| 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 = ("<table>" | |
| "<tr>" | |
| "<th>Face State</th>" | |
| "<th>Value</th>" | |
| "</tr>" | |
| "<tr>" | |
| "<td>Result</td>" | |
| "<td>{result}</td>" | |
| "</tr>" | |
| "<tr>" | |
| "<td>Liveness Score</td>" | |
| "<td>{liveness_score}</td>" | |
| "</tr>" | |
| "<tr>" | |
| "<td>Quality</td>" | |
| "<td>{quality}</td>" | |
| "</tr>" | |
| "<tr>" | |
| "<td>Luminance</td>" | |
| "<td>{luminance}</td>" | |
| "</tr>" | |
| "<tr>" | |
| "<td>Is Small</td>" | |
| "<td>{is_small}</td>" | |
| "</tr>" | |
| "<tr>" | |
| "<td>Is Boundary</td>" | |
| "<td>{is_boundary_face}</td>" | |
| "</tr>" | |
| "<tr>" | |
| "<td>Is Not Front</td>" | |
| "<td>{is_not_front}</td>" | |
| "</tr>" | |
| "<tr>" | |
| "<td>Face Occluded</td>" | |
| "<td>{is_occluded}</td>" | |
| "</tr>" | |
| "<tr>" | |
| "<td>Eye Closed</td>" | |
| "<td>{eye_closed}</td>" | |
| "</tr>" | |
| "<tr>" | |
| "<td>Mouth Opened</td>" | |
| "<td>{mouth_opened}</td>" | |
| "</tr>" | |
| "</table>".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 = ("<table>" | |
| "<tr>" | |
| "<th>Face State</th>" | |
| "<th>Value</th>" | |
| "</tr>" | |
| "<tr>" | |
| "<td>Result</td>" | |
| "<td>{result}</td>" | |
| "</tr>" | |
| "</table>".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 = ("<table>" | |
| "<tr>" | |
| "<th>Compare Result</th>" | |
| "<th>Value</th>" | |
| "</tr>" | |
| "<tr>" | |
| "<td>Result</td>" | |
| "<td>{compare_result}</td>" | |
| "</tr>" | |
| "<tr>" | |
| "<td>Similarity</td>" | |
| "<td>{compare_similarity}</td>" | |
| "</tr>" | |
| "</table>".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 = ("<tr>" | |
| "<td>{key}</td>" | |
| "<td>{value}</td>" | |
| "<td>{mrz_value}</td>" | |
| "</tr>".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(',', '<p>') | |
| row_value = ("<tr>" | |
| "<td>{key}</td>" | |
| "<td>{value}</td>" | |
| "<td>{mrz_value}</td>" | |
| "</tr>".format(key=key, value='', mrz_value=value)) | |
| table_value = table_value + row_value | |
| html = ("<table>" | |
| "<tr>" | |
| "<th style=""width:20%"">Field</th>" | |
| "<th style=""width:40%"">Value</th>" | |
| "<th style=""width:40%"">MRZ</th>" | |
| "</tr>" | |
| "<tr>" | |
| "<td>Status</td>" | |
| "<td>{status}</td>" | |
| "<td></td>" | |
| "</tr>" | |
| "{table_value}" | |
| "</table>".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 = ("<tr>" | |
| "<td>{key}</td>" | |
| "<td><img src=""data:image/png;base64,{base64_image} width = '200' height= '100' /></td>" | |
| "</tr>".format(key=image_key, base64_image=image_value)) | |
| table_value = table_value + row_value | |
| images = ("<table>" | |
| "<tr>" | |
| "<th>Field</th>" | |
| "<th>Image</th>" | |
| "</tr>" | |
| "{table_value}" | |
| "</table>".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) |