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####### Section 1 ################### | |
from PIL import Image | |
import numpy as np | |
import cv2 | |
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': '[email protected]','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.") |