Create app.py

app.py

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+from PIL import Image
+import numpy as np
+import cv2
+import face_recognition
+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
+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)
+
+            # Display image with the overlay
+            st.image(image, use_column_width=True, output_format="PNG")
+            faceMatchedflag = 1
+
+    if faceMatchedflag == 0:
+        st.warning("No faces detected in the image.")