v1.0
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lejay
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/**
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* Room Photo Analyzer using OpenAI GPT-4 Vision
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* Analyzes room photos to extract dimensions, detect doors/windows, and suggest wardrobe placement
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*/
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import OpenAI from 'openai';
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// Lazy initialization to avoid errors when API key is not set
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let openaiClient = null;
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function getOpenAIClient() {
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if (!openaiClient) {
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if (!process.env.OPENAI_API_KEY) {
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throw new Error('OPENAI_API_KEY is not configured. Add it to server/.env');
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}
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openaiClient = new OpenAI({
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apiKey: process.env.OPENAI_API_KEY
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});
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}
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return openaiClient;
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}
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/**
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* Prompt for GPT-4 Vision to analyze room photos
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*/
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const ROOM_ANALYSIS_PROMPT = `You are a professional interior designer and architect specializing in custom wardrobe installations. Analyze this room photo with a STRONG FOCUS on the visible wall surfaces (parois) and ceiling (plafond).
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PRIORITY: Carefully examine every visible wall and the ceiling. Detect their exact colors, materials, and textures as they appear in the photo. This is critical for accurate 3D room reconstruction.
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Return a JSON object with the following structure:
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{
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"roomDimensions": {
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"widthM": <estimated width in meters, e.g., 4.2>,
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"lengthM": <estimated length/depth in meters, e.g., 3.8>,
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"heightM": <estimated ceiling height in meters, typically 2.4-2.7>
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},
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"walls": [
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{
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"side": "back" | "left" | "right",
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"visible": <boolean - is this wall clearly visible in the photo?>,
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"color": "<EXACT hex color code sampled from the wall surface, e.g., #f5f5f0>",
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"material": "paint" | "wallpaper" | "brick" | "wood_panel" | "concrete" | "plaster" | "stone" | "tile",
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"texture": "smooth" | "textured" | "patterned" | "rough" | "glossy",
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"hasWindow": <boolean>,
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"hasDoor": <boolean>,
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"surfaceArea": <approximate visible surface area percentage 0-100, accounting for windows/doors>
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}
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],
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"windows": [
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{
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"wall": "back" | "left" | "right",
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"xPercent": <horizontal position from left edge, 0-100>,
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"yPercent": <vertical position from floor, 0-100>,
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"widthPercent": <width as percentage of wall, e.g., 25>,
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"heightPercent": <height as percentage of wall, e.g., 40>,
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"type": "window" | "french_window" | "skylight" | "bay_window"
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}
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],
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"doors": [
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{
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"wall": "back" | "left" | "right",
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"xPercent": <horizontal position from left edge, 0-100>,
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"widthPercent": <width as percentage of wall, typically 15-25>,
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"heightPercent": <height as percentage of wall, typically 80-90>,
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"type": "door" | "double_door" | "opening" | "closet" | "sliding_door"
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}
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],
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"floor": {
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"color": "<exact hex color code>",
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"material": "wood" | "tile" | "carpet" | "concrete" | "laminate" | "vinyl" | "parquet"
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},
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"ceiling": {
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"visible": <boolean - is the ceiling visible in the photo?>,
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"color": "<EXACT hex color code detected from the ceiling surface>",
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"type": "flat" | "sloped" | "beamed" | "coffered" | "vaulted",
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"material": "paint" | "plaster" | "wood" | "concrete",
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"slopeAngleDeg": <angle in degrees if sloped, 0 for flat, null if not applicable>,
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"slopeDirection": "front_to_back" | "left_to_right" | null
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},
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"lighting": {
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"natural": "bright" | "moderate" | "dim",
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"windowSide": "left" | "right" | "back" | "front" | null
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},
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"suggestedWardrobeWall": "back" | "left" | "right",
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"suggestedWardrobePosition": {
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"xPercent": <start position from left, 0-100>,
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"widthPercent": <suggested width as percentage of wall, e.g., 50>,
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"reason": "<brief explanation of why this position is recommended>"
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},
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"roomType": "bedroom" | "living_room" | "hallway" | "dressing" | "other",
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"confidence": <confidence score 0-100>
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}
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IMPORTANT GUIDELINES FOR WALL AND CEILING DETECTION:
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- ALWAYS include all three walls (back, left, right). Set visible=false only if a wall is truly not visible at all.
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- Sample the EXACT hex color from the dominant area of each wall surface — do NOT default to #f5f5f0.
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- Pay close attention to paint color nuances: beige vs cream vs off-white vs warm grey etc.
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- Detect the wall material: painted plaster, wallpaper, exposed brick, wood paneling, etc.
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- For the ceiling: detect its actual color (it may not be pure white), its type, and material.
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- If the ceiling is sloped (mansarde/sous-pente), estimate the slope angle and direction.
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- Estimate dimensions based on standard furniture sizes if visible (beds, doors, windows).
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- Standard door height is ~2.1m, standard door width is ~0.8-0.9m.
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- Standard ceiling height is 2.4-2.7m in residential.
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- For wardrobe placement, prefer walls without windows/doors and with enough clear space.
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- Return ONLY valid JSON, no additional text.`;
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/**
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* Analyze a room photo using GPT-4 Vision
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* @param {string} imageBase64 - Base64 encoded image data
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* @param {string} mimeType - Image MIME type (image/jpeg, image/png, etc.)
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* @returns {Object} Room analysis result
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*/
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export async function analyzeRoomPhoto(imageBase64, mimeType = 'image/jpeg') {
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const openai = getOpenAIClient();
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try {
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const response = await openai.chat.completions.create({
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model: 'gpt-4o',
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messages: [
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{
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role: 'user',
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content: [
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{ type: 'text', text: ROOM_ANALYSIS_PROMPT },
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{
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type: 'image_url',
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image_url: {
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url: `data:${mimeType};base64,${imageBase64}`,
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detail: 'high'
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}
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}
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]
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}
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],
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max_tokens: 2000,
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response_format: { type: 'json_object' }
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});
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const content = response.choices[0]?.message?.content;
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if (!content) {
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throw new Error('No response from OpenAI');
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}
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const analysis = JSON.parse(content);
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// Validate required fields
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if (!analysis.roomDimensions || !analysis.suggestedWardrobeWall) {
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throw new Error('Incomplete room analysis');
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}
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return {
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success: true,
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analysis,
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tokensUsed: response.usage?.total_tokens || 0
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};
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} catch (error) {
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console.error('Room analysis error:', error);
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if (error.code === 'invalid_api_key') {
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throw new Error('Invalid OpenAI API key');
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}
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if (error.code === 'rate_limit_exceeded') {
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throw new Error('API rate limit exceeded. Please try again later.');
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}
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throw error;
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}
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}
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/**
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* Convert analysis to 3D room configuration for Three.js
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* @param {Object} analysis - Room analysis from GPT-4 Vision
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* @returns {Object} 3D room configuration
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*/
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export function analysisTo3DConfig(analysis) {
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const { roomDimensions, walls, windows, doors, floor, ceiling, suggestedWardrobeWall, suggestedWardrobePosition } = analysis;
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return {
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// Room dimensions in meters
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width: roomDimensions.widthM || 4,
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length: roomDimensions.lengthM || 4,
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height: roomDimensions.heightM || 2.5,
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// Wall configurations with material info
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walls: {
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back: (() => {
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const w = walls?.find(w => w.side === 'back');
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return w ? { color: w.color || '#f5f5f0', visible: w.visible !== false, material: w.material || 'paint', texture: w.texture || 'smooth' }
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: { color: '#f5f5f0', visible: true, material: 'paint', texture: 'smooth' };
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})(),
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left: (() => {
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const w = walls?.find(w => w.side === 'left');
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return w ? { color: w.color || '#f5f5f0', visible: w.visible !== false, material: w.material || 'paint', texture: w.texture || 'smooth' }
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: { color: '#f5f5f0', visible: true, material: 'paint', texture: 'smooth' };
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})(),
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right: (() => {
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const w = walls?.find(w => w.side === 'right');
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return w ? { color: w.color || '#f5f5f0', visible: w.visible !== false, material: w.material || 'paint', texture: w.texture || 'smooth' }
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: { color: '#f5f5f0', visible: true, material: 'paint', texture: 'smooth' };
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})()
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},
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// Windows for each wall
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windows: (windows || []).map(w => ({
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wall: w.wall,
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x: (w.xPercent || 50) / 100,
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y: (w.yPercent || 30) / 100,
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width: (w.widthPercent || 25) / 100,
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height: (w.heightPercent || 40) / 100,
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type: w.type || 'window'
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})),
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// Doors for each wall
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doors: (doors || []).map(d => ({
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wall: d.wall,
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x: (d.xPercent || 10) / 100,
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width: (d.widthPercent || 20) / 100,
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height: (d.heightPercent || 85) / 100,
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type: d.type || 'door'
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})),
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// Floor and ceiling
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floor: {
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color: floor?.color || '#c4a574',
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material: floor?.material || 'wood'
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},
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ceiling: {
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color: ceiling?.color || '#ffffff',
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type: ceiling?.type || 'flat',
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visible: ceiling?.visible !== false,
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material: ceiling?.material || 'paint',
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slopeAngleDeg: ceiling?.slopeAngleDeg || 0,
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slopeDirection: ceiling?.slopeDirection || null
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},
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// Wardrobe placement
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wardrobePlacement: {
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wall: suggestedWardrobeWall || 'back',
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xPercent: suggestedWardrobePosition?.xPercent || 25,
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widthPercent: suggestedWardrobePosition?.widthPercent || 50
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}
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};
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}
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export default { analyzeRoomPhoto, analysisTo3DConfig };
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