Create app.py

app.py

@@ -0,0 +1,54 @@
+import streamlit as st
+import face_recognition
+import cv2
+import numpy as np
+import pickle
+from PIL import Image
+import pandas as pd
+
+pickle1 = open('rce_face_encodings.pkl','rb')
+rce_face_encodings = pickle.load(pickle1)
+pickle2 = open('rce_face_names.pkl','rb')
+rce_face_names = pickle.load(pickle2)
+pickle1.close()
+pickle2.close()
+
+
+
+face_locations = []
+face_names=[]
+
+
+st.header('RCEE :: FACE RECOGNTION')
+st.title('AI&DS')
+
+image = st.file_uploader('Pick any Image')
+if image:
+    st.image(image)
+    image = Image.open(image)
+    image = np.array(image)
+    face_locations = face_recognition.face_locations(image)
+    face_encodings = face_recognition.face_encodings(image,face_locations)
+
+    
+    for face_encoding in face_encodings:
+        matches = face_recognition.compare_faces(rce_face_encodings, face_encoding)
+        name = "Unknown"
+        face_distances = face_recognition.face_distance(rce_face_encodings, face_encoding)
+        best_match_index = np.argmin(face_distances)
+        if matches[best_match_index]:
+            name = rce_face_names[best_match_index]
+            face_names.append(name)
+    for (top, right, bottom, left), name in zip(face_locations, face_names):
+        cv2.rectangle(image, (left, top), (right, bottom), (0, 0, 255), 2)
+        cv2.rectangle(image, (left, bottom - 35), (right, bottom), (0, 0, 255), cv2.FILLED)
+        font = cv2.FONT_HERSHEY_DUPLEX
+        cv2.putText(image, name, (left + 6, bottom - 6), font, 1.0, (255, 255, 255), 1)
+    
+
+    image = cv2.cvtColor(image,cv2.COLOR_BGR2RGB)
+    cv2.imshow('Face Recognition', image)
+    df = pd.DataFrame({'Student_Name':face_names})
+    st.dataframe(df)
+    cv2.waitKey(0)
+    cv2.destroyAllWindows()