added single face detection and multiple face detection image

This commit is contained in:
Naufal 2023-09-24 23:53:12 +08:00
parent 68ba0a7d98
commit 3b1996fbad
8 changed files with 60 additions and 33 deletions

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# env folder
env/
faces/

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app.py
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@ -2,42 +2,31 @@ import face_recognition
import cv2 import cv2
import os import os
image_to_scan = 'image1.jpg' image_load = 'image1.jpg'
image_dataset_folder = 'faces' # image_data = 'faces/rika.png'
image_data = 'faces/rika.png'
# Load the image to scan # Load the images
image = face_recognition.load_image_file(image_to_scan) image_load_path = os.path.join(os.getcwd(), image_load)
image_data_path = os.path.join(os.getcwd(), image_data)
image_load = face_recognition.load_image_file(image_load_path)
image_data = face_recognition.load_image_file(image_data_path)
# Detect the faces in the image # Find the face locations and encodings in each image
face_locations = face_recognition.face_locations(image) image_load_face_locations = face_recognition.face_locations(image_load)
image_load_face_encodings = face_recognition.face_encodings(image_load, image_load_face_locations)
image_data_face_locations = face_recognition.face_locations(image_data)
image_data_face_encodings = face_recognition.face_encodings(image_data, image_data_face_locations)
# Draw a rectangle around each detected face using OpenCV # Compare the face encodings
for (top, right, bottom, left) in face_locations: matches = face_recognition.compare_faces(image_data_face_encodings, image_load_face_encodings[0])
cv2.rectangle(image, (left, top), (right, bottom), (0, 255, 0), 2)
# Display the image with the detected faces in a window # Draw boxes around the faces in the image_load image
cv2.imshow('Faces', image) for (top, right, bottom, left), match in zip(image_load_face_locations, matches):
if match:
cv2.rectangle(image_load, (left, top), (right, bottom), (0, 0, 255), 2)
# Display the image with the boxes around the matching faces
cv2.imshow('Image', image_load)
cv2.waitKey(0) cv2.waitKey(0)
# Load the images from the 'faces' folder and store them in a list
images = []
for filename in os.listdir(image_dataset_folder):
# if the file name ends with '.jpg' or '.png'
if filename.endswith('.jpg') or filename.endswith('.png'):
images.append(face_recognition.load_image_file(os.path.join(image_dataset_folder, filename)))
# Loop through the list of images and detect the faces in each image using face_recognition
for image in images:
# Detect the faces in the image
face_locations = face_recognition.face_locations(image)
# Draw a rectangle around each detected face using OpenCV
for (top, right, bottom, left) in face_locations:
cv2.rectangle(image, (left, top), (right, bottom), (0, 255, 0), 2)
# Display the images with the detected faces in a window
cv2.imshow('Faces', image)
cv2.waitKey(0)
# Wait for the user to press a key to exit the program
cv2.destroyAllWindows() cv2.destroyAllWindows()

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import face_recognition
import cv2
import os
image_load = 'image1.jpg'
image_data_folder = 'faces/'
# Load the images in the image_data_folder and save their face encodings in a list
image_dataset = []
for filename in os.listdir(image_data_folder):
image_data_path = os.path.join(os.getcwd(), image_data_folder, filename)
image_data = face_recognition.load_image_file(image_data_path)
image_data_encoding = face_recognition.face_encodings(image_data)[0]
image_dataset.append((filename, image_data_encoding))
# Load the image_load and find the face locations and encodings
image_load_path = os.path.join(os.getcwd(), image_load)
image_load = face_recognition.load_image_file(image_load_path)
image_load_face_locations = face_recognition.face_locations(image_load)
image_load_face_encodings = face_recognition.face_encodings(image_load, image_load_face_locations)
# Compare the face encodings in image_load to the face encodings in image_dataset
for (top, right, bottom, left), face_encoding in zip(image_load_face_locations, image_load_face_encodings):
matches = face_recognition.compare_faces([x[1] for x in image_dataset], face_encoding, tolerance=0.55)
if True in matches:
# Find the name of the matching face
name = image_dataset[matches.index(True)][0]
# Draw a box around the face and show the name on the top right of the box
cv2.rectangle(image_load, (left, top), (right, bottom), (0, 0, 255), 2)
cv2.putText(image_load, name, (right, top), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
# Display the image with the boxes and names around the matching faces
cv2.imshow('Image', image_load)
cv2.waitKey(0)
cv2.destroyAllWindows()

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