Update app.py

app.py

@@ -1,19 +1,33 @@
+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":
+    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 = []
@@ -23,46 +37,49 @@ def findEncodings(Images):
         encodeList.append(encode)
     return encodeList
 
-encodeListknown = findEncodings(Images)
 
+encodeListknown = findEncodings(Images)
 st.write('Encoding Complete')
 
-cap = cv2.VideoCapture(0)  # Use 0 for the default camera
-while True:
-    ret, frame = cap.read()
-    frame = cv2.flip(frame, 1)  # Flip horizontally
-    st.image(frame)
+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)
     
-    if ret:
-        imgS = cv2.resize(frame, (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)
-            matchIndex = np.argmin(faceDis)
-
-            if matches[matchIndex]:
-                name = classnames[matchIndex]
-                st.write(name)
-                y1, x2, y2, x1 = faceLoc
-                y1, x2, y2, x1 = y1 * 4, x2 * 4, y2 * 4, x1 * 4
-                cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 255, 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)
+     #########################
+     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)
 
-                # Sending data to a URL
-                url = "https://kiwi-whispering-plier.glitch.me/update"
-                data1 = {'name': name}
-                response = requests.post(url, data=data1)
+     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 response.status_code == 200:
-                    st.write("Data updated on: " + url)
-                else:
-                    st.write("Data not updated")
+         if matches[matchIndex]:
+             name = classnames[matchIndex]
+             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://kiwi-whispering-plier.glitch.me/update" 
+             data1 =  {'name':name   }
+             response = requests.post(url, data=data1)
+             
+             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()
+     st.stop()