Spaces:
Build error
Build error
File size: 2,337 Bytes
6e0c0e5 b452da4 6e0c0e5 95b885f c3ffcd4 6e0c0e5 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 |
from PIL import Image
import numpy as np
import cv2
import requests
import face_recognition
import os
import streamlit as st
p1 = "raavi.jpg"
p2 = "jivan.jpg"
st.title("Face Recognition ")
Images = []
classnames = []
# read images and train the face_recognition package
img1 = cv2.imread(p1)
Images.append(img1)
classnames.append("Ravi")
img2 = cv2.imread(p2)
Images.append(img2)
classnames.append("Jivan")
# Load images for face recognition
encodeListknown = [face_recognition.face_encodings(img)[0] for img in Images]
# take image from user
# Take picture using the camera
img_file_buffer = st.camera_input("Take a 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)
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
if not image.flags.writeable:
image.setflags(write=True)
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)
# display_image_with_overlay(image, name)
st.image(image , use_column_width=True, output_format="PNG")
faceMatchedflag = 1
if(faceMatchedflag == 0) :
st.warning("No faces detected in the image.")
|