Create app.py

app.py

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+from keras.models import load_model
+from PIL import Image
+import numpy as np
+import cv2 
+import requests
+
+import face_recognition
+import os
+from datetime import datetime
+
+#the following are to do with this interactive notebook code
+from matplotlib import pyplot as plt # this lets you draw inline pictures in the notebooks
+import pylab # this allows you to control figure size 
+pylab.rcParams['figure.figsize'] = (10.0, 8.0) # this controls figure size in the notebook
+
+import io
+import streamlit as st
+bytes_data=None
+
+Images = []
+classnames = []
+myList = os.listdir()
+#st.write(myList)
+for cls in myList:
+    if os.path.splitext(cls)[1] == ".jpg"  :
+        curImg = cv2.imread(f'{cls}')
+        Images.append(curImg)
+        classnames.append(os.path.splitext(cls)[0])
+st.write(classnames)
+
+
+def findEncodings(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
+
+
+encodeListknown = findEncodings(Images)
+st.write('Encoding Complete')
+
+img_file_buffer=st.camera_input("Take a picture")
+if img_file_buffer is not None:
+     
+     test_image = Image.open(img_file_buffer)
+     st.image(test_image, use_column_width=True)
+     
+     image = np.asarray(test_image)
+    
+     #########################
+     imgS = cv2.resize(image,(0,0),None,0.25,0.25)
+     imgS = cv2.cvtColor(imgS, cv2.COLOR_BGR2RGB)
+     facesCurFrame = face_recognition.face_locations(imgS)
+     encodesCurFrame = face_recognition.face_encodings(imgS,facesCurFrame)
+
+     for encodeFace,faceLoc in zip(encodesCurFrame,facesCurFrame):
+         matches = face_recognition.compare_faces(encodeListknown,encodeFace)
+         faceDis = face_recognition.face_distance(encodeListknown,encodeFace)
+         #print(faceDis)
+         matchIndex = np.argmin(faceDis)
+
+         if matches[matchIndex]:
+             name = classnames[matchIndex].upper()
+             st.write(name)
+             y1, x2, y2, x1 = faceLoc
+             y1, x2, y2, x1 = y1*4,x2*4,y2*4,x1*4
+             cv2.rectangle(image,(x1,y1),(x2,y2),(0,255,0),2)
+             cv2.rectangle(image,(x1,y2-35),(x2,y2),(0,255,0),cv2.FILLED)
+             cv2.putText(image,name,(x1+6,y2-6),cv2.FONT_HERSHEY_COMPLEX,1,(255, 255, 255),2)
+
+             ##############
+             # url = "https://rgiattendance.000webhostapp.com" 
+             # url1 = "/update.php"
+             # data1 =  {'name':name   }
+             # response = requests.post(url+url1, data=data1)
+
+             # https://aimljul23f.glitch.me/fsave?nm=testname
+             url = "https://aimljul23f.glitch.me/" 
+             url1 = "fsave?nm=" + name 
+             # data1 =  {'name':name   } 
+             response = requests.post(url+url1)
+             
+             if response.status_code == 200 : 
+                 st.write(" data updated on : " + url)
+             else : st.write("data not updated ")
+                 
+     ##############################
+     st.image(image)
+if bytes_data is None:
+     st.stop()