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Updated_distance.py
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Updated_distance.py
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import cv2
# variables
# distance from camera to object(face) measured
Known_distance = 30 # Inches
# mine is 14.3 something, measure your face width, are google it
Known_width = 5.7 # Inches
# Colors >>> BGR Format(BLUE, GREEN, RED)
GREEN = (0, 255, 0)
RED = (0, 0, 255)
BLACK = (0, 0, 0)
YELLOW = (0, 255, 255)
WHITE = (255, 255, 255)
CYAN = (255, 255, 0)
MAGENTA = (255, 0, 242)
GOLDEN = (32, 218, 165)
LIGHT_BLUE = (255, 9, 2)
PURPLE = (128, 0, 128)
CHOCOLATE = (30, 105, 210)
PINK = (147, 20, 255)
ORANGE = (0, 69, 255)
fonts = cv2.FONT_HERSHEY_COMPLEX
fonts2 = cv2.FONT_HERSHEY_SCRIPT_SIMPLEX
fonts3 = cv2.FONT_HERSHEY_COMPLEX_SMALL
fonts4 = cv2.FONT_HERSHEY_TRIPLEX
# Camera Object
cap = cv2.VideoCapture(0) # Number According to your Camera
Distance_level = 0
# Define the codec and create VideoWriter object
fourcc = cv2.VideoWriter_fourcc(*"XVID")
out = cv2.VideoWriter("output21.mp4", fourcc, 30.0, (640, 480))
# face detector object
face_detector = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
# focal length finder function
def FocalLength(measured_distance, real_width, width_in_rf_image):
# Function Discrption (Doc String)
"""
This Function Calculate the Focal Length(distance between lens to CMOS sensor), it is simple constant we can find by using
MEASURED_DISTACE, REAL_WIDTH(Actual width of object) and WIDTH_OF_OBJECT_IN_IMAGE
:param1 Measure_Distance(int): It is distance measured from object to the Camera while Capturing Reference image
:param2 Real_Width(int): It is Actual width of object, in real world (like My face width is = 5.7 Inches)
:param3 Width_In_Image(int): It is object width in the frame /image in our case in the reference image(found by Face detector)
:retrun Focal_Length(Float):
"""
focal_length = (width_in_rf_image * measured_distance) / real_width
return focal_length
# distance estimation function
def Distance_finder(Focal_Length, real_face_width, face_width_in_frame):
"""
This Function simply Estimates the distance between object and camera using arguments(Focal_Length, Actual_object_width, Object_width_in_the_image)
:param1 Focal_length(float): return by the Focal_Length_Finder function
:param2 Real_Width(int): It is Actual width of object, in real world (like My face width is = 5.7 Inches)
:param3 object_Width_Frame(int): width of object in the image(frame in our case, using Video feed)
:return Distance(float) : distance Estimated
"""
distance = (real_face_width * Focal_Length) / face_width_in_frame
return distance
# face detection Fauction
def face_data(image, CallOut, Distance_level):
"""
This function Detect face and Draw Rectangle and display the distance over Screen
:param1 Image(Mat): simply the frame
:param2 Call_Out(bool): If want show Distance and Rectangle on the Screen or not
:param3 Distance_Level(int): which change the line according the Distance changes(Intractivate)
:return1 face_width(int): it is width of face in the frame which allow us to calculate the distance and find focal length
:return2 face(list): length of face and (face paramters)
:return3 face_center_x: face centroid_x coordinate(x)
:return4 face_center_y: face centroid_y coordinate(y)
"""
face_width = 0
face_x, face_y = 0, 0
face_center_x = 0
face_center_y = 0
gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
faces = face_detector.detectMultiScale(gray_image, 1.3, 5)
for (x, y, w, h) in faces:
line_thickness = 2
# print(len(faces))
LLV = int(h * 0.12)
# print(LLV)
# cv2.rectangle(image, (x, y), (x+w, y+h), BLACK, 1)
cv2.line(image, (x, y + LLV), (x + w, y + LLV), (GREEN), line_thickness)
cv2.line(image, (x, y + h), (x + w, y + h), (GREEN), line_thickness)
cv2.line(image, (x, y + LLV), (x, y + LLV + LLV), (GREEN), line_thickness)
cv2.line(
image, (x + w, y + LLV), (x + w, y + LLV + LLV), (GREEN), line_thickness
)
cv2.line(image, (x, y + h), (x, y + h - LLV), (GREEN), line_thickness)
cv2.line(image, (x + w, y + h), (x + w, y + h - LLV), (GREEN), line_thickness)
face_width = w
face_center = []
# Drwaing circle at the center of the face
face_center_x = int(w / 2) + x
face_center_y = int(h / 2) + y
if Distance_level < 10:
Distance_level = 10
# cv2.circle(image, (face_center_x, face_center_y),5, (255,0,255), 3 )
if CallOut == True:
# cv2.line(image, (x,y), (face_center_x,face_center_y ), (155,155,155),1)
cv2.line(image, (x, y - 11), (x + 180, y - 11), (ORANGE), 28)
cv2.line(image, (x, y - 11), (x + 180, y - 11), (YELLOW), 20)
cv2.line(image, (x, y - 11), (x + Distance_level, y - 11), (GREEN), 18)
# cv2.circle(image, (face_center_x, face_center_y),2, (255,0,255), 1 )
# cv2.circle(image, (x, y),2, (255,0,255), 1 )
# face_x = x
# face_y = y
return face_width, faces, face_center_x, face_center_y
# reading reference image from directory
ref_image = cv2.imread("Ref_image.png")
ref_image_face_width, _, _, _ = face_data(ref_image, False, Distance_level)
Focal_length_found = FocalLength(Known_distance, Known_width, ref_image_face_width)
print(Focal_length_found)
cv2.imshow("ref_image", ref_image)
while True:
_, frame = cap.read()
# calling face_data function
# Distance_leve =0
face_width_in_frame, Faces, FC_X, FC_Y = face_data(frame, True, Distance_level)
# finding the distance by calling function Distance finder
for (face_x, face_y, face_w, face_h) in Faces:
if face_width_in_frame != 0:
Distance = Distance_finder(
Focal_length_found, Known_width, face_width_in_frame
)
Distance = round(Distance, 2)
# Drwaing Text on the screen
Distance_level = int(Distance)
cv2.putText(
frame,
f"Distance {Distance} Inches",
(face_x - 6, face_y - 6),
fonts,
0.5,
(BLACK),
2,
)
cv2.imshow("frame", frame)
out.write(frame)
if cv2.waitKey(1) == ord("q"):
break
cap.release()
# out.release()
cv2.destroyAllWindows()