pytest.py

import numpy as np
import math
import time
from matplotlib import pyplot as plt
from Adafruit_AMG88xx import Adafruit_AMG88xx
from scipy.interpolate import griddata
import cv2
from helium_client import Helium
import json

helium = Helium("/dev/serial0")
helium.connect()

channel = helium.create_channel("aws_test")

# Access an instance of Configuration
config = channel.config()
# Start sensor
sensor = Adafruit_AMG88xx()
state = config.get("channel.state")
config.set("channel.state", state)

''' pixels = [28.75, 28.25, 27.75, 27.5, 27.5, 27.25, 28.5, 29,
28.25, 29.25, 27.25, 27, 27, 26.5, 29.75, 29.5,
29, 27, 27.25, 27, 26.5, 28, 30.25, 28.25,
28.5, 27.25, 27, 26.75, 26.5, 28.25, 30.25, 30.25,
29, 27, 27, 26.5, 26.75, 29.25, 31, 30.25,
27, 26.5, 26.75, 26.5, 26, 28.25, 29.75, 28.25,
27.25, 26.25, 26, 26, 26.75, 27, 27.5, 26.5,
27.5, 26, 26.25, 25.75, 25.75, 26, 26.75, 26.5]'''

while(1):
    if state == True:
        # Read pixels, convert them to values between 0 and 1, map them to an 8x8 grid
        pixels = sensor.readPixels()
        pixmax = max(pixels)
        pixels = [x / pixmax for x in pixels]
        points = [(math.floor(ix / 8), (ix % 8)) for ix in range(0, 64)]
        grid_x, grid_y = np.mgrid[0:7:32j, 0:7:32j]

        # bicubic interpolation of 8x8 grid to make a 32x32 grid
        bicubic = griddata(points, pixels, (grid_x, grid_y), method='cubic')
        image = np.array(bicubic)
        image = np.reshape(image, (32, 32))
        # print(image)
        plt.imsave('color_img.jpg', image)

        # Read image
        img = cv2.imread("color_img.jpg", cv2.IMREAD_GRAYSCALE)
        img = cv2.bitwise_not(img)

        # Setup SimpleBlobDetector parameters.
        params = cv2.SimpleBlobDetector_Params()

        # Change thresholds
        params.minThreshold = 10
        params.maxThreshold = 255

        # Filter by Area.
        params.filterByArea = True
        params.minArea = 5

        # Filter by Circularity
        params.filterByCircularity = True
        params.minCircularity = 0.1

        # Filter by Convexity
        params.filterByConvexity = False
        params.minConvexity = 0.87

        # Filter by Inertia
        params.filterByInertia = False
        params.minInertiaRatio = 0.01

        # Set up the detector with default parameters.
        detector = cv2.SimpleBlobDetector(params)

        # Detect blobs.
        keypoints = detector.detect(img)

        # Draw detected blobs as red circles.
        for i in range (0, len(keypoints)):
            x = keypoints[i].pt[0]
            y = keypoints[i].pt[1]
            print(x, y)
	      payload = json.dumps({"objects":str(len(keypoints))})
	      json.loads(payload)

        # Get the channel setting for interval_ms
        interval = config.get("channel.interval_ms")
        config.set("channel.interval_ms", interval)
	
	      state  = config.get("channel.state")
	      config.set("channel.state", state)
	      # Report the device having set interval_ms
	      channel.send(payload)
        time.sleep(int(interval))

    else:
        print("idle")
        time.sleep(5)
	      state = config.get("channel.state")
	      config.set("channel.state", state)