165 lines
4.7 KiB
Python
165 lines
4.7 KiB
Python
# Show a windows with the video stream and testing information
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# Import required modules
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import face_recognition
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import cv2
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import configparser
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import os
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import sys
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import json
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import numpy
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import time
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# Get the absolute path to the current file
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path = os.path.dirname(os.path.abspath(__file__))
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# Read config from disk
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config = configparser.ConfigParser()
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config.read(path + "/../config.ini")
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# Start capturing from the configured webcam
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video_capture = cv2.VideoCapture(int(config.get("video", "device_id")))
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# Let the user know what's up
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print("""
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Opening a window with a test feed
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Press ctrl+C in this terminal to quit
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Click on the image to enable or disable slow mode
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""")
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def mouse(event, x, y, flags, param):
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"""Handle mouse events"""
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global slow_mode
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# Toggle slowmode on click
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if event == cv2.EVENT_LBUTTONDOWN:
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slow_mode = not slow_mode
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# Open the window and attach a a mouse listener
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cv2.namedWindow("Howdy Test")
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cv2.setMouseCallback("Howdy Test", mouse)
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# Enable a delay in the loop
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slow_mode = False
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# Count all frames ever
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total_frames = 0
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# Count all frames per second
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sec_frames = 0
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# Last secands FPS
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fps = 0
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# The current second we're counting
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sec = int(time.time())
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# Wrap everything in an keyboard interupt handler
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try:
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while True:
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# Inclement the frames
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total_frames += 1
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sec_frames += 1
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# Id we've entered a new second
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if sec != int(time.time()):
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# Set the last seconds FPS
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fps = sec_frames
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# Set the new second and reset the counter
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sec = int(time.time())
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sec_frames = 0
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# Grab a single frame of video
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ret, frame = (video_capture.read())
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# Make a frame to put overlays in
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overlay = frame.copy()
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# Fetch the frame height and width
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height, width = frame.shape[:2]
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# Create a histogram of the image with 8 values
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hist = cv2.calcHist([frame],[0],None,[8],[0,256])
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# Fill with the total values combined for percentage calulation
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hist_total = 0
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# Fill with the overal containing percentage
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hist_perc = []
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# Loop though all values to add them to the total
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for value in hist:
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hist_total += value[0]
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# Loop though all values to calculate a pensentage and add it to the overlay
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for index, value in enumerate(hist):
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value_perc = float(value[0]) / hist_total * 100
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hist_perc.append(value_perc)
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# Top left pont, 10px margins
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p1 = (20 + (10 * index), 10)
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# Bottom right point makes the bar 10px thick, with an height of half the percentage
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p2 = (10 + (10 * index), int(value_perc / 2 + 10))
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# Draw the bar in green
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cv2.rectangle(overlay, p1, p2, (0, 200, 0), thickness=cv2.FILLED)
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# Draw a stripe indicating the dark threshold
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cv2.rectangle(overlay, (8, 35), (20, 36), (255, 0, 0), thickness=cv2.FILLED)
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def print_text(line_number, text):
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"""Print the status text by line number"""
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cv2.putText(overlay, text, (10, height - 10 - (10 * line_number)), cv2.FONT_HERSHEY_SIMPLEX, .3, (0, 255, 0), 0, cv2.LINE_AA)
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# Print the statis in the bottom left
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print_text(0, "RESOLUTION: " + str(height) + "x" + str(width))
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print_text(1, "FPS: " + str(fps))
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print_text(2, "FRAMES: " + str(total_frames))
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# Show that slow mode is on, if it's on
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if slow_mode:
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cv2.putText(overlay, "SLOW MODE", (width - 66, height - 10), cv2.FONT_HERSHEY_SIMPLEX, .3, (0, 0, 255), 0, cv2.LINE_AA)
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# Ignore dark frames
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if hist_perc[0] > 50:
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# Show that this is an ignored frame in the top right
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cv2.putText(overlay, "DARK FRAME", (width - 68, 16), cv2.FONT_HERSHEY_SIMPLEX, .3, (0, 0, 255), 0, cv2.LINE_AA)
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else:
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# SHow that this is an active frame
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cv2.putText(overlay, "SCAN FRAME", (width - 68, 16), cv2.FONT_HERSHEY_SIMPLEX, .3, (0, 255, 0), 0, cv2.LINE_AA)
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# Get the locations of all faces and their locations
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face_locations = face_recognition.face_locations(frame)
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# Loop though all faces and paint a circle around them
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for loc in face_locations:
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# Get the center X and Y from the rectangular points
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x = int((loc[1] - loc[3]) / 2) + loc[3]
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y = int((loc[2] - loc[0]) / 2) + loc[0]
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# Get the raduis from the with of the square
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r = (loc[1] - loc[3]) / 2
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# Add 20% padding
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r = int(r + (r * 0.2))
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# Draw the Circle in green
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cv2.circle(overlay, (x, y), r, (0, 0, 230), 2)
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# Add the overlay to the frame with some transparency
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alpha = 0.65
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cv2.addWeighted(overlay, alpha, frame, 1 - alpha, 0, frame)
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# Show the image in a window
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cv2.imshow("Howdy Test", frame)
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# Quit on any keypress
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if cv2.waitKey(1) != -1:
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raise KeyboardInterrupt()
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# Delay the frame if slowmode is on
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if slow_mode:
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time.sleep(.55)
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# On ctrl+C
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except KeyboardInterrupt:
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# Let the user know we're stopping
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print("\nClosing window")
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# Release handle to the webcam
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video_capture.release()
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cv2.destroyAllWindows()
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