This weekend I took a bit of time to read up on OpenCV (Open Source Computer Vision Library) , I wanted to capture images of Magic the Gathering cards, then identify them using a Python library called ImageHash . Below is a demonstration of what I was able to accomplish in about 2 days of research and hacking: I’ll try and break down the steps and image manipulation functions I used to achieve this.
Remote Controlled Car using Raspberry Pi and Webcam
Setup First thing I tackled was setting up the L293D H-Bridge on the Bread Board. I found myself referencing the following Diagram a couple times. Step one is connecting your chip down the center of your board: From here I connected the 3 power pins to my board’s power rail using a few Jumpers : A few more Jumpers connect each side of the chip to ground: Finally I use a couple Wires to connect both sides of my power and ground rails:
Python says, Simon's hipster brother
Many of you may remember playing with a Simon Electronic Memory Game when you were younger, you know something that looks like this: At it’s core the game is rather simple, the device lights up random colors, and you need to repeat the pattern. Of course it gets harder the longer you play. I thought it would be fun to build a Simon game using Raspberry Pi and a few electronic components:
Arduino values to Python over Serial
I’ve done a little bit of reading on the ReadAnalogVoltage of Arduino’s home page, and they give a straight forward way to read voltage from an analog pin. I wanted to take this one step further and send the value over serial, then read it in Python using pySerial . My setup is very straight forward, I have a Arduino UNO , a bread board, and a battery pack holding 4x AA batteries: To start out I want to merely print the voltage value in Arduino Studio to the serial console, my code looks something like this:
Python and sentiment analysis
While looking for datasets to throw at sklearn , I came across UCI Sentiment Labelled Sentences Data Set . UCI is providing us with positive / negative tagging on real world data, the data comes from three sources ( Amazon , Yelp , and IMDB ). The only problem is the format is a little strange.. We have a .txt file for each source, this is a raw unstructured formatting, plus not every line is tagged with sentiment.
Test your Machine Learning
In my previous post " Python Machine Learning with Presidential Tweets “, I started messing around with sklearn and text classification. Since then I’ve discovered a great tutorial from SciPy 2015 . This video starts out slow enough for novices, and a reoccurring theme is testing your datasets. After watching a good chunk of this video, I decided to go back to my code and implement a testing phase. Basically I’ll split my data into two pieces, a training set , and a testing set .
Python Machine Learning with Presidential Tweets
I’ve been spending a little bit of time researching Machine Learning , and was very happy to come across a Python library called sklearn . While digging around Google, I came across a fantastic write up on Document Classification by Zac Steward . This article went pretty deep into writing a spam filter using machine learning, and sklearn. After reading the article I wanted to try some of the concepts, but had no interest in writing a spam filter.
SensorTag data merged with Open Weather Maps
About a week ago I worked on SensorTag metrics with Grafana . This week had some interesting weather today here in Austin, and I wanted to see to visualize it as well. Luckily Open Weather Maps offers a free API for gather near real-time weather data based on city code. def __get_open_weather_data(): url_path = 'http://api.openweathermap.org/data/2.5/weather' api_key = '??????????' url = '%s?zip=73301&APPID=%s' res = requests.get(url % (url_path, api_key)) if res: if res.
Arduino meet Raspberry Pi
While at the electronics store the other day, I noticed they had motion detectors on sale for only $4. I decided with my latest obsession of electronic tinkering, picking up a OSEEP Passive Infrared Sensor (PIR) Module might be fun. I guess I should have done a little more reading on the packaging; by the time I was home, I noticed this sensor reported in analog , not digital. This was an issue as the Raspberry Pi only reads digital input.
Raspberry Pi and Official NFL Score Board API
Now that I’ve got my hands on a Raspberry Pi 3 Model B Motherboard , I decided nows a good time to play around with the 16x2 LCD Module Controller HD44780 I had laying around (I’ve had this thing since December 2015). A live NFL (National Football League) score board seemed fitting as the season just started. I found a really good write up on raspberrypi-spy.co.uk about wiring up the controller and Pi, here is the diagram I used: