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 " + url+url1) ############################## st.image(image) if bytes_data is None: st.stop()