So I tried the methods that were mentioned in the previously asked similar question but none of them works for my python file. I have been on it for two days and can't seem to find a solution how to run this file from C# form on button click.
IronPython doesn't work because the python script has libraries that cannot be imported in Ironpython.
Running it from cmd doesn't work because cmd starts and then gets closed in a second.
Here's the code:
import imutils
from imutils import face_utils
from utils import *
import numpy as np
import pyautogui as pag
import imutils
import dlib
import cv2
# Thresholds and consecutive frame length for triggering the mouse action.
MOUTH_AR_THRESH = 0.3
MOUTH_AR_CONSECUTIVE_FRAMES = 3
EYE_AR_THRESH = 0.20
EYE_AR_CONSECUTIVE_FRAMES = 5
WINK_AR_DIFF_THRESH = 0.001
WINK_AR_CLOSE_THRESH = 0.2
WINK_CONSECUTIVE_FRAMES = 4
# Initialize the frame counters for each action as well as
# booleans used to indicate if action is performed or not
MOUTH_COUNTER = 0
EYE_COUNTER = 0
WINK_COUNTER = 0
INPUT_MODE = False
EYE_CLICK = False
LEFT_WINK = False
RIGHT_WINK = False
SCROLL_MODE = False
ANCHOR_POINT = (0, 0)
WHITE_COLOR = (255, 255, 255)
YELLOW_COLOR = (0, 255, 255)
RED_COLOR = (0, 0, 255)
GREEN_COLOR = (0, 255, 0)
BLUE_COLOR = (255, 0, 0)
BLACK_COLOR = (0, 0, 0)
# Initialize Dlib's face detector (HOG-based) and then create
# the facial landmark predictor
shape_predictor = "model/shape_predictor_68_face_landmarks.dat"
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor(shape_predictor)
# Grab the indexes of the facial landmarks for the left and
# right eye, nose and mouth respectively
(lStart, lEnd) = face_utils.FACIAL_LANDMARKS_IDXS["left_eye"]
(rStart, rEnd) = face_utils.FACIAL_LANDMARKS_IDXS["right_eye"]
(nStart, nEnd) = face_utils.FACIAL_LANDMARKS_IDXS["nose"]
(mStart, mEnd) = face_utils.FACIAL_LANDMARKS_IDXS["mouth"]
# Video capture
vid = cv2.VideoCapture(0)
resolution_w = 1366
resolution_h = 768
cam_w = 640
cam_h = 480
unit_w = resolution_w / cam_w
unit_h = resolution_h / cam_h
while True:
# Grab the frame from the threaded video file stream, resize
# it, and convert it to grayscale
# channels)
_, frame = vid.read()
frame = cv2.flip(frame, 1)
frame = imutils.resize(frame, width=cam_w, height=cam_h)
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# Detect faces in the grayscale frame
rects = detector(gray, 0)
# Loop over the face detections
if len(rects) > 0:
rect = rects[0]
else:
cv2.imshow("Frame", frame)
key = cv2.waitKey(1) & 0xFF
continue
# Determine the facial landmarks for the face region, then
# convert the facial landmark (x, y)-coordinates to a NumPy
# array
shape = predictor(gray, rect)
shape = face_utils.shape_to_np(shape)
# Extract the left and right eye coordinates, then use the
# coordinates to compute the eye aspect ratio for both eyes
mouth = shape[mStart:mEnd]
leftEye = shape[lStart:lEnd]
rightEye = shape[rStart:rEnd]
nose = shape[nStart:nEnd]
# Because I flipped the frame, left is right, right is left.
temp = leftEye
leftEye = rightEye
rightEye = temp
# Average the mouth aspect ratio together for both eyes
mar = mouth_aspect_ratio(mouth)
leftEAR = eye_aspect_ratio(leftEye)
rightEAR = eye_aspect_ratio(rightEye)
ear = (leftEAR + rightEAR) / 2.0
diff_ear = np.abs(leftEAR - rightEAR)
nose_point = (nose[3, 0], nose[3, 1])
# Compute the convex hull for the left and right eye, then
# visualize each of the eyes
mouthHull = cv2.convexHull(mouth)
leftEyeHull = cv2.convexHull(leftEye)
rightEyeHull = cv2.convexHull(rightEye)
cv2.drawContours(frame, [mouthHull], -1, YELLOW_COLOR, 1)
cv2.drawContours(frame, [leftEyeHull], -1, YELLOW_COLOR, 1)
cv2.drawContours(frame, [rightEyeHull], -1, YELLOW_COLOR, 1)
for (x, y) in np.concatenate((mouth, leftEye, rightEye), axis=0):
cv2.circle(frame, (x, y), 2, GREEN_COLOR, -1)
# Check to see if the eye aspect ratio is below the blink
# threshold, and if so, increment the blink frame counter
if diff_ear > WINK_AR_DIFF_THRESH:
if leftEAR < rightEAR:
if leftEAR < EYE_AR_THRESH:
WINK_COUNTER += 1
if WINK_COUNTER > WINK_CONSECUTIVE_FRAMES:
pag.click(button='left')
WINK_COUNTER = 0
elif leftEAR > rightEAR:
if rightEAR < EYE_AR_THRESH:
WINK_COUNTER += 1
if WINK_COUNTER > WINK_CONSECUTIVE_FRAMES:
pag.click(button='right')
WINK_COUNTER = 0
else:
WINK_COUNTER = 0
else:
if ear <= EYE_AR_THRESH:
EYE_COUNTER += 1
if EYE_COUNTER > EYE_AR_CONSECUTIVE_FRAMES:
SCROLL_MODE = not SCROLL_MODE
# INPUT_MODE = not INPUT_MODE
EYE_COUNTER = 0
# nose point to draw a bounding box around it
else:
EYE_COUNTER = 0
WINK_COUNTER = 0
if mar > MOUTH_AR_THRESH:
MOUTH_COUNTER += 1
if MOUTH_COUNTER >= MOUTH_AR_CONSECUTIVE_FRAMES:
# if the alarm is not on, turn it on
INPUT_MODE = not INPUT_MODE
# SCROLL_MODE = not SCROLL_MODE
MOUTH_COUNTER = 0
ANCHOR_POINT = nose_point
else:
MOUTH_COUNTER = 0
if INPUT_MODE:
cv2.putText(frame, "READING INPUT!", (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, RED_COLOR, 2)
x, y = ANCHOR_POINT
nx, ny = nose_point
w, h = 60, 35
multiple = 1
cv2.rectangle(frame, (x - w, y - h), (x + w, y + h), GREEN_COLOR, 2)
cv2.line(frame, ANCHOR_POINT, nose_point, BLUE_COLOR, 2)
dir = direction(nose_point, ANCHOR_POINT, w, h)
cv2.putText(frame, dir.upper(), (10, 90), cv2.FONT_HERSHEY_SIMPLEX, 0.7, RED_COLOR, 2)
drag = 18
if dir == 'right':
pag.moveRel(drag, 0)
elif dir == 'left':
pag.moveRel(-drag, 0)
elif dir == 'up':
if SCROLL_MODE:
pag.scroll(40)
else:
pag.moveRel(0, -drag)
elif dir == 'down':
if SCROLL_MODE:
pag.scroll(-40)
else:
pag.moveRel(0, drag)
if SCROLL_MODE:
cv2.putText(frame, 'SCROLL MODE IS ON!', (10, 60), cv2.FONT_HERSHEY_SIMPLEX, 0.7, RED_COLOR, 2)
# Show the frame
cv2.imshow("Frame", frame)
key = cv2.waitKey(1) & 0xFF
# If the `Esc` key was pressed, break from the loop
if key == 27:
break
# Do a bit of cleanup
cv2.destroyAllWindows()
vid.release()
