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| ####### Section 1 ################### | |
| from PIL import Image | |
| import numpy as np | |
| import opencv | |
| import requests | |
| import face_recognition | |
| import os | |
| import streamlit as st | |
| import urllib.request | |
| ####### Section 2 ################### | |
| p1 = "sarwan.jpg" | |
| p2 = "rattantata.png" | |
| p3 = "Ravinder.jpg" | |
| st.title("Face Recognition ") | |
| Images = [] | |
| classnames = [] | |
| #read images and train the face_recognition package | |
| img1 = cv2.imread(p1) | |
| Images.append(img1) | |
| classnames.append("Sarwan") | |
| img2 = cv2.imread(p2) | |
| Images.append(img2) | |
| classnames.append("RattanTata") | |
| img3 = cv2.imread(p3) | |
| Images.append(img3) | |
| classnames.append("RavinderKaur") | |
| directory = "facerecognition" | |
| myList = os.listdir(directory) | |
| for cls in myList: | |
| if os.path.splitext(cls)[1] in [".jpg", ".jpeg",".png"]: | |
| img_path = os.path.join(directory, cls) | |
| curImg = cv2.imread(img_path) | |
| Images.append(curImg) | |
| classnames.append(os.path.splitext(cls)[0]) | |
| # Load images for face recognition | |
| encodeListknown = [face_recognition.face_encodings(img)[0] for img in Images] | |
| ####### Section 3 ################### | |
| # Take picture using the camera | |
| img_file_buffer = st.camera_input("Take Your picture") | |
| # recognise the face in the uploaded image | |
| if img_file_buffer is not None: | |
| test_image = Image.open(img_file_buffer) | |
| image = np.asarray(test_image) | |
| image = image.copy() | |
| 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) | |
| faceMatchedflag = 0 | |
| # run looop to find match in encodeListknown list | |
| for encodeFace, faceLoc in zip(encodesCurFrame, facesCurFrame): | |
| # Assuming that encodeListknown is defined and populated in your code | |
| matches = face_recognition.compare_faces(encodeListknown, encodeFace) | |
| faceDis = face_recognition.face_distance(encodeListknown, encodeFace) | |
| matchIndex = np.argmin(faceDis) | |
| if matches[matchIndex]: | |
| name = classnames[matchIndex].upper() | |
| #st.write (name) | |
| # show the name on image to user | |
| 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) | |
| ########## update website | |
| # using Get Method | |
| # Construct the URL | |
| url = "https://fc11.glitch.me/submit?email=pm&message=faceReco&name=" | |
| url = url + name | |
| st.write("Constructed URL:", url) | |
| # Try to send the request and handle errors | |
| # try: | |
| # res = urllib.request.urlopen(url) | |
| # response = requests.post(url) | |
| # st.write("Data updated successfully.") | |
| # except urllib.error.URLError as e: | |
| # st.error(f"Failed to open URL: {e}") | |
| # except requests.exceptions.RequestException as e: | |
| # st.error(f"Request failed: {e}") | |
| url = "https://fc11.glitch.me/submit?email=pm&message=faceReco&name=" | |
| url = url + name | |
| st.write(url) | |
| res = urllib.request.urlopen(url) | |
| response = requests.post(url ) | |
| # # using post method | |
| # url = "https://aimljul24f.glitch.me/submit?email=pm&message=faceReco&name=" | |
| # url1 = "/save" | |
| # data = {'rollno': '99','name': name, 'email': 'p@g.com','pwd': '**' } | |
| # response = requests.post(url +url1 , data=data) | |
| # if response.status_code == 200: | |
| # st.success("Data updated on: " + "https://aimljul24f.glitch.me/") | |
| # else: | |
| # st.warning("Data not updated") | |
| ########### end update website | |
| faceMatchedflag = 1 | |
| st.image(image , use_column_width=True, output_format="PNG") | |
| if(faceMatchedflag == 0) : | |
| st.warning("No faces detected in the image.") |