141 lines
4.5 KiB
Python
141 lines
4.5 KiB
Python
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import copy
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import os
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import time
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import cv2
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import numpy as np
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#from playsound import playsound
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#import pygame as pg
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## Define our config values
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# What is our min dish count to alarm on?
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min_dishes = 1
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# Define areas we want to ignore
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# First value is the x range, second is the y range
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ignore_list = ["339-345,257-260"]
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# Set our timestamp
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time_stamp = time.strftime("%Y%m%d%H%M%S")
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# Set our circle detection variables
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circle_sensitivity = 40 # Larger numbers increase false positives
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#circle_sensitivity = 60 # Larger numbers increase false positives
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min_rad = 30 # Tweak this if you're detecting circles that are too small
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max_rad = 75 # Tweak if you're detecting circles that are too big (Ie: round sinks)
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# Cropping the image allows us to only process areas of the image
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# that should have images. Set our crop values
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crop_left = 100
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crop_right = 2000
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crop_top = 0
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crop_bottom = 2000
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def should_ignore(ignore_list, x, y):
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# Loop through our ignore_list and check for this x/y
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ignore = False
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for range in ignore_list:
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x_range = range.split(',')[0]
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y_range = range.split(',')[1]
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x_min = int(x_range.split('-')[0])
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x_max = int(x_range.split('-')[1])
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y_min = int(y_range.split('-')[0])
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y_max = int(y_range.split('-')[1])
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if (x >= x_min and x <= x_max and y >= y_min and y <= y_max):
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ignore = True
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return ignore
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def play_music(music_file, volume=0.8):
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'''
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stream music with mixer.music module in a blocking manner
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this will stream the sound from disk while playing
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'''
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# set up the mixer
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freq = 44100 # audio CD quality
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bitsize = -16 # unsigned 16 bit
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channels = 2 # 1 is mono, 2 is stereo
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buffer = 2048 # number of samples (experiment to get best sound)
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pg.mixer.init(freq, bitsize, channels, buffer)
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# volume value 0.0 to 1.0
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pg.mixer.music.set_volume(volume)
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clock = pg.time.Clock()
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try:
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pg.mixer.music.load(music_file)
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#print("Music file {} loaded!".format(music_file))
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except pg.error:
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print("File {} not found! ({})".format(music_file, pg.get_error()))
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return
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pg.mixer.music.play()
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while pg.mixer.music.get_busy():
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# check if playback has finished
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clock.tick(30)
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def check_if_dishes_exist():
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# Note: Larger images require more processing power and have more false positives
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image_original = cv2.imread(os.path.join('dirty.jpeg'))
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#print("Cropping image to limit processing to just the sink")
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image = image_original[crop_left:crop_right, crop_top:crop_bottom]
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image = image_original
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#print("Copying image")
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output = copy.copy(image)
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#print("Blurring image")
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blurred = cv2.GaussianBlur(image, (9, 9), 2, 2)
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cv2.imwrite(os.path.join('blurred.jpg'), blurred)
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#print("Converting to grey")
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gray = cv2.cvtColor(blurred, cv2.COLOR_BGR2GRAY)
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cv2.imwrite(os.path.join('gray.jpg'), gray)
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#print("Detecting circles in blurred and greyed image")
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circles = cv2.HoughCircles(gray, cv2.HOUGH_GRADIENT, 1, 20,
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param1=100,
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param2=circle_sensitivity,
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minRadius=min_rad,
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maxRadius=max_rad)
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#print("Checking if we found images")
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if circles is not None:
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dish_count = 0
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print("Dishes Found!")
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# convert the (x, y) coordinates and radius of the circles to integers
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circles = np.round(circles[0, :]).astype("int")
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# loop over the (x, y) coordinates and radius of the circles
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for (x, y, r) in circles:
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# draw the circle in the output image, then draw a rectangle
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# corresponding to the center of the circle
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cv2.circle(output, (x, y), r, (0, 255, 0), 4)
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cv2.rectangle(output, (x - 5, y - 5), (x + 5, y + 5), (0, 128, 255), -1)
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# Check our ignore_list
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if (should_ignore(ignore_list, x, y)):
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print("Circle in ignore_list: Ignoring")
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else:
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dish_count += 1
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print("Dish count:%s" % (str(dish_count)))
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cv2.imwrite(os.path.join('detected.jpg'), output)
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if dish_count >= min_dishes:
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print("Playing dirty dishes sound..")
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global_vars.current_sink_status = "dirty"
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# optional volume 0 to 1.0
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print("test")
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else:
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print("No Dishes Found!")
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if __name__ == "__main__":
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check_if_dishes_exist()
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