0
birdinFrame=False
fourcc = cv2.VideoWriter_fourcc(*'h264')
#out = cv2.VideoWriter('output.mp4',fourcc,20.0,(640,480))
out = cv2.VideoWriter(birdfeeder_dir+'/output.mp4',fourcc,fps,(int(width),int(height)))
if vc.isOpened(): # try to get the first frame
rval, frame = vc.read()
(h, w) = frame.shape[0] , frame.shape[1]
else:
rval = False
logging.debug('Started main loop')
while rval:
#You enter this loop once per frame
rval, frame = vc.read()
#uncomment the below line if you need to flip the camera upside down.
frame = cv2.flip(frame,-1)
key = cv2.waitKey(20)
if key == 27: # exit on ESC
break
framecounter = framecounter + 1
if (framecounter > 60):
# Write frame to disk every 60 frames so we can see what the camera is seeing
framecounter = 0
cv2.imwrite(birdfeeder_dir+"/webserver/currentframe.jpg",frame)
if (birdinFrame==False):
#Check if this frame has a bird in it
birdinFrame= applySSD(frame)
if (birdinFrame== True and recording== False):
#You have detected the first bird in a frame, start recording
logging.info('Started recording video')
recording=True
if (recording == True):
#write the frame to file keep track of how many frames you have saved.
framerecorded = framerecorded + 1
out.write(frame)
if (framerecorded > 200):
#after 200 frames stop recording
logging.info('Checking recorded video')
recording = False
birdinFrame=False
framerecorded = 0
out.release()
filename = birdfeeder_dir+"/output.mp4"
birdsinvideo= birdRatio(filename)
logging.debug('percentage of bird in video: '+birdsinvideo)
if (birdsinvideo> 0.50):
# if the recorded video has more than 50% of frames with a bird in it then tweet it
logging.info('Tweeting bird video')
video = open(filename,'rb')
try:
response = twitter.upload_video(media=video, media_type='video/mp4', media_category='tweet_video', check_progress=True)
twitter.update_status(status='birdfeeder 0.5', media_ids=[response['media_id']])
except TwythonError as e:
logging.error('Twitter error:'+str(e))
birdsinvideo=0
video.close()
randomsec=random.randint(0,videoLength)
vc.set(cv2.CAP_PROP_POS_MSEC, randomsec)
os.remove(birdfeeder_dir+'/output.mp4')
out = cv2.VideoWriter(birdfeeder_dir+'/output.mp4',fourcc,fps,(int(width),int(height)))
vc.release()
sudo apt-get update && sudo apt-get upgrade
curl -fsSL https://get.docker.com -o get-docker.sh
sudo sh get-docker.sh
sudo usermod -aG docker pi
sudo reboot
docker run -it --rm -d -p 8080:80 --name web -v /home/pi/dev/birdfeederAI/webserver/:/usr/share/nginx/html nginx
cat > /home/pi/dev/birdfeederAI/webserver/index.html
<html>
<head>
<title>Birdfeeder</title>
<meta http-equiv="refresh" content="2" />
</head>
<body>
<img src=./currentframe.jpg>
</body>
</html>
Ctrl+C
You can now open a web browser to your raspberry pi’s ip address port 8080 and see what your camera is seeing
We add birdfeeder to systemd so it starts on boot.
vim /home/pi/dev/birdfeederAI/bin/birdfeeder.shchmod +x /home/pi/dev/birdfeederAI/bin/birdfeeder.sh
#!/bin/bash
docker run -it --rm -d -p 8080:80 --name web -v /home/pi/dev/birdfeederAI/webserver/:/usr/share/nginx/html nginx
source /home/pi/dev/birdfeederAI/venv/bin/activate
while [ 1 -eq 1 ]
do
nice python /home/pi/dev/birdfeederAI/birdfeeder.py
done
sudo vim /lib/systemd/system/birdfeeder.service
[Unit]
Description=birdfeeder service
After=multi-user.target
[Service]
Type=idle
ExecStart=/home/pi/dev/birdfeederAI/bin/birdfeeder.sh
[Install]
WantedBy=multi-user.target
sudo chmod 644 /lib/systemd/system/birdfeeder.servicesudo systemctl daemon-reloadsudo systemctl enable birdfeeder.servicesudo rebootI enjoy tinkering around with robots and electronics. Bridging the invisible world of software with the real world of physical things.
I discovered I could glue a breadboard to the side of the base of this robotic arm, and that I could hold the arduino board to the base with elastic bands. and that the adafruit motor board left 5 analog pins free to use, and that I could put a switch, a potentiometer and an hbridge in the breadboard with these five free pins. And that I could substitute the broken led with a new one with my soldering iron 😀
It is now all ready and working. Every time I hold down the switch button it activates one of the five motors iteratively. With the potentiometer I can have the motor run in one direction or the other. And the LED at the hand of the robot arm shines while the button is pressed.
The only problem pending is I need to change all the worn out gears from the motors as they are eroded from previous experiments (the problem with dc motors as opposed to servo motors is that you can’t know where they are, so I overextended them eroding the gears)
My Map of things 