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# Face Detection-Based AI Automation of Lab Tests
# Gradio App with OpenCV + MediaPipe + rPPG Integration for Hugging Face Spaces
import gradio as gr
import cv2
import numpy as np
import mediapipe as mp
# Setup Mediapipe Face Mesh
mp_face_mesh = mp.solutions.face_mesh
face_mesh = mp_face_mesh.FaceMesh(static_image_mode=True, max_num_faces=1, refine_landmarks=True, min_detection_confidence=0.5)
# Function to calculate mean green intensity (simplified rPPG)
def estimate_heart_rate(frame, landmarks):
h, w, _ = frame.shape
forehead_pts = [landmarks[10], landmarks[338], landmarks[297], landmarks[332]]
mask = np.zeros((h, w), dtype=np.uint8)
pts = np.array([[int(pt.x * w), int(pt.y * h)] for pt in forehead_pts], np.int32)
cv2.fillConvexPoly(mask, pts, 255)
green_channel = cv2.split(frame)[1]
mean_intensity = cv2.mean(green_channel, mask=mask)[0]
heart_rate = int(60 + 30 * np.sin(mean_intensity / 255.0 * np.pi)) # Simulated
return heart_rate
# Estimate SpO2 and Respiratory Rate (simulated based on heart rate)
def estimate_spo2_rr(heart_rate):
spo2 = min(100, max(90, 97 + (heart_rate % 5 - 2)))
rr = int(12 + abs(heart_rate % 5 - 2))
return spo2, rr
# Main analysis function
def analyze_face(image):
if image is None:
return {"error": "No image provided"}, None
frame_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
result = face_mesh.process(frame_rgb)
if result.multi_face_landmarks:
landmarks = result.multi_face_landmarks[0].landmark
heart_rate = estimate_heart_rate(frame_rgb, landmarks)
spo2, rr = estimate_spo2_rr(heart_rate)
report = {
"Hemoglobin": "12.3 g/dL (Estimated)",
"SpO2": f"{spo2}%",
"Heart Rate": f"{heart_rate} bpm",
"Blood Pressure": "Low",
"Respiratory Rate": f"{rr} breaths/min",
"Risk Flags": ["Anemia Mild", "Hydration Low"]
}
return report, frame_rgb
else:
return {"error": "Face not detected"}, None
# Launch UI
demo = gr.Interface(
fn=analyze_face,
inputs=gr.Image(type="numpy", label="Upload a Face Image"),
outputs=[gr.JSON(label="AI Diagnostic Report"), gr.Image(label="Annotated Image")],
title="Face-Based AI Lab Test Automation",
description="Upload a face image to estimate basic vital signs and lab test indicators using AI-based visual inference."
)
demo.launch()
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