diff --git a/projects/Ai_Attendence_Project.py/Attendence.csv b/projects/Ai_Attendence_Project.py/Attendence.csv
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+++ b/projects/Ai_Attendence_Project.py/Attendence.csv
@@ -0,0 +1 @@
+ELON MUSK,20:12:05,08/12/2021
diff --git a/projects/Ai_Attendence_Project.py/Images/elonmusk.jpg b/projects/Ai_Attendence_Project.py/Images/elonmusk.jpg
new file mode 100644
index 00000000..f7053e94
Binary files /dev/null and b/projects/Ai_Attendence_Project.py/Images/elonmusk.jpg differ
diff --git a/projects/Ai_Attendence_Project.py/Readme b/projects/Ai_Attendence_Project.py/Readme
new file mode 100644
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+++ b/projects/Ai_Attendence_Project.py/Readme
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+#Ai_Attendence_Project 
+<br>
+This Program detects the face of the given members and will record the presence 
+in attendence.csv file with date and time 
+#Libraries Used
+
+1. Dlib 
+2. face-recognition 
+3. os
+4. cv2
+5. numpy
+6. dateandtime
diff --git a/projects/Ai_Attendence_Project.py/main.py b/projects/Ai_Attendence_Project.py/main.py
new file mode 100644
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+++ b/projects/Ai_Attendence_Project.py/main.py
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+import cv2
+import numpy as np
+import face_recognition
+import os
+from datetime import datetime
+
+path = 'Images'
+Images = []
+PersonName = []
+mylist = os.listdir(path)
+print(mylist)
+# for separating the name from their extensions
+for cu_img in mylist:
+    current_Img = cv2.imread(f'{path}/{cu_img}')
+    Images.append(current_Img)
+    PersonName.append(os.path.splitext(cu_img)[0])
+print(PersonName)
+
+
+def encodings(images):
+    encodelist = []
+    for img in images:
+        img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+        encode = face_recognition.face_encodings(img)[0]
+        encodelist.append(encode)
+    return encodelist
+
+
+encode_list_Known = encodings(Images)
+print("ALL ENCODING FOUND!!!")
+
+
+def attendance(name):
+    with open('Attendence.csv', 'r+') as f:
+        myDataList = f.readlines()
+        nameList = []
+        for line in myDataList:
+            entry = line.split(',')
+            nameList.append(entry[0])
+        if name not in nameList:
+            time_now = datetime.now()
+            tStr = time_now.strftime('%H:%M:%S')
+            dStr = time_now.strftime('%d/%m/%Y')
+            f.writelines(f'\n{name},{tStr},{dStr}')
+
+
+cap = cv2.VideoCapture(0)
+
+while True:
+    ret, frame = cap.read()
+    faces = cv2.resize(frame, (0, 0), None, 0.25, 0.25)
+    faces = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+
+    faces_currentframe = face_recognition.face_locations(faces)
+    encode_currentframe = face_recognition.face_encodings(faces, faces_currentframe)
+
+    for encodeFace, faceLoc in zip(encode_currentframe, faces_currentframe):
+        matches = face_recognition.compare_faces(encode_list_Known, encodeFace)
+        faceDistance = face_recognition.face_distance(encode_list_Known, encodeFace)
+
+        matchIndex = np.argmin(faceDistance)
+
+        if matches[matchIndex]:
+            name = PersonName[matchIndex].upper()
+            y1, x2, y2, x1 = faceLoc
+            #y1, x2, y2, x1 = y1 * 4, x2 * 4, y2 * 4, x1 * 4
+            cv2.rectangle(frame, (x1, y1), (x2, y2), (255, 0, 0), 2)
+            cv2.rectangle(frame, (x1, y2 - 35), (x2, y2), (0, 255, 0), cv2.FILLED)
+            cv2.putText(frame, name, (x1 + 6, y2 - 6), cv2.FONT_HERSHEY_COMPLEX, 1, (255, 255, 255), 2)
+            attendance(name)
+
+    cv2.imshow("camera", frame)
+    if cv2.waitKey(10) == 13:
+        break
+cap.release()
+cv2.destroyAllWindows()