This project started with assembling the Google AIY Vision Kit, this was very enjoyable and gave me a good insight into what makes up the device.
This code is a fork of the Google example face_camera_detection.
Building on top of this example, I created a counter, which allowed me to keep track of how consistently happy or sad the face in the frame is.
if avg_joy_score(faces) > 0.8: if joy_counter < 0: joy_counter = 0 else: joy_counter += 1 if avg_joy_score(faces) < 0.1: if joy_counter > 0: joy_counter = 0 else: joy_counter -= 1 if joy_counter > 20: print("Happy") joy_counter = 0
The code for sending emails is nested under a conditional of
if joy_counter < -20 in a similar way to the Happy branch is defined above.
For sending emails, I first had to work with the Reddit API, this is fairly simple as adding
/random.json to the end of a subreddit will give you a response with a random post from that subreddit. So I just used
urllib to make a request in the following way
request_url = urllib.request.urlopen("https://www.reddit.com/r/dogpictures/random.json")
Then it comes to parsing the response, as the URL to the image is deep in the JSON response. The
json package works for this, with
result being set as a string of the URL
result = json.loads(request_url.read().decode())["data"]["children"]["data"]["url"]
Then it comes to working with SendGrid, this is very simple with the
sendgrid Python library
message = Mail( firstname.lastname@example.org', email@example.com', subject='Sending with Twilio SendGrid is Fun', html_content='<img src='+result+'>') try: sg = SendGridAPIClient(env.str('SENDGRID_API_KEY')) response = sg.send(message) print(response.status_code) except Exception as e: print(e.message)
With those simple modifications, it will now send the image when you get sad.