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| from PIL import Image | |
| import numpy as np | |
| import requests | |
| import os | |
| import cv2 | |
| import face_recognition | |
| import streamlit as st | |
| #p1 = "raavi.jpg" | |
| #p2 = "jivan.jpeg" | |
| # p3 = "sejal.jpeg" | |
| 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("Sirwan sir") | |
| # img3 = cv2.imread(p3) | |
| # Images.append(img3) | |
| # classnames.append("sejal") | |
| 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] | |
| # Take image from user | |
| 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) | |
| # Convert to NumPy array and create a writeable copy | |
| image = np.array(test_image) | |
| image = image.copy() # Create a writeable copy of the image array | |
| 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 | |
| # Loop to find match in encodeListknown | |
| for encodeFace, faceLoc in zip(encodesCurFrame, facesCurFrame): | |
| 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 the image | |
| y1, x2, y2, x1 = faceLoc | |
| y1, x2, y2, x1 = y1 * 4, x2 * 4, y2 * 4, x1 * 4 | |
| # Draw rectangle around the face | |
| cv2.rectangle(image, (x1, y1), (x2, y2), (0, 255, 0), 2) | |
| # Optionally draw name label below face (commented out for now) | |
| 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) | |
| faceMatchedflag = 1 | |
| # Display image with the overlay | |
| st.image(image, use_column_width=True, output_format="PNG") | |
| if faceMatchedflag == 0: | |
| st.warning("No faces detected in the image.") | |