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visualooper.py
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# import statements
import cv2
import numpy as np
import pyautogui
import keyboard
# start video capture
cap = cv2.VideoCapture(0)
while True:
_, frame = cap.read()
frame = cv2.flip(frame, 1)
# defining the region of interest for efficiency - loop play
roi = frame[75:200, 75:200]
# defining the region of interest for recording
# note for self: the range for y comes first apparently
roi_2 = frame[75:200, 250:375]
# drawing a rectangle around the first region of interest
cv2.putText(frame, "Loop", (75, 63), cv2.FONT_HERSHEY_SIMPLEX, 1, (203, 192, 255), 2, cv2.LINE_AA)
cv2.rectangle(frame, (75, 75), (200, 200), (0, 0, 0), 2)
# drawing a rectangle around the second region of interest
cv2.putText(frame, "Record", (250, 63), cv2.FONT_HERSHEY_SIMPLEX, 1, (203, 192, 255), 2, cv2.LINE_AA)
cv2.rectangle(frame, (250, 75), (375, 200), (0, 0, 0), 2)
# creating a gaussian blurred frame
blurred_frame = cv2.GaussianBlur(roi, (5, 5), 0)
# creating a gaussian blurred frame for the second roi
blurred_frame_2 = cv2.GaussianBlur(roi_2, (5, 5), 0)
# converting BGR to HSV for the first roi
hsv = cv2.cvtColor(blurred_frame, cv2.COLOR_BGR2HSV)
# converting BGR to HSV for the second roi
hsv_2 = cv2.cvtColor(blurred_frame_2, cv2.COLOR_BGR2HSV)
# mask creation for brown-ish objects since the headstock of my guitar is brown
# This code isn't really the best way to go about it, so I used the colour of my tuner instead
#lower_brown = np.array([10, 100, 50], dtype=np.uint8)
#upper_brown = np.array([20, 255, 200], dtype=np.uint8)
# color of guitar tuner
lower_blue = np.array([100, 150, 0], dtype=np.uint8)
upper_blue = np.array([255, 255, 255], dtype=np.uint8)
# mask for the first roi
mask = cv2.inRange(hsv, lower_blue, upper_blue)
# mask for the second roi
mask_2 = cv2.inRange(hsv_2, lower_blue, upper_blue)
# filtering kernel
kernel = np.ones((3, 3), np.uint8)
# filtering for blue mask
mask = cv2.dilate(mask, kernel, iterations=4) # dilation
mask = cv2.GaussianBlur(mask, (5, 5), 100) # gaussian blur filtering
# filtering for blue mask in the second roi
mask_2 = cv2.dilate(mask_2, kernel, iterations=4) # dilation
mask_2 = cv2.GaussianBlur(mask_2, (5, 5), 100) # gaussian blur filtering
# finding contours for the masked objects/blue objects
contours, _ = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
# finding contours for the blue objects in the second roi
contours_2, _ = cv2.findContours(mask_2, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
# sorting the contours in ascending order
# test comment
contours = sorted(contours, key=lambda x: cv2.contourArea(x), reverse=True)
contours_2 = sorted(contours_2, key=lambda x: cv2.contourArea(x), reverse=True)
for contour in contours:
area = cv2.contourArea(contour)
if area > 300:
(x, y, w, h) = cv2.boundingRect(contour)
cv2.circle(roi, (x, y), 20, (0, 255, 0), 2)
cv2.drawContours(roi, contour, -1, (255, 0, 0), 1)
# He's a little confused, but he's got the spirit
if x > 75 and y > 75 and x < 200 and y < 200:
cv2.putText(frame, "No Action", (0, 20), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2, cv2.LINE_AA)
else:
cv2.putText(frame, "Action", (0, 20), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2, cv2.LINE_AA)
keyboard.press_and_release('shift + space')
for contour_2 in contours_2:
area = cv2.contourArea(contour_2)
if area > 300:
(x, y, w, h) = cv2.boundingRect(contour_2)
cv2.circle(roi_2, (x, y), 20, (0, 255, 0), 2)
cv2.drawContours(roi_2, contour_2, -1, (255, 0, 0), 1)
if x > 250 and y > 75 and x < 375 and y < 200:
cv2.putText(frame, "No Action", (0, 20), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2, cv2.LINE_AA)
else:
cv2.putText(frame, "Record", (500, 20), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2, cv2.LINE_AA)
keyboard.press_and_release('r')
keyboard.press_and_release('enter')
# opening the mask window for reference
cv2.imshow("Mask", mask)
# resizing and showing the main window
cv2.namedWindow("Frame", cv2.WINDOW_NORMAL)
cv2.resizeWindow("Frame", 1400, 1000)
cv2.imshow("Frame", frame)
key = cv2.waitKey(1)
if key == 27:
break
cap.release()
cv2.destroyAllWindows()