import gradio as gr
import requests
import datadog_api_client
from PIL import Image
def check_liveness(frame):
    url = "http://127.0.0.1:8080/check_liveness"
    file = {'file': open(frame, 'rb')}
    r = requests.post(url=url, files=file)
    result = r.json().get('face_state').get('result')
    html = None
    faces = None
    if r.json().get('face_state').get('is_not_front') is not None:
        liveness_score = r.json().get('face_state').get('liveness_score')
        eye_closed = r.json().get('face_state').get('eye_closed')
        is_boundary_face = r.json().get('face_state').get('is_boundary_face')
        is_not_front = r.json().get('face_state').get('is_not_front')
        is_occluded = r.json().get('face_state').get('is_occluded')
        is_small = r.json().get('face_state').get('is_small')
        luminance = r.json().get('face_state').get('luminance')
        mouth_opened = r.json().get('face_state').get('mouth_opened')
        quality = r.json().get('face_state').get('quality')
        html = ("
"
                    ""
                        "| Face State"
                        " | Value"
                    " | 
"
                    ""
                        "| Result"
                        " | {result}"
                    " | 
"
                    ""
                        "| Liveness Score"
                        " | {liveness_score}"
                    " | 
"
                    ""
                        "| Quality"
                        " | {quality}"
                    " | 
"
                    ""
                        "| Luminance"
                        " | {luminance}"
                    " | 
"
                    ""
                        "| Is Small"
                        " | {is_small}"
                    " | 
"
                    ""
                        "| Is Boundary"
                        " | {is_boundary_face}"
                    " | 
"
                    ""
                        "| Is Not Front"
                        " | {is_not_front}"
                    " | 
"
                    ""
                        "| Face Occluded"
                        " | {is_occluded}"
                    " | 
"
                    ""
                        "| Eye Closed"
                        " | {eye_closed}"
                    " | 
"
                    ""
                        "| Mouth Opened"
                        " | {mouth_opened}"
                    " | 
"
                    "
".format(liveness_score=liveness_score, quality=quality, luminance=luminance, is_small=is_small, is_boundary_face=is_boundary_face,
                                      is_not_front=is_not_front, is_occluded=is_occluded, eye_closed=eye_closed, mouth_opened=mouth_opened, result=result))
    else:
        html = (""
            ""
                "| Face State"
                " | Value"
            " | 
"
            ""
                "| Result"
                " | {result}"
            " | 
"
            "
".format(result=result))
    try:
        image = Image.open(frame)        
        for face in r.json().get('faces'):
            x1 = face.get('x1')
            y1 = face.get('y1')
            x2 = face.get('x2')
            y2 = face.get('y2')
            if x1 < 0:
                x1 = 0
            if y1 < 0:
                y1 = 0
            if x2 >= image.width:
                x2 = image.width - 1
            if y2 >= image.height:
                y2 = image.height - 1
            face_image = image.crop((x1, y1, x2, y2))
            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)))
            if faces is None:
                faces = face_image
            else:
                new_image = Image.new('RGB',(faces.width + face_image.width + 10, 150), (80,80,80))
                new_image.paste(faces,(0,0))
                new_image.paste(face_image,(faces.width + 10, 0))
                faces = new_image.copy()
    except:
        pass
    return [faces, html]
def compare_face(frame1, frame2):
    url = "http://127.0.0.1:8081/compare_face"
    files = {'file1': open(frame1, 'rb'), 'file2': open(frame2, 'rb')}
    r = requests.post(url=url, files=files)
    html = None
    faces = None
    compare_result = r.json().get('compare_result')
    compare_similarity = r.json().get('compare_similarity')
    html = (""
                ""
                    "| Compare Result"
                    " | Value"
                " | 
"
                ""
                    "| Result"
                    " | {compare_result}"
                " | 
"
                ""
                    "| Similarity"
                    " | {compare_similarity}"
                " | 
"
                "
".format(compare_result=compare_result, compare_similarity=compare_similarity))
    try:
        image1 = Image.open(frame1)
        image2 = Image.open(frame2)
        face1 = None
        face2 = None
        if r.json().get('face1') is not None:
            face = r.json().get('face1')
            x1 = face.get('x1')
            y1 = face.get('y1')
            x2 = face.get('x2')
            y2 = face.get('y2')
            if x1 < 0:
                x1 = 0
            if y1 < 0:
                y1 = 0
            if x2 >= image1.width:
                x2 = image1.width - 1
            if y2 >= image1.height:
                y2 = image1.height - 1
            face1 = image1.crop((x1, y1, x2, y2))
            face_image_ratio = face1.width / float(face1.height)
            resized_w = int(face_image_ratio * 150)
            resized_h = 150
            face1 = face1.resize((int(resized_w), int(resized_h)))
        if r.json().get('face2') is not None:
            face = r.json().get('face2')
            x1 = face.get('x1')
            y1 = face.get('y1')
            x2 = face.get('x2')
            y2 = face.get('y2')
            if x1 < 0:
                x1 = 0
            if y1 < 0:
                y1 = 0
            if x2 >= image2.width:
                x2 = image2.width - 1
            if y2 >= image2.height:
                y2 = image2.height - 1
            face2 = image2.crop((x1, y1, x2, y2))
            face_image_ratio = face2.width / float(face2.height)
            resized_w = int(face_image_ratio * 150)
            resized_h = 150
            face2 = face2.resize((int(resized_w), int(resized_h)))
        if face1 is not None and face2 is not None:
            new_image = Image.new('RGB',(face1.width + face2.width + 10, 150), (80,80,80))
            new_image.paste(face1,(0,0))
            new_image.paste(face2,(face1.width + 10, 0))
            faces = new_image.copy()
        elif face1 is not None and face2 is None:
            new_image = Image.new('RGB',(face1.width + face1.width + 10, 150), (80,80,80))
            new_image.paste(face1,(0,0))
            faces = new_image.copy()
        elif face1 is None and face2 is not None:
            new_image = Image.new('RGB',(face2.width + face2.width + 10, 150), (80,80,80))
            new_image.paste(face2,(face2.width + 10, 0))
            faces = new_image.copy()
    except:
        pass
    return [faces, html]
def idcard_recognition(frame):
    url = "http://127.0.0.1:8082/idcard_recognition"
    files = {'file': open(frame, 'rb')}
    r = requests.post(url=url, files=files)
    html = None
    images = None
    mrz = None
    status = r.json().get('Status')
    table_value = ""
    if r.json().get('MRZ') is not None:
        mrz = r.json().get('MRZ')
    for key, value in r.json().items():
        if key == 'Status' or key == 'Images' or key == 'MRZ' or key == 'Position':
            continue
        mrz_value = ''
        if mrz is not None and mrz.get(key) is not None:
            mrz_value = mrz[key]
            del mrz[key]
        row_value = (""
                        "| {key}"
                        " | {value}"
                        " | {mrz_value}"
                    " | 
".format(key=key, value=value, mrz_value=mrz_value))
        table_value = table_value + row_value
    if mrz is not None:
        for key, value in mrz.items():
            if key == 'MRZ':
                value = value.replace('<', '<')
                value = value.replace(',', '')
            row_value = ("
"
                            "| {key}"
                            " | {value}"
                            " | {mrz_value}"
                        " | 
".format(key=key, value='', mrz_value=value))
            table_value = table_value + row_value
            
    html = (""
                ""
                    "| Field"
                    " | Value"
                    " | MRZ"
                " | 
"
                ""
                    "| Status"
                    " | {status}"
                    " | "
                " | 
"
                "{table_value}"
                "
".format(status=status, table_value=table_value))
    
    table_value = ""
    for key, value in r.json().items():
        if key == 'Images':
            for image_key, image_value in value.items():
                row_value = (""
                                "| {key}"
                                " | "
                            "![]() | 
".format(key=image_key, base64_image=image_value))
                table_value = table_value + row_value
    images = (""
                ""
                    "| Field"
                    " | Image"
                " | 
"
                "{table_value}"
                "
".format(table_value=table_value))
    
    return [html, images]
with gr.Blocks() as demo:
    gr.Markdown(
        """
    # KBY-AI Technology
    We offer SDKs for face recognition, liveness detection, and ID card recognition.
    """
    )
    with gr.TabItem("Face Liveness Detection"):
        with gr.Row():
            with gr.Column():
                live_image_input = gr.Image(type='filepath')
                gr.Examples(['live_examples/1.jpg', 'live_examples/2.jpg', 'live_examples/3.jpg', 'live_examples/4.jpg'], 
                            inputs=live_image_input)
                check_liveness_button = gr.Button("Check Liveness")
            with gr.Column():
                liveness_face_output = gr.Image(type="pil").style(height=150)
                livness_result_output = gr.HTML()
        
        check_liveness_button.click(check_liveness, inputs=live_image_input, outputs=[liveness_face_output, livness_result_output])
    with gr.TabItem("Face Recognition"):
        with gr.Row():
            with gr.Column():
                compare_face_input1 = gr.Image(type='filepath')
                gr.Examples(['face_examples/1.jpg', 'face_examples/3.jpg', 'face_examples/5.jpg', 'face_examples/7.jpg', 'face_examples/9.jpg'], 
                            inputs=compare_face_input1)
                compare_face_button = gr.Button("Compare Face")
            with gr.Column():
                compare_face_input2 = gr.Image(type='filepath')
                gr.Examples(['face_examples/2.jpg', 'face_examples/4.jpg', 'face_examples/6.jpg', 'face_examples/8.jpg', 'face_examples/10.jpg'], 
                            inputs=compare_face_input2)
            with gr.Column():
                compare_face_output = gr.Image(type="pil").style(height=150)
                compare_result_output = gr.HTML(label='Result')
        compare_face_button.click(compare_face, inputs=[compare_face_input1, compare_face_input2], outputs=[compare_face_output, compare_result_output])
    with gr.TabItem("ID Card Recognition"):
        with gr.Row():
            with gr.Column(scale=3):
                id_image_input = gr.Image(type='filepath')
                gr.Examples(['idcard_examples/1.jpg', 'idcard_examples/2.jpg', 'idcard_examples/3.jpg'], 
                            inputs=id_image_input)
                id_recognition_button = gr.Button("ID Card Recognition")
            with gr.Column(scale=5):
                id_result_output = gr.HTML()
        
            with gr.Column(scale=2):
                image_result_output = gr.HTML()
        id_recognition_button.click(idcard_recognition, inputs=id_image_input, outputs=[id_result_output, image_result_output])
demo.launch(server_name="0.0.0.0", server_port=9000)