I have update this Repository

.gitignore

@@ -0,0 +1 @@
+*.mp4

Capture_Reference_image/Capture_Reference_Image.py

@@ -1,63 +1,63 @@
-
-import cv2 
-import time
-import os
-# chose your camera number:
-cam_number =2
-camera = cv2.VideoCapture(cam_number)
-starting_time =time.time()
-Frame_Counter= 0
-Cap_frame =0 
-Dir_name = "capture_images"
-number_image_captured =20
-capture_image=False
-while True:
-    # checking the Directory Exist or not .
-    IsDirExist = os.path.exists(Dir_name)
-    print(IsDirExist)
-    # if there is no Directory named "capture_image", simply create it. using os 
-    if not IsDirExist:
-        os.mkdir(Dir_name)
-
-    Frame_Counter+=1
-    # reading the frames from camera 
-    ret, frame = camera.read()
-    # reading saving frame seperatly
-    ret, saving_frame = camera.read()
-    # finding with and height of image 
-    height, width, dim = saving_frame.shape
-    # print(width, height, dim)
-
-    # writing the width and height of on the image saving image 
-    cv2.putText(saving_frame, f"Height: {height}", (30, 50), cv2.FONT_HERSHEY_COMPLEX, 0.4, (0,255,0),1)
-    cv2.putText(saving_frame, f"Width:  {width}", (30, 70), cv2.FONT_HERSHEY_COMPLEX, 0.4, (0,255,0),1)
-    # capture frame if capture_image is ture and number_image_captured are less then 10
-    # if we press 'c' on keyboard then capture_image become 'True'
-    if capture_image==True and Cap_frame <= number_image_captured:
-        Cap_frame+=1
-        cv2.putText(frame, 'Capturing', (50, 70), cv2.FONT_HERSHEY_COMPLEX, 2, (0,244, 255),1)
-        cv2.imwrite(f"{Dir_name}/frame-{Cap_frame}.png", saving_frame)
-    else:
-        cv2.putText(frame, 'Not Capturing', (50, 70), cv2.FONT_HERSHEY_COMPLEX, 2, (255,0, 255),1)
-        Cap_frame =0
-        capture_image =False
-    cv2.imshow("frame", frame)
-    cv2.imshow("saving Image", saving_frame)
-    total_time = time.time()
-    frame_time=total_time -starting_time
-    # calculating how much frame pass in each second
-
-    fps = Frame_Counter/frame_time
-    # print(fps)
-    # print(capture_image)
-     # when we press 'q' it quites the program
-    if cv2.waitKey(1) == ord('q'):
-        break
-    # if we press 'c' on the keyboard then it starts capturing the images. 
-    if cv2.waitKey(1)==ord('c'):
-        capture_image= True
-
-# finally closing the camera 
-camera.release()
-# closing all opend windows
+
+import cv2 
+import time
+import os
+# chose your camera number:
+cam_number =2
+camera = cv2.VideoCapture(cam_number)
+starting_time =time.time()
+Frame_Counter= 0
+Cap_frame =0 
+Dir_name = "capture_images"
+number_image_captured =20
+capture_image=False
+while True:
+    # checking the Directory Exist or not .
+    IsDirExist = os.path.exists(Dir_name)
+    print(IsDirExist)
+    # if there is no Directory named "capture_image", simply create it. using os 
+    if not IsDirExist:
+        os.mkdir(Dir_name)
+
+    Frame_Counter+=1
+    # reading the frames from camera 
+    ret, frame = camera.read()
+    # reading saving frame seperatly
+    ret, saving_frame = camera.read()
+    # finding with and height of image 
+    height, width, dim = saving_frame.shape
+    # print(width, height, dim)
+
+    # writing the width and height of on the image saving image 
+    cv2.putText(saving_frame, f"Height: {height}", (30, 50), cv2.FONT_HERSHEY_COMPLEX, 0.4, (0,255,0),1)
+    cv2.putText(saving_frame, f"Width:  {width}", (30, 70), cv2.FONT_HERSHEY_COMPLEX, 0.4, (0,255,0),1)
+    # capture frame if capture_image is ture and number_image_captured are less then 10
+    # if we press 'c' on keyboard then capture_image become 'True'
+    if capture_image==True and Cap_frame <= number_image_captured:
+        Cap_frame+=1
+        cv2.putText(frame, 'Capturing', (50, 70), cv2.FONT_HERSHEY_COMPLEX, 2, (0,244, 255),1)
+        cv2.imwrite(f"{Dir_name}/frame-{Cap_frame}.png", saving_frame)
+    else:
+        cv2.putText(frame, 'Not Capturing', (50, 70), cv2.FONT_HERSHEY_COMPLEX, 2, (255,0, 255),1)
+        Cap_frame =0
+        capture_image =False
+    cv2.imshow("frame", frame)
+    cv2.imshow("saving Image", saving_frame)
+    total_time = time.time()
+    frame_time=total_time -starting_time
+    # calculating how much frame pass in each second
+
+    fps = Frame_Counter/frame_time
+    # print(fps)
+    # print(capture_image)
+     # when we press 'q' it quites the program
+    if cv2.waitKey(1) == ord('q'):
+        break
+    # if we press 'c' on the keyboard then it starts capturing the images. 
+    if cv2.waitKey(1)==ord('c'):
+        capture_image= True
+   
+# finally closing the camera 
+camera.release()
+# closing all opend windows
 cv2.destroyAllWindows()

Capture_Reference_image/Distance_Measurement.py

@@ -1,54 +1,54 @@
-import cv2 as cv
-
-
-# data
-Know_distance =30 # in centimeters
-#mine is 14.3 something, measure your face width, are google it 
-Know_width_face =14.3 #centimeters
-# chose your camera
-cam_number =1
-face_detector = cv.CascadeClassifier('data/haarcascade_frontalface_default.xml')
-camera = cv.VideoCapture(cam_number)
-def FocalLengthFinder(Measured_distance, real_width_of_face, width_of_face_in_image):
-    # finding focal length
-    focal_length = (width_of_face_in_image* Measured_distance)/real_width_of_face
-    return focal_length
-
-def Distance_Measurement(face_real_width, Focal_Length, face_with_in_image):
-   distance= (face_real_width * Focal_Length)/face_with_in_image 
-   return distance 
-def Face_Detection(image):
-    f_width =0
-    Gray_image = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
-    faces = face_detector.detectMultiScale(Gray_image, 1.3, 5)
-    for (x, y, h, w) in faces:
-        cv.rectangle(image, (x,y), (x+w, y+h), (255,255,255), 1)
-        f_width =w
-    print(f_width)
-    return f_width, image
-reference_image =cv.imread("rf.png")
-face_w , image_read= Face_Detection(reference_image)
-cv.imshow("ref", image_read)
-calculate_focal_length =FocalLengthFinder(Know_distance, Know_width_face,face_w)
-print(calculate_focal_length)
-font = cv.FONT_HERSHEY_SIMPLEX 
-while True:
-    ret, frame = camera.read()
-    height, width, dim = frame.shape
-    # change the color of image
-    # print(height, width)
-    Gray_image = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
-    faces = face_detector.detectMultiScale(Gray_image, 1.3, 5)
-    for (x, y, h, w) in faces:
-        cv.rectangle(frame, (x,y), (x+w, y+h), (255,255,255), 1)
-        distance =Distance_Measurement(Know_width_face,calculate_focal_length, w)
-        print(distance)
-
-        cv.putText(frame, f" Distance = {distance}", (50,50),font, 0.7, (0,255,0), 3)
-
-    cv.imshow('frame', frame)
-
-    if cv.waitKey(1)==ord('q'):
-        break
-camera.release()
-cv.destroyAllWindows()
+import cv2 as cv
+
+
+# data
+Know_distance =30 # in centimeters
+#mine is 14.3 something, measure your face width, are google it 
+Know_width_face =14.3 #centimeters
+# chose your camera
+cam_number =1
+face_detector = cv.CascadeClassifier('data/haarcascade_frontalface_default.xml')
+camera = cv.VideoCapture(cam_number)
+def FocalLengthFinder(Measured_distance, real_width_of_face, width_of_face_in_image):
+    # finding focal length
+    focal_length = (width_of_face_in_image* Measured_distance)/real_width_of_face
+    return focal_length
+
+def Distance_Measurement(face_real_width, Focal_Length, face_with_in_image):
+   distance= (face_real_width * Focal_Length)/face_with_in_image 
+   return distance 
+def Face_Detection(image):
+    f_width =0
+    Gray_image = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
+    faces = face_detector.detectMultiScale(Gray_image, 1.3, 5)
+    for (x, y, h, w) in faces:
+        cv.rectangle(image, (x,y), (x+w, y+h), (255,255,255), 1)
+        f_width =w
+    print(f_width)
+    return f_width, image
+reference_image =cv.imread("rf.png")
+face_w , image_read= Face_Detection(reference_image)
+cv.imshow("ref", image_read)
+calculate_focal_length =FocalLengthFinder(Know_distance, Know_width_face,face_w)
+print(calculate_focal_length)
+font = cv.FONT_HERSHEY_SIMPLEX 
+while True:
+    ret, frame = camera.read()
+    height, width, dim = frame.shape
+    # change the color of image
+    # print(height, width)
+    Gray_image = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
+    faces = face_detector.detectMultiScale(Gray_image, 1.3, 5)
+    for (x, y, h, w) in faces:
+        cv.rectangle(frame, (x,y), (x+w, y+h), (255,255,255), 1)
+        distance =Distance_Measurement(Know_width_face,calculate_focal_length, w)
+        print(distance)
+
+        cv.putText(frame, f" Distance = {distance}", (50,50),font, 0.7, (0,255,0), 3)
+
+    cv.imshow('frame', frame)
+
+    if cv.waitKey(1)==ord('q'):
+        break
+camera.release()
+cv.destroyAllWindows()