stack_overflow_users.py

import numpy as np
import gradio as gr

import aiohttp
import asyncio
import cv2
import dlib
import base64
import ssl


ssl._create_default_https_context = ssl._create_unverified_context


URL = "https://api.stackexchange.com/2.2/users?site=stackoverflow"
MAX_USERS = 10


def filter_profile_data(data):
    """
    Filter user profile data to get reputation, display name, profile link, and profile image
    of first 10 users based on reputation.

    :param data: array of dicts containing raw user profile information
    :return: array of dicts filtered user profile information
    """
    data = data["items"]
    data = data[: min(MAX_USERS, len(data))]
    keys_to_keep = ["reputation", "location", "display_name", "link", "profile_image"]
    filtered_data = []
    for raw_user in data:
        user = {}
        for key in keys_to_keep:
            user[key] = raw_user[key] if key in raw_user else None
        filtered_data.append(user)
    return filtered_data


async def fetch_stack_overflow_profiles(url):
    """
    Fetch user profiles from Stack Overflow API.

    :param url: URL of API to be called
    :return: Raw user profile data if response is successful else error message
    """
    async with aiohttp.ClientSession() as session:
        try:
            async with session.get(url, timeout=10) as response:
                if response.status == 200:
                    data = await response.json()
                    data = filter_profile_data(data)
                    return data
                else:
                    return f"Failed to retrieve Stack Overflow user data: Status Code {response.status}"
        except aiohttp.ClientError as e:
            return str(e)
        except asyncio.TimeoutError:
            return "User data request timed out"


async def download_profile_image(url):
    """
    Download profile image from given URL.

    :param url: URL of profile image
    :return: RGB decoded image if image can be downloaded else error message
    """
    async with aiohttp.ClientSession() as session:
        try:
            async with session.get(url, timeout=10) as response:
                if response.status == 200:
                    data = await response.read()
                    array = np.asarray(bytearray(data), dtype=np.uint8)
                    image = cv2.imdecode(array, 1)
                    return image
                else:
                    return f"Failed to retrieve user profile image: Status Code {response.status}"
        except aiohttp.ClientError as e:
            return f"Profile image could not be downloaded: {str(e)}"
        except asyncio.TimeoutError:
            return "User profile image request timed out"


def detect_face_in_image(image):
    """
    Detects whether a there is a face in the input image using dlib.

    :param image: Image to check for face
    :return: Image with bounding box highlighting face if face exists else original image
    :return: True if face exists in image else False
    """
    detector = dlib.get_frontal_face_detector()
    faces, _, _ = detector.run(image, 1, -0.5)
    for face in faces:
        cv2.rectangle(
            image,
            (face.left(), face.top()),
            (face.right(), face.bottom()),
            (0, 255, 0),
            4,
        )
    _, buffer = cv2.imencode(".jpg", image)
    image = base64.b64encode(buffer)
    return image, len(faces) > 0


def fetch_and_process_users():
    """
    Higher level function to fetch users and analyze their profile images.

    :return: HTML content displaying fetched user information and error messages as necessary
    """
    profiles = asyncio.run(fetch_stack_overflow_profiles(URL))
    if type(profiles) is str:
        return get_error_html(profiles)

    user_content = []

    for profile in profiles:
        image_url = profile["profile_image"]
        image = asyncio.run(download_profile_image(image_url)) if image_url else None

        if image is None:
            user_html = get_user_html(
                None, profile, "", "Image for this user could not be fetched!"
            )
            user_content.append(user_html)
            continue

        if type(image) is str:
            user_html = get_user_html(None, profile, "", image)
            user_content.append(user_html)
            continue

        image, face_exists = detect_face_in_image(image)
        face_message = (
            "Face detected and highlighted in the user profile image!"
            if face_exists
            else "No face detected in the user profile image!"
        )
        image = image.decode("utf-8")

        user_html = get_user_html(image, profile, face_message, None)
        user_content.append(user_html)

    return "".join(user_content)


def get_error_html(error_message):
    """
    Constructs an HTML template to display error message.

    :param error_message: Message to be displayed
    :return: HTML code with the error message
    """
    return f"""
        <div style='display: flex; flex-direction: column; align-items: center; margin-bottom: 5rem;'>
            <div style='text-align: center; font-size: 16px;'> 
                <strong style='font-size: 18px;'></strong> {error_message} Try generating again.
                <br>
            </div>
        </div>
        """


def get_user_html(image, profile, face_message, error_message):
    """
    Constructs an HTML template to display user information and error message.

    :param image: Base64 image to be displayed on the page
    :param profile: Profile information to be displayed
    :param face_message: Message that indicates whether face exists or not in the picture
    :param error_message: Error message to display in case image cannot be fetched
    :return: HTML code with the user information with a potential error message
    """
    if error_message is None:
        image_html = f"""
            <div style="margin-bottom: 1rem;">
                <img src="data:image/jpeg;base64,{image}" alt="Profile image" style="width: 100%; height: 100%; object-fit: cover;">
            </div>
            <span style="font-size: 16px; color: grey;">{face_message}</span>
        """
    else:
        image_html = f"""
            <div style="text-align: center; font-size: 16px; margin-bottom: 1rem;"> 
                <strong style="font-size: 18px;"></strong> {error_message} Try generating again.
                <br>
            </div>
        """

    user_html = f"""
        <div style="display: flex; flex-direction: column; align-items: center; margin-bottom: 5rem;">
           {image_html}
            <div style="text-align: center; font-size: 16px;"> 
                <strong style="font-size: 18px;">Name:</strong> {profile.get("display_name", "Not available")}
                <br>
                <strong style="font-size: 18px;">Reputation:</strong> {profile.get("reputation", "Not available")}
                <br>
                <strong style="font-size: 18px;">Location:</strong> {profile.get("location", "Not available")}
                <br>
                <a href="{profile.get("link", "")}" target="_blank" style="font-size: 16px; color: blue; text-decoration: none;">View Profile</a>
            </div>
        </div>
    """
    return user_html


def get_html_content():
    """
    Constructs the whole HTML template to be displayed to the user.

    :return: HTML code to display each user's information and error messages
    """
    html_content = fetch_and_process_users()
    return html_content


demo = gr.Interface(
    fn=get_html_content,
    inputs=[],
    outputs=gr.components.HTML(label="Stack Overflow User Profiles"),
    title="Stack Overflow User Profiles and Face Detection",
    css="footer{display:none !important}",
    allow_flagging="never",
)


if __name__ == "__main__":
    demo.launch()