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import { useState, useRef, useEffect } from "react";
import { useVLMContext } from "../context/useVLMContext";
import { drawBoundingBoxesOnCanvas } from "./BoxAnnotator";
const MODES = ["File"] as const;
type Mode = typeof MODES[number];
const EXAMPLE_VIDEO_URL = "/space/videos/1.mp4";
const EXAMPLE_PROMPT = "Detect each individual animated characters in the image. The characters are moving. For each character, output a JSON array of objects with fields. Each character should have its own ([x1, y1, x2, y2]) where coordinates are in pixel values. No coordinates should be the same. This should be used to draw a box using the points around the character. This is an example of two boxes, the format of this : [x1, y1, x2, y2], [x1, y1, x2, y2]";
function isImageFile(file: File) {
return file.type.startsWith("image/");
}
function isVideoFile(file: File) {
return file.type.startsWith("video/");
}
function denormalizeBox(box: number[], width: number, height: number) {
// If all values are between 0 and 1, treat as normalized
if (box.length === 4 && box.every(v => v >= 0 && v <= 1)) {
return [
box[0] * width,
box[1] * height,
box[2] * width,
box[3] * height
];
}
return box;
}
// Add this robust fallback parser near the top
function extractAllBoundingBoxes(output: string): { label: string, bbox_2d: number[] }[] {
// Try to parse as JSON first
try {
const parsed = JSON.parse(output);
if (Array.isArray(parsed)) {
const result: { label: string, bbox_2d: number[] }[] = [];
for (const obj of parsed) {
if (obj && obj.label && Array.isArray(obj.bbox_2d)) {
if (Array.isArray(obj.bbox_2d[0])) {
for (const arr of obj.bbox_2d) {
if (Array.isArray(arr) && arr.length === 4) {
result.push({ label: obj.label, bbox_2d: arr });
}
}
} else if (obj.bbox_2d.length === 4) {
result.push({ label: obj.label, bbox_2d: obj.bbox_2d });
}
}
}
if (result.length > 0) return result;
}
} catch (e) {}
// Fallback: extract all [x1, y1, x2, y2] arrays from the string
const boxRegex = /\[\s*([0-9.]+)\s*,\s*([0-9.]+)\s*,\s*([0-9.]+)\s*,\s*([0-9.]+)\s*\]/g;
const boxes: { label: string, bbox_2d: number[] }[] = [];
let match;
while ((match = boxRegex.exec(output)) !== null) {
const arr = [parseFloat(match[1]), parseFloat(match[2]), parseFloat(match[3]), parseFloat(match[4])];
boxes.push({ label: '', bbox_2d: arr });
}
return boxes;
}
export default function MultiSourceCaptioningView() {
const [mode, setMode] = useState<Mode>("File");
const [videoUrl] = useState<string>(EXAMPLE_VIDEO_URL);
const [prompt, setPrompt] = useState<string>(EXAMPLE_PROMPT);
const [processing, setProcessing] = useState(false);
const [error, setError] = useState<string | null>(null);
const [uploadedFile, setUploadedFile] = useState<File | null>(null);
const [uploadedUrl, setUploadedUrl] = useState<string>("");
const [videoProcessing, setVideoProcessing] = useState(false);
const [imageProcessed, setImageProcessed] = useState(false);
const [exampleProcessing, setExampleProcessing] = useState(false);
const [debugOutput, setDebugOutput] = useState<string>("");
const [canvasDims, setCanvasDims] = useState<{w:number,h:number}|null>(null);
const [videoDims, setVideoDims] = useState<{w:number,h:number}|null>(null);
const [inferenceStatus, setInferenceStatus] = useState<string>("");
const videoRef = useRef<HTMLVideoElement | null>(null);
const overlayVideoRef = useRef<HTMLVideoElement | null>(null);
const processingVideoRef = useRef<HTMLVideoElement | null>(null);
const canvasRef = useRef<HTMLCanvasElement | null>(null);
const imageRef = useRef<HTMLImageElement | null>(null);
const boxHistoryRef = useRef<any[]>([]);
const { isLoaded, isLoading, error: modelError, runInference } = useVLMContext();
// Add this useEffect for overlay video synchronization
useEffect(() => {
const main = videoRef.current;
const overlay = overlayVideoRef.current;
if (!main || !overlay) return;
// Sync play/pause
const onPlay = () => { if (overlay.paused) overlay.play(); };
const onPause = () => { if (!overlay.paused) overlay.pause(); };
// Sync seeking and time
const onSeekOrTime = () => {
if (Math.abs(main.currentTime - overlay.currentTime) > 0.05) {
overlay.currentTime = main.currentTime;
}
};
main.addEventListener('play', onPlay);
main.addEventListener('pause', onPause);
main.addEventListener('seeked', onSeekOrTime);
main.addEventListener('timeupdate', onSeekOrTime);
// Clean up
return () => {
main.removeEventListener('play', onPlay);
main.removeEventListener('pause', onPause);
main.removeEventListener('seeked', onSeekOrTime);
main.removeEventListener('timeupdate', onSeekOrTime);
};
}, [videoRef, overlayVideoRef, uploadedUrl, videoUrl, mode]);
useEffect(() => {
if ((mode === "File") && processingVideoRef.current) {
processingVideoRef.current.play().catch(() => {});
}
}, [mode, videoUrl, uploadedUrl]);
const processVideoFrame = async () => {
if (!processingVideoRef.current || !canvasRef.current) return;
const video = processingVideoRef.current;
const canvas = canvasRef.current;
if (video.paused || video.ended || video.videoWidth === 0) return;
canvas.width = video.videoWidth;
canvas.height = video.videoHeight;
const ctx = canvas.getContext("2d");
if (!ctx) return;
ctx.drawImage(video, 0, 0, canvas.width, canvas.height);
await runInference(video, prompt, (output: string) => {
setDebugOutput(output);
let boxes = extractAllBoundingBoxes(output);
// Box persistence logic (2 seconds)
const now = Date.now();
if (Array.isArray(boxes) && boxes.length > 0) {
boxHistoryRef.current = boxHistoryRef.current.filter((b: any) => now - b.timestamp < 2000);
boxHistoryRef.current.push(...boxes.map(box => ({ ...box, timestamp: now })));
}
// Draw all boxes from last 2 seconds
const boxHistory = boxHistoryRef.current.filter((b: any) => now - b.timestamp < 2000);
ctx.clearRect(0, 0, canvas.width, canvas.height);
if (boxHistory.length > 0) {
const scaleX = canvas.width / video.videoWidth;
const scaleY = canvas.height / video.videoHeight;
// Fix: Draw all boxes, even if bbox_2d is an array of arrays
const denormalizedBoxes: any[] = [];
for (const b of boxHistory) {
if (Array.isArray(b.bbox_2d) && Array.isArray(b.bbox_2d[0])) {
// Multiple boxes per label
for (const arr of b.bbox_2d) {
if (Array.isArray(arr) && arr.length === 4) {
denormalizedBoxes.push({
...b,
bbox_2d: denormalizeBox(arr, canvas.width, canvas.height)
});
}
}
} else if (Array.isArray(b.bbox_2d) && b.bbox_2d.length === 4) {
// Single box
denormalizedBoxes.push({
...b,
bbox_2d: denormalizeBox(b.bbox_2d, canvas.width, canvas.height)
});
}
}
drawBoundingBoxesOnCanvas(ctx, denormalizedBoxes, { color: "#FF00FF", lineWidth: 4, font: "20px Arial", scaleX, scaleY });
}
});
};
const handleFileChange = (e: React.ChangeEvent<HTMLInputElement>) => {
const file = e.target.files?.[0] || null;
setUploadedFile(file);
setUploadedUrl(file ? URL.createObjectURL(file) : "");
setError(null);
setImageProcessed(false);
setVideoProcessing(false);
setExampleProcessing(false);
};
// Webcam mode: process frames with setInterval
useEffect(() => {
if (mode !== "File" || !isLoaded || !uploadedFile || !isVideoFile(uploadedFile) || !videoProcessing) return;
let interval: ReturnType<typeof setInterval> | null = null;
interval = setInterval(() => {
processVideoFrame();
}, 1000);
return () => {
if (interval) clearInterval(interval);
};
}, [mode, isLoaded, prompt, runInference, uploadedFile, videoProcessing]);
// Example video mode: process frames with setInterval
useEffect(() => {
if (mode !== "File" || uploadedFile || !isLoaded || !exampleProcessing) return;
let interval: ReturnType<typeof setInterval> | null = null;
interval = setInterval(() => {
processVideoFrame();
}, 1000);
return () => {
if (interval) clearInterval(interval);
};
}, [mode, isLoaded, prompt, runInference, uploadedFile, exampleProcessing]);
// File mode: process uploaded image (only on button click)
const handleProcessImage = async () => {
if (!isLoaded || !uploadedFile || !isImageFile(uploadedFile) || !imageRef.current || !canvasRef.current) return;
const img = imageRef.current;
const canvas = canvasRef.current;
canvas.width = img.naturalWidth;
canvas.height = img.naturalHeight;
setCanvasDims({w:canvas.width,h:canvas.height});
setVideoDims({w:img.naturalWidth,h:img.naturalHeight});
const ctx = canvas.getContext("2d");
if (!ctx) return;
ctx.drawImage(img, 0, 0, canvas.width, canvas.height);
setProcessing(true);
setError(null);
setInferenceStatus("Running inference...");
await runInference(img, prompt, (output: string) => {
setDebugOutput(output);
setInferenceStatus("Inference complete.");
ctx.drawImage(img, 0, 0, canvas.width, canvas.height);
let boxes = extractAllBoundingBoxes(output);
console.log("Model output:", output);
console.log("Boxes after normalization:", boxes);
console.log("Canvas size:", canvas.width, canvas.height);
if (boxes.length > 0) {
const [x1, y1, x2, y2] = boxes[0].bbox_2d;
console.log("First box coords:", x1, y1, x2, y2);
}
if (boxes.length === 0) setInferenceStatus("No boxes detected or model output invalid.");
if (Array.isArray(boxes) && boxes.length > 0) {
const scaleX = canvas.width / img.naturalWidth;
const scaleY = canvas.height / img.naturalHeight;
drawBoundingBoxesOnCanvas(ctx, boxes, { scaleX, scaleY });
}
setImageProcessed(true);
});
setProcessing(false);
};
// File mode: process uploaded video frames (start/stop)
const handleToggleVideoProcessing = () => {
setVideoProcessing((prev) => !prev);
};
// Handle start/stop for example video processing
const handleToggleExampleProcessing = () => {
setExampleProcessing((prev) => !prev);
};
// Test draw box function
const handleTestDrawBox = () => {
if (!canvasRef.current) return;
const canvas = canvasRef.current;
const ctx = canvas.getContext("2d");
if (!ctx) return;
ctx.clearRect(0, 0, canvas.width, canvas.height);
ctx.strokeStyle = "#FF00FF";
ctx.lineWidth = 4;
ctx.strokeRect(40, 40, Math.max(40,canvas.width/4), Math.max(40,canvas.height/4));
ctx.font = "20px Arial";
ctx.fillStyle = "#FF00FF";
ctx.fillText("Test Box", 50, 35);
};
useEffect(() => {
const draw = () => {
const overlayVideo = overlayVideoRef.current;
const canvas = canvasRef.current;
if (!overlayVideo || !canvas) return;
if (overlayVideo.videoWidth === 0) return;
canvas.width = overlayVideo.videoWidth;
canvas.height = overlayVideo.videoHeight;
const ctx = canvas.getContext("2d");
if (!ctx) return;
ctx.clearRect(0, 0, canvas.width, canvas.height);
const now = Date.now();
const boxHistory = boxHistoryRef.current.filter((b: any) => now - b.timestamp < 2000);
if (boxHistory.length > 0) {
const scaleX = canvas.width / overlayVideo.videoWidth;
const scaleY = canvas.height / overlayVideo.videoHeight;
// Fix: Draw all boxes, even if bbox_2d is an array of arrays
const denormalizedBoxes: any[] = [];
for (const b of boxHistory) {
if (Array.isArray(b.bbox_2d) && Array.isArray(b.bbox_2d[0])) {
// Multiple boxes per label
for (const arr of b.bbox_2d) {
if (Array.isArray(arr) && arr.length === 4) {
denormalizedBoxes.push({
...b,
bbox_2d: denormalizeBox(arr, canvas.width, canvas.height)
});
}
}
} else if (Array.isArray(b.bbox_2d) && b.bbox_2d.length === 4) {
// Single box
denormalizedBoxes.push({
...b,
bbox_2d: denormalizeBox(b.bbox_2d, canvas.width, canvas.height)
});
}
}
drawBoundingBoxesOnCanvas(ctx, denormalizedBoxes, { color: "#FF00FF", lineWidth: 4, font: "20px Arial", scaleX, scaleY });
}
};
draw();
const interval = setInterval(draw, 100);
return () => clearInterval(interval);
}, [overlayVideoRef, canvasRef]);
return (
<div className="absolute inset-0 text-white">
<div className="fixed top-0 left-0 w-full bg-gray-900 text-white text-center py-2 z-50">
{isLoading ? "Loading model..." : isLoaded ? "Model loaded" : modelError ? `Model error: ${modelError}` : "Model not loaded"}
</div>
<div className="text-center text-sm text-blue-300 mt-2">{inferenceStatus}</div>
<div className="flex flex-col items-center justify-center h-full w-full">
{/* Mode Selector */}
<div className="mb-6">
<div className="flex space-x-4">
{MODES.map((m) => (
<button
key={m}
className={`px-6 py-2 rounded-lg font-semibold transition-all duration-200 ${
mode === m ? "bg-blue-600 text-white" : "bg-gray-700 text-gray-300 hover:bg-blue-500"
}`}
onClick={() => setMode(m)}
>
{m}
</button>
))}
</div>
</div>
{/* Mode Content */}
<div className="w-full max-w-2xl flex-1 flex flex-col items-center justify-center">
{mode === "File" && (
<div className="w-full text-center flex flex-col items-center">
<div className="mb-4 w-full max-w-xl">
<label className="block text-left mb-2 font-medium">Detection Prompt:</label>
<textarea
className="w-full p-2 rounded-lg text-black"
rows={3}
value={prompt}
onChange={(e) => setPrompt(e.target.value)}
/>
</div>
<div className="mb-4 w-full max-w-xl">
<input
type="file"
accept="image/*,video/*"
onChange={handleFileChange}
className="block w-full text-sm text-gray-300 file:mr-4 file:py-2 file:px-4 file:rounded-lg file:border-0 file:text-sm file:font-semibold file:bg-blue-600 file:text-white hover:file:bg-blue-700"
/>
</div>
{/* Show uploaded image */}
{uploadedFile && isImageFile(uploadedFile) && (
<div className="relative w-full max-w-xl">
<img
ref={imageRef}
src={uploadedUrl}
alt="Uploaded"
className="w-full rounded-lg shadow-lg mb-2"
style={{ background: "#222" }}
/>
<canvas
ref={canvasRef}
className="absolute top-0 left-0 w-full h-full pointer-events-none"
style={{ zIndex: 10, pointerEvents: "none" }}
/>
<button
className="mt-4 px-6 py-2 rounded-lg bg-blue-600 text-white font-semibold"
onClick={handleProcessImage}
disabled={processing}
>
{processing ? "Processing..." : imageProcessed ? "Reprocess Image" : "Process Image"}
</button>
</div>
)}
{/* Show uploaded video */}
{uploadedFile && isVideoFile(uploadedFile) && (
<div className="relative w-full max-w-xl">
{/* Visible overlay video for user */}
<video
ref={overlayVideoRef}
src={uploadedUrl}
controls
autoPlay
loop
muted
playsInline
className="w-full rounded-lg shadow-lg mb-2"
style={{ background: "#222" }}
/>
{/* Hidden processing video for FastVLM/canvas */}
<video
ref={processingVideoRef}
src={uploadedUrl}
autoPlay
loop
muted
playsInline
style={{ display: "none" }}
onLoadedData={e => { e.currentTarget.play().catch(() => {}); }}
/>
<canvas
ref={canvasRef}
className="absolute top-0 left-0 w-full h-full pointer-events-none"
style={{ zIndex: 20, pointerEvents: "none" }}
/>
<button
className="mt-4 px-6 py-2 rounded-lg bg-blue-600 text-white font-semibold"
onClick={handleToggleVideoProcessing}
>
{videoProcessing ? "Stop Processing" : "Start Processing"}
</button>
</div>
)}
{/* Show example video if no file uploaded */}
{!uploadedFile && (
<div className="relative w-full max-w-xl">
{/* Visible overlay video for user */}
<video
ref={overlayVideoRef}
src={EXAMPLE_VIDEO_URL}
controls
autoPlay
loop
muted
playsInline
className="w-full rounded-lg shadow-lg mb-2"
style={{ background: "#222" }}
/>
{/* Hidden processing video for FastVLM/canvas */}
<video
ref={processingVideoRef}
src={EXAMPLE_VIDEO_URL}
autoPlay
loop
muted
playsInline
style={{ display: "none" }}
onLoadedData={e => { e.currentTarget.play().catch(() => {}); }}
/>
<canvas
ref={canvasRef}
className="absolute top-0 left-0 w-full h-full pointer-events-none"
style={{ zIndex: 20, pointerEvents: "none" }}
/>
<button
className="mt-4 px-6 py-2 rounded-lg bg-blue-600 text-white font-semibold"
onClick={handleToggleExampleProcessing}
>
{exampleProcessing ? "Stop Processing" : "Start Processing"}
</button>
</div>
)}
{processing && <div className="text-blue-400 mt-2">Processing frame...</div>}
{error && <div className="text-red-400 mt-2">Error: {error}</div>}
<button
className="mt-4 px-6 py-2 rounded-lg bg-gray-600 text-white font-semibold"
onClick={handleTestDrawBox}
>
Test Draw Box
</button>
<div className="mt-2 p-2 bg-gray-800 rounded text-xs">
<div>Canvas: {canvasDims ? `${canvasDims.w}x${canvasDims.h}` : "-"} | Video: {videoDims ? `${videoDims.w}x${videoDims.h}` : "-"}</div>
<div>Raw Model Output:</div>
<pre className="overflow-x-auto max-h-32 whitespace-pre-wrap">{debugOutput}</pre>
</div>
</div>
)}
</div>
</div>
</div>
);
} |