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| 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] | |
| with gr.Blocks() as demo: | |
| gr.Markdown( | |
| """ | |
| # KBY-AI - Face Liveness Detecion | |
| We offer SDKs for face recognition, liveness detection(anti-spoofing) and ID card recognition. | |
| We also specialize in providing outsourcing services with a variety of technical stacks like AI(Computer Vision/Machine Learning), Mobile apps, and web apps. | |
| ##### KYC Verification Demo - https://github.com/kby-ai/KYC-Verification-Demo-Android | |
| ##### ID Capture Web Demo - https://id-document-recognition-react-alpha.vercel.app | |
| ##### Documentation - Help Center - https://docs.kby-ai.com | |
| """ | |
| ) | |
| with gr.TabItem("Face Liveness Detection"): | |
| gr.Markdown( | |
| """ | |
| ##### Docker Hub - https://hub.docker.com/r/kbyai/face-liveness-detection | |
| ```bash | |
| sudo docker pull kbyai/face-liveness-detection:latest | |
| sudo docker run -e LICENSE="xxxxx" -p 8080:8080 -p 9000:9000 kbyai/face-liveness-detection:latest | |
| ``` | |
| """ | |
| ) | |
| 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]) | |
| gr.HTML('<a href="https://api.visitorbadge.io/api/combined?path=https%3A%2F%2Fhuggingface.co%2Fspaces%2Fkby-ai%2FFaceLivenessDetection&countColor=%23263759"><img src="https://api.visitorbadge.io/api/combined?path=https%3A%2F%2Fhuggingface.co%2Fspaces%2Fkby-ai%2FFaceLivenessDetection&countColor=%23263759&label=VISITORS&countColor=%23263759" /></a>') | |
| demo.launch(server_name="0.0.0.0", server_port=7860) |