adds streamlit face-recognition example

examples/streamlit/streamlit-face-recognition/Dockerfile

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+FROM python:3.11-slim
+
+RUN apt-get update && apt install cmake g++ git -y \
+    && rm -rf /var/lib/apt/lists/*
+
+WORKDIR /app
+
+COPY requirements.txt /app/requirements.txt
+RUN pip install -r requirements.txt
+
+COPY . /app
+
+ENTRYPOINT ["streamlit", "run", "app.py", \
+            "--server.port=80", \
+            "--server.headless=true", \
+            "--server.address=0.0.0.0", \
+            "--browser.gatherUsageStats=false", \
+            "--server.enableStaticServing=true", \
+            "--server.fileWatcherType=none", \
+            # hide the Streamlit menu
+            "--client.toolbarMode=viewer"]

examples/streamlit/streamlit-face-recognition/README.md

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+# Streamlit face recognition
+
+An app that shows how to use `face_recognition`

examples/streamlit/streamlit-face-recognition/app.py

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+import streamlit as st
+import face_recognition
+from PIL import Image, ImageDraw
+import numpy as np
+
+
+def detect_faces(image):
+    # Convert the image to RGB (face_recognition requires RGB)
+    rgb_image = image.convert("RGB")
+
+    # Convert PIL Image to numpy array
+    np_image = np.array(rgb_image)
+
+    # Find all face locations and face encodings in the image
+    face_locations = face_recognition.face_locations(np_image)
+
+    # Create a copy of the image to draw on
+    image_with_faces = image.copy()
+    draw = ImageDraw.Draw(image_with_faces)
+
+    # Draw rectangles around detected faces
+    for face_location in face_locations:
+        top, right, bottom, left = face_location
+        draw.rectangle(((left, top), (right, bottom)), outline="red", width=2)
+
+    return image_with_faces, len(face_locations)
+
+
+st.title("Face Detection App")
+
+uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
+
+if uploaded_file is not None:
+    # Read the image file
+    image = Image.open(uploaded_file)
+
+    # Display the original image
+    st.image(image, caption="Original Image", use_column_width=True)
+
+    try:
+        # Detect faces
+        image_with_faces, face_count = detect_faces(image)
+
+        # Display the result
+        st.image(
+            image_with_faces,
+            caption=f"Detected Faces: {face_count}",
+            use_column_width=True,
+        )
+
+        if face_count == 0:
+            st.write("No faces detected in the image.")
+        elif face_count == 1:
+            st.write("1 face detected in the image.")
+        else:
+            st.write(f"{face_count} faces detected in the image.")
+    except Exception as e:
+        st.error(f"An error occurred during face detection: {str(e)}")
+        st.write(
+            "Please try uploading a different image or check if the face_recognition models are properly installed."
+        )

examples/streamlit/streamlit-face-recognition/requirements.txt

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+face-recognition
+git+https://github.com/ageitgey/face_recognition_models
+streamlit
+numpy
+Pillow