multiple face detection and recognition added

components/realtimeFaceDetection/RealtimeFaceDetection.tsx

@@ -8,6 +8,7 @@ import { Camera } from "lucide-react";
 import { useToast } from "@/hooks/use-toast";
 
 const MODEL_URL = "https://cdn.jsdelivr.net/npm/@vladmandic/face-api/model";
+const PADDING = 50; // Padding around face in pixels
 
 const RealtimeFaceDetection = () => {
   const webcamRef = useRef<Webcam>(null);
@@ -35,9 +36,42 @@ const RealtimeFaceDetection = () => {
     loadModels();
   }, [toast]);
 
+  const extractFaceWithPadding = (
+    video: HTMLVideoElement,
+    box: faceapi.Box
+  ): HTMLCanvasElement => {
+    const canvas = document.createElement("canvas");
+    const context = canvas.getContext("2d");
+
+    // Calculate padded dimensions
+    const x = Math.max(0, box.x - PADDING);
+    const y = Math.max(0, box.y - PADDING);
+    const width = Math.min(video.videoWidth - x, box.width + 2 * PADDING);
+    const height = Math.min(video.videoHeight - y, box.height + 2 * PADDING);
+
+    canvas.width = width;
+    canvas.height = height;
+
+    if (context) {
+      // Extract face region with padding
+      context.drawImage(
+        video,
+        x,
+        y,
+        width,
+        height, // Source coordinates
+        0,
+        0,
+        width,
+        height // Destination coordinates
+      );
+    }
+
+    return canvas;
+  };
+
   const detectFace = async () => {
-    if (!webcamRef.current || !webcamRef.current.video || !canvasRef.current)
-      return;
+    if (!webcamRef.current?.video || !canvasRef.current) return;
 
     const video = webcamRef.current.video;
     const canvas = canvasRef.current;
@@ -45,7 +79,6 @@ const RealtimeFaceDetection = () => {
 
     if (!context) return;
 
-    // Set canvas size to match video
     canvas.width = video.videoWidth;
     canvas.height = video.videoHeight;
     context.clearRect(0, 0, canvas.width, canvas.height); // Clear previous drawings
@@ -54,46 +87,28 @@ const RealtimeFaceDetection = () => {
     context.translate(canvas.width, 0); // Move the origin to the right side of the canvas
     context.scale(-1, 1); // Flip the context horizontally
 
-    // Detect face
+    // Detect all faces
     const detections = await faceapi
-      .detectSingleFace(video, new faceapi.TinyFaceDetectorOptions())
+      .detectAllFaces(video, new faceapi.TinyFaceDetectorOptions())
       .withFaceLandmarks()
-      .withFaceDescriptor();
+      .withFaceDescriptors();
 
-    if (detections) {
-      // Draw bounding box
-      const { x, y, width, height } = detections.detection.box;
-      context.strokeStyle = "red"; // Box color
-      context.lineWidth = 3;
-      context.strokeRect(x, y, width, height);
+    for (const detection of detections) {
+      // Draw box for visualization
+      const { box } = detection.detection;
+      context.strokeStyle = "#00FF00";
+      context.lineWidth = 2;
+      context.strokeRect(box.x, box.y, box.width, box.height);
 
-      // Capture the face as an image
-      const imageCanvas = document.createElement("canvas");
-      const imageContext = imageCanvas.getContext("2d");
-
-      if (imageContext) {
-        imageCanvas.width = video.videoWidth;
-        imageCanvas.height = video.videoHeight;
-
-        // Mirror the image context as well
-        imageContext.translate(imageCanvas.width, 0);
-        imageContext.scale(-1, 1);
-
-        imageContext.drawImage(
-          video,
-          0,
-          0,
-          imageCanvas.width,
-          imageCanvas.height
-        );
-
-        // Convert to Blob and send
-        imageCanvas.toBlob((blob) => {
-          if (blob) {
-            sendFaceDataToAPI(blob);
-          }
-        }, "image/jpeg");
-      }
+      // Extract face with padding and send to API
+      const faceCanvas = extractFaceWithPadding(video, box);
+      faceCanvas.toBlob(
+        (blob) => {
+          if (blob) sendFaceDataToAPI(blob);
+        },
+        "image/jpeg",
+        0.95
+      );
     }
   };
 
@@ -106,7 +121,7 @@ const RealtimeFaceDetection = () => {
         `${process.env.NEXT_PUBLIC_BASE_URL}/search`,
         {
           method: "POST",
-          body: formData, // Send multipart/form-data
+          body: formData,
         }
       );
 
@@ -125,13 +140,8 @@ const RealtimeFaceDetection = () => {
   const startDetection = () => {
     if (!isModelLoaded) return;
     setIsDetecting(true);
-    const interval = setInterval(detectFace, 1000);
-    setTimeout(() => {
-      clearInterval(interval);
-      setIsDetecting(false);
-    }, 100000); // Stops detection after 10 seconds
+    setInterval(detectFace, 300);
   };
-
   return (
     <div className="max-w-3xl mx-auto">
       <div className="relative">