Spaces:
Runtime error
Runtime error
File size: 3,089 Bytes
9403c50 |
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 68 69 70 71 72 73 74 75 |
import streamlit as st
from PIL import Image, ImageDraw
import face_recognition
import numpy as np
# Load known face encodings and names
ruthchild_image = face_recognition.load_image_file("picturesofknownpeople/ruthchild.jpg")
ruthchild_face_encoding = face_recognition.face_encodings(ruthchild_image)[0]
harryking_image = face_recognition.load_image_file("picturesofknownpeople/harryking.jpg")
harryking_face_encoding = face_recognition.face_encodings(harryking_image)[0]
barackobama_image = face_recognition.load_image_file("picturesofknownpeople/barack_obama.jpg")
barackobama_face_encoding = face_recognition.face_encodings(barackobama_image)[0]
michelleobama_image = face_recognition.load_image_file("picturesofknownpeople/michelle_obama.jpg")
michelleobama_face_encoding = face_recognition.face_encodings(michelleobama_image)[0]
biden_image = face_recognition.load_image_file("picturesofknownpeople/biden.jpg")
biden_face_encoding = face_recognition.face_encodings(biden_image)[0]
known_face_encodings = [
ruthchild_face_encoding,
harryking_face_encoding,
barackobama_face_encoding,
michelleobama_face_encoding,
biden_face_encoding
]
known_face_names = [
"ruthchild",
"harryking",
"barackobama",
"michelleobama",
"biden"
]
def main():
st.set_page_config(page_title="Insightly", page_icon="https://i.ibb.co/bX6GdqG/insightly-wbg.png")
st.sidebar.image("https://i.ibb.co/bX6GdqG/insightly-wbg.png", use_column_width=True)
st.title("Face Recognition with Streamlit")
uploaded_image = st.file_uploader("Upload an image", type=["jpg", "png", "jpeg"])
if uploaded_image is not None:
unknown_image = face_recognition.load_image_file(uploaded_image)
# Find faces in the uploaded image
face_locations = face_recognition.face_locations(unknown_image)
face_encodings = face_recognition.face_encodings(unknown_image, face_locations)
# Create a Pillow ImageDraw Draw instance to draw on the image
pil_image = Image.fromarray(unknown_image)
draw = ImageDraw.Draw(pil_image)
for (top, right, bottom, left), face_encoding in zip(face_locations, face_encodings):
matches = face_recognition.compare_faces(known_face_encodings, face_encoding)
name = "Unknown"
face_distances = face_recognition.face_distance(known_face_encodings, face_encoding)
best_match_index = np.argmin(face_distances)
if matches[best_match_index]:
name = known_face_names[best_match_index]
# Draw a box and label on the image
draw.rectangle(((left, top), (right, bottom)), outline=(0, 0, 255))
text_width, text_height = draw.textsize(name)
draw.rectangle(((left, bottom - text_height - 10), (right, bottom)), fill=(0, 0, 255), outline=(0, 0, 255))
draw.text((left + 6, bottom - text_height - 5), name, fill=(255, 255, 255, 255))
st.image(pil_image, caption="Processed Image", use_column_width=True)
if __name__ == "__main__":
main()
|