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Face-Recognition-Opy
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import os
import gradio as gr
import requests
import json
import io
from gradio.components import Image
from PIL import Image as PILImage, ImageDraw, ImageFont  # This import may be needed if you're processing images

from PIL import Image

from PIL import Image
import io
import base64

def face_crop(image, face_rect):
    x = face_rect.get('x')
    y = face_rect.get('y')
    width = face_rect.get('width')
    height = face_rect.get('height')


    if x < 0:
        x = 0
    if y < 0:
        y = 0
    if x + width >= image.width:
        width = image.width - x
    if y + height >= image.height:
        height = image.height - y

    face_image = image.crop((x, y, x + width - 1, y + height - 1))
    face_image_ratio = face_image.width / float(face_image.height)
    resized_w = int(face_image_ratio * 150)
    resized_h = 150

    face_image = face_image.resize((int(resized_w), int(resized_h)))
    return face_image

def pil_image_to_base64(image, format="PNG"):
    """
    Converts a PIL.Image object to a Base64-encoded string.

    :param image: PIL.Image object
    :param format: Format to save the image, e.g., "PNG", "JPEG"
    :return: Base64-encoded string
    """
    # Save the image to a BytesIO buffer
    buffer = io.BytesIO()
    image.save(buffer, format=format)
    buffer.seek(0)  # Rewind the buffer

    # Convert the buffer's contents to a Base64 string
    base64_string = base64.b64encode(buffer.getvalue()).decode('utf-8')
    return base64_string

def compare_face(image1, image2, verifyThreshold):
    try:
        img_bytes1 = io.BytesIO()
        image1.save(img_bytes1, format="JPEG")
        img_bytes1.seek(0)
    except:
        return ["Failed to open image1", {"resultCode": "Failed to open image1"}]

    try:
        img_bytes2 = io.BytesIO()
        image2.save(img_bytes2, format="JPEG")
        img_bytes2.seek(0)
    except:
        return ["Failed to open image2", {"resultCode": "Failed to open image2"}]
    
    url = "http://127.0.0.1:8000/compare_face"
    files = {'image1': img_bytes1, 'image2': img_bytes2}
    result = requests.post(url=url, files=files)
    if result.ok:
        json_result = result.json()
        if json_result.get("resultCode") != "Ok":
            return [json_result.get("resultCode"), json_result]

        html = ""
        faces1 = json_result.get("faces1", {})
        faces2 = json_result.get("faces2", {})
        results = json_result.get("results", {})

        for result in results:
            score = result.get('score')
            face1_idx = result.get('face1')
            face2_idx = result.get('face2')

            face_image1 = face_crop(image1, faces1[face1_idx])
            face_value1 = ('<img src="data:image/png;base64,{base64_image}" style="width: 100px; height: auto; object-fit: contain;"/>').format(base64_image=pil_image_to_base64(face_image1, format="PNG"))

            face_image2 = face_crop(image2, faces2[face2_idx])
            face_value2 = ('<img src="data:image/png;base64,{base64_image}" style="width: 100px; height: auto; object-fit: contain;"/>').format(base64_image=pil_image_to_base64(face_image2, format="PNG"))

            match_icon = '<svg fill="red" width="19" height="32" viewBox="0 0 19 32"><path d="M0 13.92V10.2H19V13.92H0ZM0 21.64V17.92H19V21.64H0Z"></path><path d="M14.08 0H18.08L5.08 32H1.08L14.08 0Z"></path></svg>'
            if score > verifyThreshold:
                match_icon = '<svg fill="green" width="19" height="32" viewBox="0 0 19 32"><path d="M0 13.9202V10.2002H19V13.9202H0ZM0 21.6402V17.9202H19V21.6402H0Z"></path></svg>'

            item_value = ('<div style="align-items: center; gap: 10px; display: flex; flex-direction: column;">'
                            '<div style="display: flex; align-items: center; gap: 20px;">'
                            '{face_value1}'
                            '{match_icon}'
                            '{face_value2}'
                            '</div>'
                            '<div style="text-align: center; margin-top: 10px;">'
                            'Score: {score}'
                            '</div>'
                            '</div>'
            ).format(face_value1=face_value1, face_value2=face_value2, match_icon=match_icon, score=f"{score:.2f}")
            html += item_value
            html += '<hr style="border: 1px solid #C0C0C0; margin: 10px 0;"/>'

        return [html, json_result]
    else:
        return [result.text, {"resultCode": result.text}]


def detect_face(image):
    try:
        img_bytes = io.BytesIO()
        image.save(img_bytes, format="JPEG")
        img_bytes.seek(0)
    except:
        return ["Failed to open image", {"resultCode": "Failed to open image"}]
    
    url = "http://127.0.0.1:8000/detect_face"
    files = {'image': img_bytes}
    result = requests.post(url=url, files=files)
    if result.ok:
        json_result = result.json()

        html = ""
        resultCode = json_result.get("resultCode")
        if resultCode == "Ok":
            faces = json_result.get("result", {})

            for face in faces:
                face_rect = face.get("rect", {})
                angles = face.get("angles", {})
                age_gender = face.get("age_gender", {})
                emotion = face.get("emotion", {})
                attribute = face.get("attribute", {})

                face_image = face_crop(image, face_rect)
                face_value = ('<img src="data:image/png;base64,{base64_image}" style="width: 100px; height: auto; object-fit: contain;"/>').format(base64_image=pil_image_to_base64(face_image, format="PNG"))

                item_value = ('<div style="display: flex; justify-content: center; align-items: flex-start; margin: 10px;">'
                                '<div style="display: flex; align-items: flex-start; gap: 40px; ">'
                                '{face_value}'
                                    '<div style="display: flex; gap: 20px; border-left: 1px solid #C0C0C0; padding-left: 20px;">'
                                        '<div>'
                                            '<p><b>Age</b></p>'
                                            '<p><b>Gender</b></p>'
                                            '<p><b>Mask</b></p>'
                                            '<p><b>Left Eye</b></p>'
                                            '<p><b>Right Eye</b></p>'
                                            '<p><b>Yaw</b></p>'
                                            '<p><b>Roll</b></p>'
                                            '<p><b>Pitch</b></p>'
                                        '</div>'
                                        '<div>'
                                            '<p>{age}</p>'
                                            '<p>{gender}</p>'
                                            '<p>{masked}</p>'
                                            '<p>{left_eye}</p>'
                                            '<p>{right_eye}</p>'
                                            '<p>{yaw}</p>'
                                            '<p>{roll}</p>'
                                            '<p>{pitch}</p>'
                                        '</div>'
                                    '</div>'
                                    '<div style="display: flex; gap: 20px; border-left: 1px solid #C0C0C0; padding-left: 20px;">'
                                        '<div>'
                                            '<p><b>Neutral</b></p>'
                                            '<p><b>Happy</b></p>'
                                            '<p><b>Angry</b></p>'
                                            '<p><b>Surprised</b></p>'
                                            '<p><b>Disgusted</b></p>'
                                            '<p><b>Sad</b></p>'
                                            '<p><b>Scared</b></p>'
                                        '</div>'
                                        '<div>'
                                            '<p>{neutral}</p>'
                                            '<p>{happy}</p>'
                                            '<p>{angry}</p>'
                                            '<p>{surprised}</p>'
                                            '<p>{disgusted}</p>'
                                            '<p>{sad}</p>'
                                            '<p>{scared}</p>'
                                        '</div>'
                                    '</div>'
                                '</div></div>').format(face_value=face_value, 
                                    age=age_gender.get('age'), 
                                    gender="Female" if age_gender.get('gender') == 0 else "Male", 
                                    neutral=f"{emotion.get('neutral'):.2f}", 
                                    happy=f"{emotion.get('happy'):.2f}", 
                                    angry=f"{emotion.get('angry'):.2f}", 
                                    surprised=f"{emotion.get('surprised'):.2f}", 
                                    disgusted=f"{emotion.get('disgusted'):.2f}", 
                                    sad=f"{emotion.get('sad'):.2f}", 
                                    scared=f"{emotion.get('scared'):.2f}", 
                                    masked="Yes" if attribute.get('masked') == 1 else "No", 
                                    left_eye="Open" if attribute.get('left_eye_opened') == 1 else "Close", 
                                    right_eye="Open" if attribute.get('right_eye_opened') == 1 else "Close", 
                                    yaw=f"{angles.get('yaw'):.2f}", 
                                    roll=f"{angles.get('roll'):.2f}", 
                                    pitch=f"{angles.get('pitch'):.2f}", 
                                    )

                html += item_value
                html += '<hr style="border: 1px solid #C0C0C0; margin: 10px 0;"/>'
        else:
            html = "No face!"

        return [html, json_result]
    else:
        return [result.text, {"resultCode": result.text}]

with gr.Blocks() as demo:
    gr.Markdown(
      f"""
      <a href="https://recognito.vision" style="display: flex; align-items: center;">
        <img src="https://recognito.vision/wp-content/uploads/2024/03/Recognito-modified.png" style="width: 8%; margin-right: 15px;"/>
        <div>
          <p style="font-size: 32px; font-weight: bold; margin: 0;">Recognito</p>
          <p style="font-size: 18px; margin: 0;">www.recognito.vision</p>
        </div>
      </a>
      <p style="font-size: 20px; font-weight: bold;">📘 Product Documentation</p>
      <div style="display: flex; align-items: center;">          
        &emsp;&emsp;<a href="https://docs.recognito.vision" style="display: flex; align-items: center;"><img src="https://recognito.vision/wp-content/uploads/2024/05/book.png" style="width: 48px; margin-right: 5px;"/></a>
      </div>
      <p style="font-size: 20px; font-weight: bold;">🏠 Visit Recognito</p>
      <div style="display: flex; align-items: center;">
        &emsp;&emsp;<a href="https://recognito.vision" style="display: flex; align-items: center;"><img src="https://recognito.vision/wp-content/uploads/2024/03/recognito_64_cl.png" style="width: 32px; margin-right: 5px;"/></a>
        &nbsp;&nbsp;&nbsp;&nbsp;<a href="https://www.linkedin.com/company/recognito-vision" style="display: flex; align-items: center;"><img src="https://recognito.vision/wp-content/uploads/2024/03/linkedin_64_cl.png" style="width: 32px; margin-right: 5px;"/></a>
        &nbsp;&nbsp;&nbsp;&nbsp;<a href="https://huggingface.co/recognito" style="display: flex; align-items: center;"><img src="https://recognito.vision/wp-content/uploads/2024/03/hf_64_cl.png" style="width: 32px; margin-right: 5px;"/></a>
        &nbsp;&nbsp;&nbsp;&nbsp;<a href="https://github.com/recognito-vision" style="display: flex; align-items: center;"><img src="https://recognito.vision/wp-content/uploads/2024/03/github_64_cl.png" style="width: 32px; margin-right: 5px;"/></a>
        &nbsp;&nbsp;&nbsp;&nbsp;<a href="https://hub.docker.com/u/recognito" style="display: flex; align-items: center;"><img src="https://recognito.vision/wp-content/uploads/2024/03/docker_64_cl.png" style="width: 32px; margin-right: 5px;"/></a>
        &nbsp;&nbsp;&nbsp;&nbsp;<a href="https://www.youtube.com/@recognito-vision" style="display: flex; align-items: center;"><img src="https://recognito.vision/wp-content/uploads/2024/04/youtube_64_cl.png" style="width: 32px; margin-right: 5px;"/></a>
      </div>
      <p style="font-size: 20px; font-weight: bold;">🤝 Contact us for our on-premise ID Document Verification SDKs deployment</p>
      <div style="display: flex; align-items: center;">
        &emsp;&emsp;<a target="_blank" href="mailto:hello@recognito.vision"><img src="https://img.shields.io/badge/email-hassan@recognito.vision-blue.svg?logo=gmail " alt="www.recognito.vision"></a>
        &nbsp;&nbsp;&nbsp;&nbsp;<a target="_blank" href="https://wa.me/+14158003112"><img src="https://img.shields.io/badge/whatsapp-+14158003112-blue.svg?logo=whatsapp " alt="www.recognito.vision"></a>
        &nbsp;&nbsp;&nbsp;&nbsp;<a target="_blank" href="https://t.me/recognito_vision"><img src="https://img.shields.io/badge/telegram-@recognito__vision-blue.svg?logo=telegram " alt="www.recognito.vision"></a>
        &nbsp;&nbsp;&nbsp;&nbsp;<a target="_blank" href="https://join.slack.com/t/recognito-workspace/shared_invite/zt-2d4kscqgn-"><img src="https://img.shields.io/badge/slack-recognito__workspace-blue.svg?logo=slack " alt="www.recognito.vision"></a>
      </div>
      <br/>
      """
    )

    with gr.TabItem("Face Recognition"):
        with gr.Row():
            with gr.Column(scale=7):
                with gr.Row():
                    with gr.Column():
                        image_input1 = gr.Image(type='pil')
                        gr.Examples(['examples/1.webp', 'examples/2.webp', 'examples/3.webp', 'examples/4.webp'], 
                                    inputs=image_input1)
                    with gr.Column():
                        image_input2 = gr.Image(type='pil')
                        gr.Examples(['examples/5.webp', 'examples/6.webp', 'examples/7.webp', 'examples/8.webp'], 
                                    inputs=image_input2)
                verifyThreshold = gr.Slider(minimum=0, maximum=1, value=0.67, label="Verify Threshold")    
                face_recog_button = gr.Button("Face Recognition")
            with gr.Column(scale=3):
                with gr.TabItem("Output"):
                    recog_html_output = gr.HTML()
                with gr.TabItem("JSON"):
                    recog_json_output = gr.JSON()
    with gr.TabItem("Face Attribute"):
        with gr.Row():
            with gr.Column():
                image_input = gr.Image(type='pil')
                gr.Examples(['examples/11.webp', 'examples/12.webp', 'examples/13.webp', 'examples/14.webp'], 
                            inputs=image_input)
                face_attr_button = gr.Button("Face Attribute")
            with gr.Column():
                with gr.TabItem("Output"):
                    detect_html_output = gr.HTML()
                with gr.TabItem("JSON"):
                    detect_json_output = gr.JSON()


    face_recog_button.click(compare_face, inputs=[image_input1, image_input2, verifyThreshold], outputs=[recog_html_output, recog_json_output])
    face_attr_button.click(detect_face, inputs=[image_input], outputs=[detect_html_output, detect_json_output])

demo.launch(server_name="0.0.0.0", server_port=7860)