79 lines
2.0 KiB
Python
79 lines
2.0 KiB
Python
import io
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import picamera
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import cv2
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import numpy as np
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import datetime
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import time
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import Adafruit_CharLCD as LCD
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# Init camera
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camera = picamera.PiCamera()
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camera.resolution = (1280, 720)
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# Init classifier, various options:
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#~ /usr/share/opencv/haarcascades/haarcascade_frontalface_default.xml (~22sec)
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#~ /usr/share/opencv/haarcascades/haarcascade_frontalface_alt.xml (>25sec)
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#~ /usr/share/opencv/haarcascades/haarcascade_frontalface_alt2.xml (~21sec)
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#~ /usr/share/opencv/haarcascades/haarcascade_frontalface_alt_tree.xml (~14sec, seems to miss many faces)
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classifier = cv2.CascadeClassifier('/usr/share/opencv/haarcascades/haarcascade_frontalface_alt2.xml')
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# Set FPS (though RPi is probably to slow to meet it ;-)
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FPS = 1.0
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frameTimeDelta = datetime.timedelta(seconds=1.0/FPS)
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# Init LCD
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lcd_rs = 27
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lcd_en = 22
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lcd_d4 = 25
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lcd_d5 = 24
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lcd_d6 = 23
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lcd_d7 = 18
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lcd_backlight = 4
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lcd_columns = 16
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lcd_rows = 2
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lcd = LCD.Adafruit_CharLCD(lcd_rs, lcd_en, lcd_d4, lcd_d5, lcd_d6, lcd_d7,
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lcd_columns, lcd_rows, lcd_backlight)
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prevFaceCount = 0
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totalUse = 0
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while True:
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print(time.time(),"GO")
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start = datetime.datetime.utcnow()
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stream = io.BytesIO()
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camera.capture(stream, format='jpeg')
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print(time.time(),"captured")
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buff = np.fromstring(stream.getvalue(), dtype=np.uint8)
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image = cv2.imdecode(buff,1)
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gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
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print(time.time(),"grayed")
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faces = classifier.detectMultiScale(gray, 1.2, 5, minSize=(30,20))
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# TODO: time passed since last * prevFaceCount = usage
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print(time.time(),"Found {} faces".format(len(faces)))
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lcd.clear()
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lcd.message("Current {:>8}\nTotal {:>10}".format(len(faces), totalUse))
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if len(faces) < 1 and prevFaceCount < 1:
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lcd.set_backlight(0)
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else:
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lcd.set_backlight(1)
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end = datetime.datetime.utcnow()
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prevFaceCount = len(faces)
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totalUse += len(faces)
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if end - start < frameTimeDelta:
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waitTime = frameTimeDelta - (end-start)
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print("wait {}".waitTime.total_seconds())
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time.sleep(waitTime.total_seconds())
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