This python script uses the face_recognition library to perform face recognition on an image. It can recognize faces of known individuals and label them in an unknown image. In this README, we'll provide instructions on how to use the code and set up the environment.
Before using this code, ensure that you have the necessary libraries installed. You can install them using pip:
!pip install face_recognitionMake sure you also have numpy, Pillow(PIL) and IPython installed in your Python environment.
- Clone this repository or create a new Python script.
- Add the images you want to use for recognition. The known faces should be stored in seperate image files, and the unknown image should be specified as "unknown.jpg" in the code.
- Replace the names and known face encodings in the code with the names and encodings of the individuals you want to recognize.
- Run the Python script. The code will perform face recognition on the unknown image and display the results.
The code is divided into the following sections:
Importing the required Python libraries, including face_recognition, numpy, Pillow, and IPython.display.
import face_recognition
import numpy as np
from PIL import Image, ImageDraw
from IPython.display import displayLoading known faces and their encodings from image files. You can add more known faces by extending the known_face_encodings and known_face_names lists.
face_1 = face_recognition.load_image_file("bill.jpg")
face_1_encoding = face_recognition.face_encodings(face_1)[0]
face_2 = face_recognition.load_image_file("elon.jpg")
face_2_encoding = face_recognition.face_encodings(face_2)[0]
face_3 = face_recognition.load_image_file("sundar.jpg")
face_3_encoding = face_recognition.face_encodings(face_3)[0]
known_face_encodings = [
face_1_encoding,
face_2_encoding,
face_3_encodings
]
known_face_names = [
"Bill Gates",
"Elon Musk",
"Sundar Pichai"
]Loading the image in which you want to recognize faces. Ensure this image is named "unknown.jpg".
unknown_image = face_recognition.load_image_file("unknown.jpg")Detecting faces in the unknown image, comparing their encodings with the known faces, and assigning names to recognized faces.
face_locations = face_recognition.face_locations(unknown_image)
face_encodings = face_recognition.face_encodings(unknown_image, face_locations)
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.rectangle(((left, top), (right, bottom)), outline=(0, 255, 255))
print(name)
text_width, text_height = draw.textsize(name)
draw.text((left + 6, bottom - text_height + 25), name, fill=(255, 255, 255, 255))Drawing rectangles around recognized faces and displaying the image with labels.
del draw
display(pil_image)
- The accuracy of face recognition depends on the quality and diversity of known face images. It may not be perfect in all cases.
- Ensure that the image file paths and names are correctly specified in the code.
Feel free to modify the code to suit your needs and add more individuals to the known faces list for recognition.
Enjoy using the face recognition script!
If you encounter any issues or have questions, feel free to reach out for assistance.
You can include this README.md file in your project's repository, and it will serve as a guide for users who want to use the provided face recognition code.