| 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;"> | |
|   <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> | |
| <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> | |
| <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> | |
| <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;"> | |
|   <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> | |
| <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> | |
| <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> | |
| <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> | |
| <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;"> Activation Success!</p>""") | |
| else: | |
| gr.Markdown("""<p style="text-align: left; font-size: 20px; color: red;"> 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(""" 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(""" 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) | |