Update gradio/app.py

gradio/app.py

@@ -1,271 +1,291 @@
-import sys
-sys.path.append('../')
-
-import os
-import gradio as gr
-import cv2
-import time
-import numpy as np
-from PIL import Image
-
-from engine.header import *
-
-file_path = os.path.abspath(__file__)
-gradio_path = os.path.dirname(file_path)
-root_path = os.path.dirname(gradio_path)
-
-version = get_version().decode('utf-8')
-print_info('\t <Recognito Face Recognition> \t version {}'.format(version))
-
-device_id = get_deviceid().decode('utf-8')
-print_info('\t <Hardware ID> \t\t {}'.format(device_id))
-
-g_activation_result = -1
-MATCH_THRESHOLD = 0.67
-
-css = """
-.example-image img{
-    display: flex; /* Use flexbox to align items */
-    justify-content: center; /* Center the image horizontally */
-    align-items: center; /* Center the image vertically */
-    height: 300px; /* Set the height of the container */
-    object-fit: contain; /* Preserve aspect ratio while fitting the image within the container */
-}
-
-.example-image{
-    display: flex; /* Use flexbox to align items */
-    justify-content: center; /* Center the image horizontally */
-    align-items: center; /* Center the image vertically */
-    height: 350px; /* Set the height of the container */
-    object-fit: contain; /* Preserve aspect ratio while fitting the image within the container */
-}
-
-.face-row {
-    display: flex;
-    justify-content: space-around; /* Distribute space evenly between elements */
-    align-items: center; /* Align items vertically */
-    width: 100%; /* Set the width of the row to 100% */
-}
-
-.face-image{
-    justify-content: center; /* Center the image horizontally */
-    align-items: center; /* Center the image vertically */
-    height: 160px; /* Set the height of the container */
-    width: 160px;
-    object-fit: contain; /* Preserve aspect ratio while fitting the image within the container */
-}
-
-.face-image img{
-    justify-content: center; /* Center the image horizontally */
-    align-items: center; /* Center the image vertically */
-    height: 160px; /* Set the height of the container */
-    object-fit: contain; /* Preserve aspect ratio while fitting the image within the container */
-}
-
-.markdown-success-container {
-    background-color: #F6FFED;
-    padding: 20px;
-    margin: 20px;
-    border-radius: 1px;
-    border: 2px solid green;
-    text-align: center;
-}
-
-.markdown-fail-container {
-    background-color: #FFF1F0;
-    padding: 20px;
-    margin: 20px;
-    border-radius: 1px;
-    border: 2px solid red;
-    text-align: center;
-}
-
-.block-background {
-    # background-color: #202020; /* Set your desired background color */
-    border-radius: 5px;
-}
-
-"""
-
-def activate_sdk():
-    online_key = os.environ.get("FR_LICENSE_KEY")
-    offline_key_path = os.path.join(root_path, "license.txt")
-    dict_path = os.path.join(root_path, "engine/bin")
-
-    ret = -1
-    if online_key is None:
-        print_warning("Recognition online license key not found!")
-    else:
-        print_info(f"FR_LICENSE_KEY: {online_key}")
-        ret = init_sdk(dict_path.encode('utf-8'), online_key.encode('utf-8'))
-
-    if ret == 0:
-        print_log("Successfully online init SDK!")
-    else:
-        print_error(f"Failed to online init SDK, Error code {ret}\n Trying offline init SDK...");
-        if os.path.exists(offline_key_path) is False:
-            print_warning("Recognition offline license key file not found!")
-            print_error(f"Falied to offline init SDK, Error code {ret}")
-            return ret
-        else:
-            ret = init_sdk_offline(dict_path.encode('utf-8'), offline_key_path.encode('utf-8'))
-            if ret == 0:
-                print_log("Successfully offline init SDK!")
-            else:
-                print_error(f"Falied to offline init SDK, Error code {ret}")
-                return ret
-                
-    return ret
-
-def compare_face_clicked(frame1, frame2, threshold):
-    global g_activation_result
-    if g_activation_result != 0:
-        gr.Warning("SDK Activation Failed!")
-        return None, None, None, None, None, None, None, None, None
-
-    try:
-        image1 = open(frame1, 'rb')
-        image2 = open(frame2, 'rb')
-    except:
-        raise gr.Error("Please select images files!")
-
-    image_mat1 = cv2.imdecode(np.frombuffer(image1.read(), np.uint8), cv2.IMREAD_COLOR)
-    image_mat2 = cv2.imdecode(np.frombuffer(image2.read(), np.uint8), cv2.IMREAD_COLOR)
-    start_time = time.time()
-    result, score, face_bboxes, face_features = compare_face(image_mat1, image_mat2, float(threshold))
-    end_time = time.time()
-    process_time = (end_time - start_time) * 1000
-
-    try:
-        image1 = Image.open(frame1)
-        image2 = Image.open(frame2)
-        images = [image1, image2]
-
-        face1 = Image.new('RGBA',(150, 150), (80,80,80,0))
-        face2 = Image.new('RGBA',(150, 150), (80,80,80,0))
-        faces = [face1, face2]
-
-        face_bboxes_result = []
-        if face_bboxes is not None:
-            for i, bbox in enumerate(face_bboxes):
-                x1 = bbox[0]
-                y1 = bbox[1]
-                x2 = bbox[2]
-                y2 = bbox[3]
-                if x1 < 0:
-                    x1 = 0
-                if y1 < 0:
-                    y1 = 0
-                if x2 >= images[i].width:
-                    x2 = images[i].width - 1
-                if y2 >= images[i].height:
-                    y2 = images[i].height - 1
-
-                face_bbox_str = f"x1: {x1}, y1: {y1}, x2: {x2}, y2: {y2}"
-                face_bboxes_result.append(face_bbox_str)
-
-                faces[i] = images[i].crop((x1, y1, x2, y2))
-                face_image_ratio = faces[i].width / float(faces[i].height)
-                resized_w = int(face_image_ratio * 150)
-                resized_h = 150
-
-                faces[i] = faces[i].resize((int(resized_w), int(resized_h)))
-    except:
-        pass
-        
-    matching_result = Image.open(os.path.join(gradio_path, "icons/blank.png"))
-    similarity_score = ""
-    if faces[0] is not None and faces[1] is not None:
-        if score is not None:
-            str_score = str("{:.4f}".format(score))
-            if result == "SAME PERSON":
-                matching_result = Image.open(os.path.join(gradio_path, "icons/same.png"))
-                similarity_score = f"""<br/><div class="markdown-success-container"><p style="text-align: center; font-size: 20px; color: green;">Similarity score: {str_score}</p></div>"""
-            else:
-                matching_result = Image.open(os.path.join(gradio_path, "icons/different.png"))
-                similarity_score = f"""<br/><div class="markdown-fail-container"><p style="text-align: center; font-size: 20px; color: red;">Similarity score: {str_score}</p></div>"""
-    
-    return faces[0], faces[1], matching_result, similarity_score, face_bboxes_result[0], face_bboxes_result[1], face_features[0], face_features[1], str(process_time)
-
-def launch_demo(activate_result):
-    with gr.Blocks(css=css) 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: 3%; margin-right: 15px;"/>
-            </a>
-            <div style="display: flex; align-items: center;justify-content: center;">
-                <p style="font-size: 36px; font-weight: bold;">Face Recognition {version}</p>
-            </div>
-            <p style="font-size: 20px; font-weight: bold;">🤝 Contact us for our on-premise Face Recognition, Liveness Detection SDKs deployment</p>
-            </div>
-            <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-hello@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-recognito-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-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-blue.svg?logo=slack " alt="www.recognito.vision"></a>
-            </div>
-            <br/>
-            <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.png" style="width: 24px; 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/linkedin64.png" style="width: 24px; 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/hf1_64.png" style="width: 24px; 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/github64.png" style="width: 24px; 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/docker64.png" style="width: 24px; margin-right: 5px;"/></a>
-            </div>
-            <br/>
-            """
-        )
-        
-        with gr.Group():
-            if activate_result == 0:
-                gr.Markdown("""<p style="text-align: left; font-size: 20px; color: green;">&emsp;Activation Success!</p>""")         
-            else:
-                gr.Markdown("""<p style="text-align: left; font-size: 20px; color: red;">&emsp;Activation Failed!</p>""") 
-                    
-            gr.Textbox(device_id, label="Hardware ID")
-
-        with gr.Row():
-            with gr.Column(scale=2):
-                with gr.Row():
-                    with gr.Column(scale=1):
-                        compare_face_input1 = gr.Image(label="Image1", type='filepath', elem_classes="example-image")
-                        gr.Examples([os.path.join(root_path,'examples/1.jpg'), 
-                                    os.path.join(root_path,'examples/2.jpg'), 
-                                    os.path.join(root_path,'examples/3.jpg'), 
-                                    os.path.join(root_path,'examples/4.jpg')], 
-                                    inputs=compare_face_input1)
-                    with gr.Column(scale=1):
-                        compare_face_input2 = gr.Image(label="Image2", type='filepath', elem_classes="example-image")
-                        gr.Examples([os.path.join(root_path,'examples/5.jpg'),
-                                    os.path.join(root_path,'examples/6.jpg'),
-                                    os.path.join(root_path,'examples/7.jpg'),
-                                    os.path.join(root_path,'examples/8.jpg')],
-                                    inputs=compare_face_input2)
-                        
-            with gr.Blocks():
-                with gr.Column(scale=1, min_width=400, elem_classes="block-background"):   
-                    txt_threshold = gr.Textbox(f"{MATCH_THRESHOLD}", label="Matching Threshold", interactive=True)
-                    compare_face_button = gr.Button("Compare Face", variant="primary", size="lg")
-                    with gr.Row(elem_classes="face-row"):
-                        face_output1 = gr.Image(value=os.path.join(gradio_path,'icons/face.jpg'), label="Face 1", scale=0, elem_classes="face-image")
-                        compare_result = gr.Image(value=os.path.join(gradio_path,'icons/blank.png'), min_width=30, scale=0, show_download_button=False, show_label=False)
-                        face_output2 = gr.Image(value=os.path.join(gradio_path,'icons/face.jpg'), label="Face 2", scale=0, elem_classes="face-image")
-                    similarity_markdown = gr.Markdown("")
-                    txt_speed = gr.Textbox(f"", label="Processing Time (ms)", interactive=False, visible=False)
-                    with gr.Group():
-                        gr.Markdown("""&nbsp;face1""")
-                        txt_bbox1 = gr.Textbox(f"", label="Rect", interactive=False)
-                        txt_feature1 = gr.Textbox(f"", label="Feature", interactive=False, max_lines=5)
-                    with gr.Group():
-                        gr.Markdown("""&nbsp;face2""")
-                        txt_bbox2 = gr.Textbox(f"", label="Rect", interactive=False)
-                        txt_feature2 = gr.Textbox(f"", label="Feature", interactive=False, max_lines=5)
-
-                    compare_face_button.click(compare_face_clicked, inputs=[compare_face_input1, compare_face_input2, txt_threshold], outputs=[face_output1, face_output2, compare_result, similarity_markdown, txt_bbox1, txt_bbox2, txt_feature1, txt_feature2, txt_speed])
-            
-    demo.launch(server_name="0.0.0.0", server_port=7860, show_api=False)
-
-if __name__ == '__main__':
-    g_activation_result = activate_sdk()
-    launch_demo(g_activation_result)
+import sys
+sys.path.append('../')
+
+import os
+import gradio as gr
+import cv2
+import time
+import numpy as np
+from PIL import Image
+
+from engine.header import *
+
+file_path = os.path.abspath(__file__)
+gradio_path = os.path.dirname(file_path)
+root_path = os.path.dirname(gradio_path)
+
+version = get_version().decode('utf-8')
+print_info('\t <Recognito Face Recognition> \t version {}'.format(version))
+
+device_id = get_deviceid().decode('utf-8')
+print_info('\t <Hardware ID> \t\t {}'.format(device_id))
+
+g_activation_result = -1
+MATCH_THRESHOLD = 0.67
+
+css = """
+.example-image img{
+    display: flex; /* Use flexbox to align items */
+    justify-content: center; /* Center the image horizontally */
+    align-items: center; /* Center the image vertically */
+    height: 300px; /* Set the height of the container */
+    object-fit: contain; /* Preserve aspect ratio while fitting the image within the container */
+}
+
+.example-image{
+    display: flex; /* Use flexbox to align items */
+    justify-content: center; /* Center the image horizontally */
+    align-items: center; /* Center the image vertically */
+    height: 350px; /* Set the height of the container */
+    object-fit: contain; /* Preserve aspect ratio while fitting the image within the container */
+}
+
+.face-row {
+    display: flex;
+    justify-content: space-around; /* Distribute space evenly between elements */
+    align-items: center; /* Align items vertically */
+    width: 100%; /* Set the width of the row to 100% */
+}
+
+.face-image{
+    justify-content: center; /* Center the image horizontally */
+    align-items: center; /* Center the image vertically */
+    height: 160px; /* Set the height of the container */
+    width: 160px;
+    object-fit: contain; /* Preserve aspect ratio while fitting the image within the container */
+}
+
+.face-image img{
+    justify-content: center; /* Center the image horizontally */
+    align-items: center; /* Center the image vertically */
+    height: 160px; /* Set the height of the container */
+    object-fit: contain; /* Preserve aspect ratio while fitting the image within the container */
+}
+
+.markdown-success-container {
+    background-color: #F6FFED;
+    padding: 20px;
+    margin: 20px;
+    border-radius: 1px;
+    border: 2px solid green;
+    text-align: center;
+}
+
+.markdown-fail-container {
+    background-color: #FFF1F0;
+    padding: 20px;
+    margin: 20px;
+    border-radius: 1px;
+    border: 2px solid red;
+    text-align: center;
+}
+
+.block-background {
+    # background-color: #202020; /* Set your desired background color */
+    border-radius: 5px;
+}
+
+"""
+
+def activate_sdk():
+    online_key = os.environ.get("FR_LICENSE_KEY")
+    offline_key_path = os.path.join(root_path, "license.txt")
+    dict_path = os.path.join(root_path, "engine/bin")
+
+    ret = -1
+    if online_key is None:
+        print_warning("Recognition online license key not found!")
+    else:
+        print_info(f"FR_LICENSE_KEY: {online_key}")
+        ret = init_sdk(dict_path.encode('utf-8'), online_key.encode('utf-8'))
+
+    if ret == 0:
+        print_log("Successfully online init SDK!")
+    else:
+        print_error(f"Failed to online init SDK, Error code {ret}\n Trying offline init SDK...");
+        if os.path.exists(offline_key_path) is False:
+            print_warning("Recognition offline license key file not found!")
+            print_error(f"Falied to offline init SDK, Error code {ret}")
+            return ret
+        else:
+            ret = init_sdk_offline(dict_path.encode('utf-8'), offline_key_path.encode('utf-8'))
+            if ret == 0:
+                print_log("Successfully offline init SDK!")
+            else:
+                print_error(f"Falied to offline init SDK, Error code {ret}")
+                return ret
+                
+    return ret
+
+def compare_face_clicked(frame1, frame2, threshold):
+    global g_activation_result
+    if g_activation_result != 0:
+        gr.Warning("SDK Activation Failed!")
+        return None, None, None, None, None, None, None, None, None
+
+    try:
+        image1 = open(frame1, 'rb')
+        image2 = open(frame2, 'rb')
+    except:
+        raise gr.Error("Please select images files!")
+
+    image_mat1 = cv2.imdecode(np.frombuffer(image1.read(), np.uint8), cv2.IMREAD_COLOR)
+    image_mat2 = cv2.imdecode(np.frombuffer(image2.read(), np.uint8), cv2.IMREAD_COLOR)
+    start_time = time.time()
+    result, score, face_bboxes, face_features = compare_face(image_mat1, image_mat2, float(threshold))
+    end_time = time.time()
+    process_time = (end_time - start_time) * 1000
+
+    try:
+        image1 = Image.open(frame1)
+        image2 = Image.open(frame2)
+        images = [image1, image2]
+
+        face1 = Image.new('RGBA',(150, 150), (80,80,80,0))
+        face2 = Image.new('RGBA',(150, 150), (80,80,80,0))
+        faces = [face1, face2]
+
+        face_bboxes_result = []
+        if face_bboxes is not None:
+            for i, bbox in enumerate(face_bboxes):
+                x1 = bbox[0]
+                y1 = bbox[1]
+                x2 = bbox[2]
+                y2 = bbox[3]
+                if x1 < 0:
+                    x1 = 0
+                if y1 < 0:
+                    y1 = 0
+                if x2 >= images[i].width:
+                    x2 = images[i].width - 1
+                if y2 >= images[i].height:
+                    y2 = images[i].height - 1
+
+                face_bbox_str = f"x1: {x1}, y1: {y1}, x2: {x2}, y2: {y2}"
+                face_bboxes_result.append(face_bbox_str)
+
+                faces[i] = images[i].crop((x1, y1, x2, y2))
+                face_image_ratio = faces[i].width / float(faces[i].height)
+                resized_w = int(face_image_ratio * 150)
+                resized_h = 150
+
+                faces[i] = faces[i].resize((int(resized_w), int(resized_h)))
+    except:
+        pass
+        
+    matching_result = Image.open(os.path.join(gradio_path, "icons/blank.png"))
+    similarity_score = ""
+    if faces[0] is not None and faces[1] is not None:
+        if score is not None:
+            str_score = str("{:.4f}".format(score))
+            if result == "SAME PERSON":
+                matching_result = Image.open(os.path.join(gradio_path, "icons/same.png"))
+                similarity_score = f"""<br/><div class="markdown-success-container"><p style="text-align: center; font-size: 20px; color: green;">Similarity score: {str_score}</p></div>"""
+            else:
+                matching_result = Image.open(os.path.join(gradio_path, "icons/different.png"))
+                similarity_score = f"""<br/><div class="markdown-fail-container"><p style="text-align: center; font-size: 20px; color: red;">Similarity score: {str_score}</p></div>"""
+    
+    return faces[0], faces[1], matching_result, similarity_score, face_bboxes_result[0], face_bboxes_result[1], face_features[0], face_features[1], str(process_time)
+
+def launch_demo(activate_result):
+    with gr.Blocks(css=css) 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: 3%; margin-right: 15px;"/>
+            </a>
+            <div style="display: flex; align-items: center;justify-content: center;">
+                <p style="font-size: 36px; font-weight: bold;">Face Recognition {version}</p>
+            </div>
+            <p style="font-size: 20px; font-weight: bold;">🤝 Contact us for our on-premise Face Recognition, Liveness Detection SDKs deployment</p>
+            </div>
+            <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-hello@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-recognito-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-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-blue.svg?logo=slack " alt="www.recognito.vision"></a>
+            </div>
+            <br/>
+            <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.png" style="width: 24px; 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/linkedin64.png" style="width: 24px; 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/hf1_64.png" style="width: 24px; 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/github64.png" style="width: 24px; 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/docker64.png" style="width: 24px; margin-right: 5px;"/></a>
+            </div>
+            <br/>
+            """
+        )
+        
+        with gr.Group():
+            if activate_result == 0:
+                gr.Markdown("""<p style="text-align: left; font-size: 20px; color: green;">&emsp;Activation Success!</p>""")         
+            else:
+                gr.Markdown("""<p style="text-align: left; font-size: 20px; color: red;">&emsp;Activation Failed!</p>""") 
+                    
+            gr.Textbox(device_id, label="Hardware ID")
+
+        with gr.Row():
+            with gr.Column(scale=2):
+                with gr.Row():
+                    with gr.Column(scale=1):
+                        compare_face_input1 = gr.Image(label="Image1", type='filepath', elem_classes="example-image")
+                        gr.Examples([os.path.join(root_path,'examples/1.jpg'), 
+                                    os.path.join(root_path,'examples/2.jpg'), 
+                                    os.path.join(root_path,'examples/3.jpg'), 
+                                    os.path.join(root_path,'examples/4.jpg')], 
+                                    inputs=compare_face_input1)
+                    with gr.Column(scale=1):
+                        compare_face_input2 = gr.Image(label="Image2", type='filepath', elem_classes="example-image")
+                        gr.Examples([os.path.join(root_path,'examples/5.jpg'),
+                                    os.path.join(root_path,'examples/6.jpg'),
+                                    os.path.join(root_path,'examples/7.jpg'),
+                                    os.path.join(root_path,'examples/8.jpg')],
+                                    inputs=compare_face_input2)
+                        
+            with gr.Blocks():
+                with gr.Column(scale=1, min_width=400, elem_classes="block-background"):   
+                    txt_threshold = gr.Textbox(f"{MATCH_THRESHOLD}", label="Matching Threshold", interactive=True)
+                    compare_face_button = gr.Button("Compare Face", variant="primary", size="lg")
+                    with gr.Row(elem_classes="face-row"):
+                        face_output1 = gr.Image(value=os.path.join(gradio_path,'icons/face.jpg'), label="Face 1", scale=0, elem_classes="face-image")
+                        compare_result = gr.Image(value=os.path.join(gradio_path,'icons/blank.png'), min_width=30, scale=0, show_download_button=False, show_label=False)
+                        face_output2 = gr.Image(value=os.path.join(gradio_path,'icons/face.jpg'), label="Face 2", scale=0, elem_classes="face-image")
+                    similarity_markdown = gr.Markdown("")
+                    txt_speed = gr.Textbox(f"", label="Processing Time (ms)", interactive=False, visible=False)
+                    with gr.Group():
+                        gr.Markdown("""&nbsp;face1""")
+                        txt_bbox1 = gr.Textbox(f"", label="Rect", interactive=False)
+                        txt_feature1 = gr.Textbox(f"", label="Feature", interactive=False, max_lines=5)
+                    with gr.Group():
+                        gr.Markdown("""&nbsp;face2""")
+                        txt_bbox2 = gr.Textbox(f"", label="Rect", interactive=False)
+                        txt_feature2 = gr.Textbox(f"", label="Feature", interactive=False, max_lines=5)
+
+                    compare_face_button.click(compare_face_clicked, inputs=[compare_face_input1, compare_face_input2, txt_threshold], outputs=[face_output1, face_output2, compare_result, similarity_markdown, txt_bbox1, txt_bbox2, txt_feature1, txt_feature2, txt_speed])
+            
+    demo.launch(server_name="0.0.0.0", server_port=7860, show_api=False)
+
+def compare_faces(img1: Image.Image, img2: Image.Image) -> str:
+    # Example placeholder logic — replace with your actual face comparison code
+    # You can use your FaceSDK logic here
+    if img1.size == img2.size:
+        return "Match"
+    else:
+        return "No match"
+    
+if __name__ == '__main__':
+    g_activation_result = activate_sdk()
+    # launch_demo(g_activation_result)
+    
+    # Create Gradio interface
+    iface = gr.Interface(
+        fn=compare_faces,
+        inputs=["image", "image"],
+        outputs="text",
+        title="Face Comparison API",
+        description="Upload two images to compare faces."
+    )
+    
+    iface.launch()
+