bundle.js

(function () {
    'use strict';

    /**
     * Camera management module for video stream handling
     */

    class CameraManager {
      constructor() {
        this.currentStream = null;
        this.availableCameras = [];
        this.selectedCameraId = null;
        this.videoElement = null;
        this.preferredConstraints = {
          width: {
            ideal: 480,
            min: 240
          },
          height: {
            ideal: 640,
            min: 320
          }
        };
        this.fallbackConstraints = {
          width: {
            ideal: 640,
            min: 320
          },
          height: {
            ideal: 480,
            min: 240
          }
        };
      }

      /**
       * Initialize camera manager and enumerate devices
       * @returns {Promise<void>}
       */
      async initialize() {
        try {
          // Request permission first
          await this.requestCameraPermission();

          // Enumerate cameras
          await this.enumerateCameras();
          console.log(`Found ${this.availableCameras.length} camera(s)`);
        } catch (error) {
          console.error('Failed to initialize camera manager:', error);
          throw new Error(`Camera initialization failed: ${error.message}`);
        }
      }

      /**
       * Request camera permission
       * @returns {Promise<void>}
       */
      async requestCameraPermission() {
        try {
          // Request basic camera access to get permissions
          const tempStream = await navigator.mediaDevices.getUserMedia({
            video: true
          });

          // Stop the temporary stream
          tempStream.getTracks().forEach(track => track.stop());
          console.log('Camera permission granted');
        } catch (error) {
          throw new Error('Camera permission denied or not available');
        }
      }

      /**
       * Enumerate available cameras
       * @returns {Promise<void>}
       */
      async enumerateCameras() {
        try {
          const devices = await navigator.mediaDevices.enumerateDevices();
          this.availableCameras = devices.filter(device => device.kind === 'videoinput').map((device, index) => ({
            id: device.deviceId,
            label: device.label || `Camera ${index + 1}`,
            groupId: device.groupId
          }));
          if (this.availableCameras.length === 0) {
            throw new Error('No cameras found');
          }

          // Select first camera by default
          this.selectedCameraId = this.availableCameras[0].id;
        } catch (error) {
          throw new Error(`Failed to enumerate cameras: ${error.message}`);
        }
      }

      /**
       * Get list of available cameras
       * @returns {Array}
       */
      getAvailableCameras() {
        return [...this.availableCameras];
      }

      /**
       * Start video stream with selected camera
       * @param {HTMLVideoElement} videoElement 
       * @param {string} cameraId 
       * @returns {Promise<Object>} - Stream info
       */
      async startCamera(videoElement) {
        let cameraId = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : null;
        try {
          // Stop current stream if exists
          if (this.currentStream) {
            this.stopCamera();
          }

          // Use provided camera or current selection
          const targetCameraId = cameraId || this.selectedCameraId;
          this.selectedCameraId = targetCameraId;

          // Store video element reference
          this.videoElement = videoElement;

          // Try preferred resolution first (480x640)
          let stream = null;
          let usedConstraints = null;
          try {
            const constraints = {
              video: {
                deviceId: {
                  exact: targetCameraId
                },
                ...this.preferredConstraints
              }
            };
            console.log('Trying preferred resolution (480x640)...');
            stream = await navigator.mediaDevices.getUserMedia(constraints);
            usedConstraints = this.preferredConstraints;
          } catch (error) {
            console.log('Preferred resolution failed, trying fallback (640x480)...');
            const constraints = {
              video: {
                deviceId: {
                  exact: targetCameraId
                },
                ...this.fallbackConstraints
              }
            };
            stream = await navigator.mediaDevices.getUserMedia(constraints);
            usedConstraints = this.fallbackConstraints;
          }

          // Set up video element
          videoElement.srcObject = stream;
          this.currentStream = stream;

          // Wait for video metadata to load
          await new Promise((resolve, reject) => {
            videoElement.addEventListener('loadedmetadata', resolve, {
              once: true
            });
            videoElement.addEventListener('error', reject, {
              once: true
            });

            // Timeout after 10 seconds
            setTimeout(() => reject(new Error('Video load timeout')), 10000);
          });

          // Get actual video dimensions
          const videoWidth = videoElement.videoWidth;
          const videoHeight = videoElement.videoHeight;
          console.log(`Video stream started: ${videoWidth}x${videoHeight}`);

          // Determine if camera should be rotated for display
          //const shouldRotateDisplay = ImageUtils.shouldRotateCamera(videoWidth, videoHeight);
          const shouldRotateDisplay = false;
          const isPortrait = videoHeight > videoWidth;

          // Get video wrapper for aspect ratio handling
          const videoWrapper = videoElement.closest('.video-wrapper');

          // Apply rotation CSS if needed
          if (shouldRotateDisplay) ; else {
            videoElement.classList.remove('rotate-90ccw');
          }

          // Apply portrait aspect ratio if video is vertical
          if (videoWrapper) {
            if (isPortrait) {
              videoWrapper.classList.add('portrait');
              console.log('Applied portrait aspect ratio (3:4)');
            } else {
              videoWrapper.classList.remove('portrait');
            }
          }
          return {
            width: videoWidth,
            height: videoHeight,
            rotated: shouldRotateDisplay,
            constraints: usedConstraints,
            cameraId: targetCameraId,
            cameraLabel: this.getCameraLabel(targetCameraId)
          };
        } catch (error) {
          console.error('Failed to start camera:', error);
          throw new Error(`Camera start failed: ${error.message}`);
        }
      }

      /**
       * Stop current video stream
       */
      stopCamera() {
        if (this.currentStream) {
          this.currentStream.getTracks().forEach(track => {
            track.stop();
            console.log(`Stopped ${track.kind} track`);
          });
          this.currentStream = null;
        }
        if (this.videoElement) {
          this.videoElement.srcObject = null;
          this.videoElement.classList.remove('rotate-90ccw');

          // Remove portrait class from wrapper
          const videoWrapper = this.videoElement.closest('.video-wrapper');
          if (videoWrapper) {
            videoWrapper.classList.remove('portrait');
          }
        }
        console.log('Camera stopped');
      }

      /**
       * Switch to a different camera
       * @param {string} cameraId 
       * @returns {Promise<Object>}
       */
      async switchCamera(cameraId) {
        if (!this.videoElement) {
          throw new Error('No video element available');
        }
        return await this.startCamera(this.videoElement, cameraId);
      }

      /**
       * Get label for camera ID
       * @param {string} cameraId 
       * @returns {string}
       */
      getCameraLabel(cameraId) {
        const camera = this.availableCameras.find(cam => cam.id === cameraId);
        return camera ? camera.label : 'Unknown Camera';
      }

      /**
       * Get current camera information
       * @returns {Object|null}
       */
      getCurrentCameraInfo() {
        if (!this.selectedCameraId || !this.videoElement) {
          return null;
        }
        return {
          id: this.selectedCameraId,
          label: this.getCameraLabel(this.selectedCameraId),
          width: this.videoElement.videoWidth,
          height: this.videoElement.videoHeight,
          isRotated: this.videoElement.classList.contains('rotate-90ccw')
        };
      }

      /**
       * Check if camera is currently active
       * @returns {boolean}
       */
      isActive() {
        return this.currentStream !== null && this.currentStream.getTracks().some(track => track.readyState === 'live');
      }

      /**
       * Get video element reference
       * @returns {HTMLVideoElement|null}
       */
      getVideoElement() {
        return this.videoElement;
      }

      /**
       * Set up camera selection dropdown
       * @param {HTMLSelectElement} selectElement 
       */
      populateCameraSelect(selectElement) {
        // Clear existing options
        selectElement.innerHTML = '';
        if (this.availableCameras.length === 0) {
          const option = document.createElement('option');
          option.value = '';
          option.textContent = 'No cameras available';
          option.disabled = true;
          selectElement.appendChild(option);
          return;
        }

        // Add camera options
        this.availableCameras.forEach(camera => {
          const option = document.createElement('option');
          option.value = camera.id;
          option.textContent = camera.label;
          selectElement.appendChild(option);
        });

        // Select current camera
        if (this.selectedCameraId) {
          selectElement.value = this.selectedCameraId;
        }
      }

      /**
       * Handle device change events (camera plugged/unplugged)
       * @param {Function} callback 
       */
      onDeviceChange(callback) {
        navigator.mediaDevices.addEventListener('devicechange', async () => {
          console.log('Camera devices changed');
          try {
            await this.enumerateCameras();
            callback(this.availableCameras);
          } catch (error) {
            console.error('Error handling device change:', error);
            callback([]);
          }
        });
      }

      /**
       * Dispose of resources
       */
      dispose() {
        this.stopCamera();
        this.availableCameras = [];
        this.selectedCameraId = null;
        this.videoElement = null;
        console.log('Camera manager disposed');
      }
    }

    /**
     * Image utilities for preprocessing and transformations
     */

    class ImageUtils {
      /**
       * Create a canvas element for image processing
       * @param {number} width 
       * @param {number} height 
       * @returns {HTMLCanvasElement}
       */
      static createCanvas(width, height) {
        const canvas = document.createElement('canvas');
        canvas.width = width;
        canvas.height = height;
        return canvas;
      }

      /**
       * Rotate image 90 degrees counterclockwise
       * @param {ImageData} imageData 
       * @returns {ImageData}
       */
      static rotateImage90CCW(imageData) {
        const {
          width,
          height,
          data
        } = imageData;
        const rotatedCanvas = this.createCanvas(height, width);
        const ctx = rotatedCanvas.getContext('2d');

        // Create temporary canvas with original image
        const tempCanvas = this.createCanvas(width, height);
        const tempCtx = tempCanvas.getContext('2d');
        tempCtx.putImageData(imageData, 0, 0);

        // Apply rotation transformation
        ctx.translate(height, 0);
        ctx.rotate(Math.PI / 2);
        ctx.drawImage(tempCanvas, 0, 0);
        return ctx.getImageData(0, 0, height, width);
      }

      /**
       * Resize image to target dimensions
       * @param {ImageData} imageData 
       * @param {number} targetWidth 
       * @param {number} targetHeight 
       * @returns {ImageData}
       */
      static resizeImage(imageData, targetWidth, targetHeight) {
        const {
          width,
          height
        } = imageData;

        // Create canvas with original image
        const sourceCanvas = this.createCanvas(width, height);
        const sourceCtx = sourceCanvas.getContext('2d');
        sourceCtx.putImageData(imageData, 0, 0);

        // Create target canvas
        const targetCanvas = this.createCanvas(targetWidth, targetHeight);
        const targetCtx = targetCanvas.getContext('2d');

        // Resize using canvas scaling
        targetCtx.drawImage(sourceCanvas, 0, 0, width, height, 0, 0, targetWidth, targetHeight);
        return targetCtx.getImageData(0, 0, targetWidth, targetHeight);
      }

      /**
       * Extract image data from video element
       * @param {HTMLVideoElement} video 
       * @returns {ImageData}
       */
      static getVideoFrame(video) {
        const canvas = this.createCanvas(video.videoWidth, video.videoHeight);
        const ctx = canvas.getContext('2d');
        ctx.drawImage(video, 0, 0);
        return ctx.getImageData(0, 0, video.videoWidth, video.videoHeight);
      }

      /**
       * Normalize image data for model inference
       * Uses ImageNet normalization values
       * @param {ImageData} imageData 
       * @returns {Float32Array}
       */
      static normalizeImageData(imageData) {
        const {
          width,
          height,
          data
        } = imageData;
        const normalizedData = new Float32Array(3 * width * height);

        // ImageNet normalization constants
        const mean = [0.485, 0.456, 0.406];
        const std = [0.229, 0.224, 0.225];
        let pixelIndex = 0;
        for (let i = 0; i < data.length; i += 4) {
          // Extract RGB values (skip alpha channel)
          const r = data[i] / 255.0;
          const g = data[i + 1] / 255.0;
          const b = data[i + 2] / 255.0;

          // Apply normalization: (pixel - mean) / std
          normalizedData[pixelIndex] = (r - mean[0]) / std[0]; // R channel
          normalizedData[pixelIndex + width * height] = (g - mean[1]) / std[1]; // G channel
          normalizedData[pixelIndex + 2 * width * height] = (b - mean[2]) / std[2]; // B channel

          pixelIndex++;
        }
        return normalizedData;
      }

      /**
       * Preprocess image for model inference
       * @param {HTMLVideoElement} video 
       * @param {number} targetWidth 
       * @param {number} targetHeight 
       * @param {boolean} shouldRotate - Whether to rotate 90 degrees CCW
       * @returns {Float32Array}
       */
      static preprocessVideoFrame(video, targetWidth, targetHeight) {
        try {
          // Extract frame from video
          let imageData = this.getVideoFrame(video);

          //console.log("In", imageData.width, imageData.height);
          imageData = this.cropCenter3to4(imageData);

          // Rotate if needed (for 640x480 -> 480x640)
          //if (shouldRotate) {
          //    imageData = this.rotateImage90CCW(imageData);
          //}

          // Resize to target dimensions
          if (imageData.width !== targetWidth || imageData.height !== targetHeight) {
            imageData = this.resizeImage(imageData, targetWidth, targetHeight);
          }

          // Normalize for model input
          return this.normalizeImageData(imageData);
        } catch (error) {
          console.error('Error preprocessing video frame:', error);
          throw error;
        }
      }

      /**
       * Create tensor from preprocessed data
       * @param {Float32Array} normalizedData 
       * @param {number} height 
       * @param {number} width 
       * @returns {Object} - Tensor-like object for ONNX
       */
      static createInputTensor(normalizedData, height, width) {
        return {
          data: normalizedData,
          dims: [1, 3, height, width],
          type: 'float32'
        };
      }

      /**
       * Process model output to create segmentation mask
       * @param {Float32Array} modelOutput 
       * @param {number} height 
       * @param {number} width 
       * @returns {Uint8Array} - Binary mask
       */
      static processModelOutput(modelOutput, height, width) {
        const mask = new Uint8Array(height * width);

        // Apply softmax and get argmax for each pixel
        for (let i = 0; i < height * width; i++) {
          const backgroundLogit = modelOutput[i];
          const cardLogit = modelOutput[i + height * width];

          // Simple argmax (card class = 1, background = 0)
          mask[i] = cardLogit > backgroundLogit ? 255 : 0;
        }
        return mask;
      }

      /**
       * Create overlay canvas with segmentation mask
       * @param {Uint8Array} mask 
       * @param {number} width 
       * @param {number} height 
       * @param {HTMLCanvasElement} targetCanvas 
       * @param {boolean} shouldRotate - Whether to rotate mask back
       */
      static drawSegmentationOverlay(mask, width, height, targetCanvas) {
        let shouldRotate = arguments.length > 4 && arguments[4] !== undefined ? arguments[4] : false;
        const ctx = targetCanvas.getContext('2d');

        // Create mask canvas
        const maskCanvas = this.createCanvas(width, height);
        const maskCtx = maskCanvas.getContext('2d');
        const maskImageData = maskCtx.createImageData(width, height);

        // Fill mask with cyan color where mask is active
        for (let i = 0; i < mask.length; i++) {
          const pixelIndex = i * 4;
          if (mask[i] > 0) {
            maskImageData.data[pixelIndex] = 0; // R
            maskImageData.data[pixelIndex + 1] = 255; // G (cyan)
            maskImageData.data[pixelIndex + 2] = 255; // B (cyan)
            maskImageData.data[pixelIndex + 3] = 128; // A (50% transparent)
          } else {
            maskImageData.data[pixelIndex + 3] = 0; // Fully transparent
          }
        }
        maskCtx.putImageData(maskImageData, 0, 0);

        // Clear target canvas
        ctx.clearRect(0, 0, targetCanvas.width, targetCanvas.height);
        shouldRotate = false;
        // Draw mask with rotation if needed
        if (shouldRotate) {
          ctx.save();
          ctx.translate(targetCanvas.width, 0);
          ctx.rotate(Math.PI / 2);
          ctx.drawImage(maskCanvas, 0, 0, height, width, 0, 0, targetCanvas.height, targetCanvas.width);
          ctx.restore();
        } else {
          ctx.drawImage(maskCanvas, 0, 0, width, height, 0, 0, targetCanvas.width, targetCanvas.height);
        }
      }

      /**
       * Check if camera orientation suggests it should be rotated
       * @param {number} width 
       * @param {number} height 
       * @returns {boolean}
       */
      static shouldRotateCamera(width, height) {
        return width > height; // Horizontal camera should be rotated to vertical
      }

      /**
       * Check if input image needs rotation for model (640x480 -> 480x640)
       * @param {number} width 
       * @param {number} height 
       * @returns {boolean}
       */
      static shouldRotateForModel(width, height) {
        return width === 640 && height === 480;
      }

      /**
       * Crop the center of an image to 3:4 aspect ratio (width:height)
       * Returns the largest possible crop that maintains the 3:4 proportion
       * @param {ImageData} imageData 
       * @returns {ImageData}
       */
      static cropCenter3to4(imageData) {
        const {
          width,
          height
        } = imageData;

        // Calculate the largest possible 3:4 crop
        let cropWidth, cropHeight;

        // Determine crop dimensions based on original aspect ratio
        if (width / height > 3 / 4) {
          // Image is wider than 3:4, crop width
          cropHeight = height;
          cropWidth = Math.floor(height * 3 / 4);
        } else {
          // Image is taller than 3:4, crop height
          cropWidth = width;
          cropHeight = Math.floor(width * 4 / 3);
        }

        // Calculate crop position (center the crop)
        const startX = Math.floor((width - cropWidth) / 2);
        const startY = Math.floor((height - cropHeight) / 2);

        // Create source canvas
        const sourceCanvas = this.createCanvas(width, height);
        const sourceCtx = sourceCanvas.getContext('2d');
        sourceCtx.putImageData(imageData, 0, 0);

        // Create target canvas for cropped image
        const targetCanvas = this.createCanvas(cropWidth, cropHeight);
        const targetCtx = targetCanvas.getContext('2d');

        // Draw the cropped portion
        targetCtx.drawImage(sourceCanvas, startX, startY, cropWidth, cropHeight,
        // Source rectangle
        0, 0, cropWidth, cropHeight // Destination rectangle
        );
        return targetCtx.getImageData(0, 0, cropWidth, cropHeight);
      }
    }

    /**
     * Model inference module using ONNX Runtime Web
     */

    class ModelInference {
      constructor() {
        this.session = null;
        this.isModelLoaded = false;
        this.isInferring = false;
        this.modelPath = 'models/card_segmentation_fp16.onnx';

        // Model specifications
        this.inputHeight = 320;
        this.inputWidth = 240;
        this.numClasses = 2;

        // GPU acceleration info
        this.accelerationInfo = {
          activeProvider: 'unknown',
          availableProviders: [],
          gpuInfo: null,
          supportsWebGL: false,
          supportsWebGPU: false
        };

        // Performance tracking
        this.inferenceStats = {
          totalInferences: 0,
          totalTime: 0,
          averageTime: 0,
          lastInferenceTime: 0
        };
      }

      /**
       * Initialize ONNX Runtime and load the model with GPU acceleration
       * @returns {Promise<boolean>}
       */
      async initialize() {
        try {
          console.log('Initializing ONNX Runtime with GPU acceleration...');

          // Configure ONNX Runtime
          ort.env.wasm.wasmPaths = 'https://cdn.jsdelivr.net/npm/onnxruntime-web@1.22.0/dist/';
          ort.env.wasm.numThreads = 1; // Single thread for stability

          // Detect GPU capabilities
          await this.detectGPUCapabilities();

          // Determine optimal execution providers
          const executionProviders = this.getOptimalExecutionProviders();
          console.log('Attempting to load model with providers:', executionProviders);
          console.log(`Loading model from: ${this.modelPath}`);

          // Try to load model with optimal providers
          this.session = await this.loadModelWithFallback(executionProviders);
          console.log(`Model loaded successfully with provider: ${this.accelerationInfo.activeProvider}`);
          this.isModelLoaded = true;

          // Log model and acceleration information
          this.logModelInfo();
          this.logAccelerationInfo();
          return true;
        } catch (error) {
          console.error('Failed to initialize model:', error);
          this.isModelLoaded = false;
          throw new Error(`Model initialization failed: ${error.message}`);
        }
      }

      /**
       * Detect GPU capabilities and available acceleration
       */
      async detectGPUCapabilities() {
        console.log('Detecting GPU capabilities...');

        // Check WebGL support
        this.accelerationInfo.supportsWebGL = this.checkWebGLSupport();

        // Check WebGPU support
        this.accelerationInfo.supportsWebGPU = await this.checkWebGPUSupport();

        // Get GPU info if available
        if (this.accelerationInfo.supportsWebGL) {
          this.accelerationInfo.gpuInfo = this.getWebGLInfo();
        }
        console.log('GPU Capabilities:', {
          WebGL: this.accelerationInfo.supportsWebGL,
          WebGPU: this.accelerationInfo.supportsWebGPU,
          GPU: this.accelerationInfo.gpuInfo
        });
      }

      /**
       * Check WebGL support
       * @returns {boolean}
       */
      checkWebGLSupport() {
        try {
          const canvas = document.createElement('canvas');
          const gl = canvas.getContext('webgl') || canvas.getContext('experimental-webgl');
          return !!gl;
        } catch (error) {
          console.warn('WebGL check failed:', error);
          return false;
        }
      }

      /**
       * Check WebGPU support
       * @returns {Promise<boolean>}
       */
      async checkWebGPUSupport() {
        try {
          if (!navigator.gpu) {
            return false;
          }
          const adapter = await navigator.gpu.requestAdapter();
          return !!adapter;
        } catch (error) {
          console.warn('WebGPU check failed:', error);
          return false;
        }
      }

      /**
       * Get WebGL renderer information
       * @returns {Object|null}
       */
      getWebGLInfo() {
        try {
          const canvas = document.createElement('canvas');
          const gl = canvas.getContext('webgl') || canvas.getContext('experimental-webgl');
          if (!gl) return null;
          const debugInfo = gl.getExtension('WEBGL_debug_renderer_info');
          return {
            vendor: debugInfo ? gl.getParameter(debugInfo.UNMASKED_VENDOR_WEBGL) : gl.getParameter(gl.VENDOR),
            renderer: debugInfo ? gl.getParameter(debugInfo.UNMASKED_RENDERER_WEBGL) : gl.getParameter(gl.RENDERER),
            version: gl.getParameter(gl.VERSION),
            shadingLanguageVersion: gl.getParameter(gl.SHADING_LANGUAGE_VERSION)
          };
        } catch (error) {
          console.warn('Failed to get WebGL info:', error);
          return null;
        }
      }

      /**
       * Determine optimal execution providers based on capabilities
       * @returns {Array<string>}
       */
      getOptimalExecutionProviders() {
        const providers = [];

        // Prioritize WebGPU first for best performance
        if (this.accelerationInfo.supportsWebGPU) {
          providers.push('webgpu');
          this.accelerationInfo.availableProviders.push('webgpu');
        }

        // Fall back to WebGL if WebGPU is not available or fails
        if (this.accelerationInfo.supportsWebGL) {
          providers.push('webgl');
          this.accelerationInfo.availableProviders.push('webgl');
        }

        // Always add WASM as final fallback
        providers.push('wasm');
        this.accelerationInfo.availableProviders.push('wasm');
        return providers;
      }

      /**
       * Load model with fallback mechanism
       * @param {Array<string>} executionProviders 
       * @returns {Promise<InferenceSession>}
       */
      async loadModelWithFallback(executionProviders) {
        const baseOptions = {
          enableMemPattern: false,
          enableCpuMemArena: false,
          graphOptimizationLevel: 'all'
        };

        // Try each provider in order
        for (const provider of executionProviders) {
          try {
            console.log(`Attempting to load model with ${provider} provider...`);
            const options = {
              ...baseOptions,
              executionProviders: [provider]
            };
            const session = await ort.InferenceSession.create(this.modelPath, options);
            this.accelerationInfo.activeProvider = provider;
            console.log(`✓ Successfully loaded with ${provider} provider`);
            return session;
          } catch (error) {
            const errorMsg = error.message;

            // Log specific information for operator compatibility issues
            if (errorMsg.includes('cannot resolve operator')) {
              var _errorMsg$match;
              const operatorName = ((_errorMsg$match = errorMsg.match(/operator '(\w+)'/)) === null || _errorMsg$match === void 0 ? void 0 : _errorMsg$match[1]) || 'unknown';
              console.warn(`✗ ${provider.toUpperCase()} provider doesn't support operator '${operatorName}' - falling back to next provider`);
            } else {
              console.warn(`✗ Failed to load with ${provider} provider:`, errorMsg);
            }

            // Store failed provider info for reporting
            this.accelerationInfo[`${provider}Error`] = errorMsg;
            continue;
          }
        }
        throw new Error('Failed to load model with any execution provider');
      }

      /**
       * Log acceleration information
       */
      logAccelerationInfo() {
        console.log('=== Acceleration Information ===');
        console.log(`Active Provider: ${this.accelerationInfo.activeProvider}`);
        console.log(`Available Providers: ${this.accelerationInfo.availableProviders.join(', ')}`);
        console.log(`WebGL Support: ${this.accelerationInfo.supportsWebGL}`);
        console.log(`WebGPU Support: ${this.accelerationInfo.supportsWebGPU}`);
        if (this.accelerationInfo.gpuInfo) {
          console.log('GPU Information:');
          console.log(`  Vendor: ${this.accelerationInfo.gpuInfo.vendor}`);
          console.log(`  Renderer: ${this.accelerationInfo.gpuInfo.renderer}`);
          console.log(`  Version: ${this.accelerationInfo.gpuInfo.version}`);
        }
        console.log('===============================');
      }

      /**
       * Get acceleration information
       * @returns {Object}
       */
      getAccelerationInfo() {
        return {
          ...this.accelerationInfo
        };
      }

      /**
       * Log model information for debugging
       */
      logModelInfo() {
        if (!this.session) return;
        console.log('=== Model Information ===');
        console.log('Input tensors:');
        this.session.inputNames.forEach((name, index) => {
          // Try to access input metadata safely
          try {
            if (this.session.inputs && this.session.inputs[index]) {
              const input = this.session.inputs[index];
              console.log(`  ${name}: ${input.dims} (${input.type})`);
            } else {
              console.log(`  ${name}: metadata not available`);
            }
          } catch (error) {
            console.log(`  ${name}: metadata not available`);
          }
        });
        console.log('Output tensors:');
        this.session.outputNames.forEach((name, index) => {
          // Try to access output metadata safely
          try {
            if (this.session.outputs && this.session.outputs[index]) {
              const output = this.session.outputs[index];
              console.log(`  ${name}: ${output.dims} (${output.type})`);
            } else {
              console.log(`  ${name}: metadata not available`);
            }
          } catch (error) {
            console.log(`  ${name}: metadata not available`);
          }
        });
        console.log('========================');
      }

      /**
       * Run inference on preprocessed image data
       * @param {Float32Array} inputData 
       * @returns {Promise<Float32Array>}
       */
      async runInference(inputData) {
        if (!this.isModelLoaded || !this.session) {
          throw new Error('Model not loaded. Call initialize() first.');
        }
        if (this.isInferring) {
          console.warn('Inference already in progress, skipping...');
          return null;
        }
        try {
          this.isInferring = true;
          const startTime = performance.now();

          // Create input tensor
          const inputTensor = new ort.Tensor('float32', inputData, [1, 3, this.inputHeight, this.inputWidth]);

          // Get input name from model
          const inputName = this.session.inputNames[0];

          // Run inference
          const results = await this.session.run({
            [inputName]: inputTensor
          });

          // Get output tensor
          const outputName = this.session.outputNames[0];
          const outputTensor = results[outputName];

          // Calculate inference time
          const endTime = performance.now();
          const inferenceTime = endTime - startTime;

          // Update statistics
          this.updateInferenceStats(inferenceTime);
          console.log(`Inference completed in ${inferenceTime.toFixed(2)}ms`);
          return outputTensor.data;
        } catch (error) {
          console.error('Inference failed:', error);
          throw new Error(`Inference failed: ${error.message}`);
        } finally {
          this.isInferring = false;
        }
      }

      /**
       * Process video frame and return segmentation mask
       * @param {HTMLVideoElement} video 
       * @returns {Promise<Object>} - {mask: Uint8Array, stats: Object}
       */
      async processVideoFrame(video) {
        try {
          // Check if model is ready
          if (!this.isModelLoaded) {
            throw new Error('Model not initialized');
          }

          // Get video dimensions
          const videoWidth = video.videoWidth;
          const videoHeight = video.videoHeight;
          if (videoWidth === 0 || videoHeight === 0) {
            throw new Error('Video not ready');
          }

          // Determine if rotation is needed for model input
          const shouldRotateForModel = ImageUtils.shouldRotateForModel(videoWidth, videoHeight);

          // Preprocess video frame
          const preprocessedData = ImageUtils.preprocessVideoFrame(video, this.inputWidth, this.inputHeight, shouldRotateForModel);

          // Run inference
          const modelOutput = await this.runInference(preprocessedData);
          if (!modelOutput) {
            return null; // Inference skipped
          }

          // Process model output to create mask
          const mask = ImageUtils.processModelOutput(modelOutput, this.inputHeight, this.inputWidth);
          return {
            mask: mask,
            shouldRotateBack: shouldRotateForModel,
            stats: this.getInferenceStats()
          };
        } catch (error) {
          console.error('Error processing video frame:', error);
          throw error;
        }
      }

      /**
       * Update inference performance statistics
       * @param {number} inferenceTime 
       */
      updateInferenceStats(inferenceTime) {
        this.inferenceStats.totalInferences++;
        this.inferenceStats.totalTime += inferenceTime;
        this.inferenceStats.averageTime = this.inferenceStats.totalTime / this.inferenceStats.totalInferences;
        this.inferenceStats.lastInferenceTime = inferenceTime;
      }

      /**
       * Get current inference statistics
       * @returns {Object}
       */
      getInferenceStats() {
        return {
          ...this.inferenceStats,
          fps: this.inferenceStats.lastInferenceTime > 0 ? 1000 / this.inferenceStats.lastInferenceTime : 0
        };
      }

      /**
       * Reset inference statistics
       */
      resetStats() {
        this.inferenceStats = {
          totalInferences: 0,
          totalTime: 0,
          averageTime: 0,
          lastInferenceTime: 0
        };
      }

      /**
       * Check if model is ready for inference
       * @returns {boolean}
       */
      isReady() {
        return this.isModelLoaded && !this.isInferring;
      }

      /**
       * Get model specifications
       * @returns {Object}
       */
      getModelSpecs() {
        return {
          inputHeight: this.inputHeight,
          inputWidth: this.inputWidth,
          numClasses: this.numClasses,
          isLoaded: this.isModelLoaded
        };
      }

      /**
       * Dispose of the model and free resources
       */
      dispose() {
        if (this.session) {
          this.session.release();
          this.session = null;
        }
        this.isModelLoaded = false;
        this.isInferring = false;
        console.log('Model resources disposed');
      }
    }

    /**
     * Main application module
     * Coordinates camera, model inference, and UI interactions
     */

    class CardSegmentationApp {
      constructor() {
        // Core modules
        this.cameraManager = new CameraManager();
        this.modelInference = new ModelInference();

        // DOM elements
        this.elements = {};

        // Application state
        this.state = {
          isInitialized: false,
          isModelLoaded: false,
          isCameraActive: false,
          isInferenceRunning: false,
          currentError: null
        };

        // Animation frame ID for inference loop
        this.inferenceLoopId = null;

        // Performance tracking
        this.performanceStats = {
          frameCount: 0,
          lastFpsUpdate: 0,
          fps: 0
        };
      }

      /**
       * Initialize the application
       */
      async init() {
        try {
          console.log('Initializing Card Segmentation App...');

          // Get DOM elements
          this.setupDOMElements();

          // Set up event listeners
          this.setupEventListeners();

          // Show loading indicator
          this.showLoading('Initializing cameras...');

          // Initialize camera manager
          await this.cameraManager.initialize();
          this.populateCameraDropdown();

          // Initialize model
          this.showLoading('Loading AI model...');
          await this.modelInference.initialize();

          // Update acceleration info display
          this.updateAccelerationInfo();

          // Hide loading, show camera selection
          this.hideLoading();
          this.showCameraSelection();
          this.state.isInitialized = true;
          this.state.isModelLoaded = true;
          console.log('Application initialized successfully');
        } catch (error) {
          console.error('Application initialization failed:', error);
          this.showError('Failed to initialize application', error.message);
        }
      }

      /**
       * Set up DOM element references
       */
      setupDOMElements() {
        this.elements = {
          // Main containers
          cameraSelection: document.getElementById('cameraSelection'),
          videoContainer: document.getElementById('videoContainer'),
          loadingIndicator: document.getElementById('loadingIndicator'),
          errorDisplay: document.getElementById('errorDisplay'),
          // Camera selection
          cameraSelect: document.getElementById('cameraSelect'),
          startCamera: document.getElementById('startCamera'),
          // Video and controls
          videoElement: document.getElementById('videoElement'),
          overlayCanvas: document.getElementById('overlayCanvas'),
          toggleInference: document.getElementById('toggleInference'),
          switchCamera: document.getElementById('switchCamera'),
          // Info displays
          resolutionInfo: document.getElementById('resolutionInfo'),
          fpsInfo: document.getElementById('fpsInfo'),
          inferenceStatus: document.getElementById('inferenceStatus'),
          accelerationInfo: document.getElementById('accelerationInfo'),
          // Loading and error
          loadingText: document.getElementById('loadingText'),
          errorMessage: document.getElementById('errorMessage'),
          retryButton: document.getElementById('retryButton')
        };
      }

      /**
       * Set up event listeners
       */
      setupEventListeners() {
        // Camera selection
        this.elements.cameraSelect.addEventListener('change', e => {
          this.elements.startCamera.disabled = !e.target.value;
        });
        this.elements.startCamera.addEventListener('click', () => {
          this.startCamera();
        });

        // Video controls
        this.elements.toggleInference.addEventListener('click', () => {
          this.toggleInference();
        });
        this.elements.switchCamera.addEventListener('click', () => {
          this.showCameraSelection();
        });

        // Error handling
        this.elements.retryButton.addEventListener('click', () => {
          this.hideError();
          this.init();
        });

        // Handle video loaded
        this.elements.videoElement.addEventListener('loadedmetadata', () => {
          this.setupOverlayCanvas();
        });

        // Handle camera device changes
        this.cameraManager.onDeviceChange(() => {
          this.populateCameraDropdown();
        });

        // Handle page unload
        window.addEventListener('beforeunload', () => {
          this.cleanup();
        });
      }

      /**
       * Populate camera selection dropdown
       */
      populateCameraDropdown() {
        this.cameraManager.populateCameraSelect(this.elements.cameraSelect);
        this.elements.startCamera.disabled = this.elements.cameraSelect.value === '';
      }

      /**
       * Start camera with selected device
       */
      async startCamera() {
        try {
          const selectedCameraId = this.elements.cameraSelect.value;
          if (!selectedCameraId) {
            throw new Error('No camera selected');
          }
          this.showLoading('Starting camera...');

          // Start camera stream
          const streamInfo = await this.cameraManager.startCamera(this.elements.videoElement, selectedCameraId);

          // Update UI
          this.updateResolutionInfo(streamInfo);
          this.setupOverlayCanvas();

          // Show video container
          this.hideLoading();
          this.hideCameraSelection();
          this.showVideoContainer();
          this.state.isCameraActive = true;
          console.log('Camera started successfully:', streamInfo);
        } catch (error) {
          console.error('Failed to start camera:', error);
          this.showError('Failed to start camera', error.message);
        }
      }

      /**
       * Set up overlay canvas to match video dimensions
       */
      setupOverlayCanvas() {
        const video = this.elements.videoElement;
        const canvas = this.elements.overlayCanvas;
        if (video.videoWidth && video.videoHeight) {
          canvas.width = video.videoWidth;
          canvas.height = video.videoHeight;

          // Apply same rotation class as video if needed
          if (video.classList.contains('rotate-90ccw')) {
            canvas.classList.add('rotate-90ccw');
          } else {
            canvas.classList.remove('rotate-90ccw');
          }
        }
      }

      /**
       * Toggle inference on/off
       */
      toggleInference() {
        if (this.state.isInferenceRunning) {
          this.stopInference();
        } else {
          this.startInference();
        }
      }

      /**
       * Start continuous inference
       */
      startInference() {
        if (!this.state.isModelLoaded || !this.state.isCameraActive) {
          this.showError('Cannot start inference', 'Camera or model not ready');
          return;
        }
        this.state.isInferenceRunning = true;
        this.elements.toggleInference.textContent = 'Stop Detection';
        this.elements.toggleInference.className = 'btn btn-danger';
        this.updateInferenceStatus('Detection: Running');

        // Reset performance stats
        this.performanceStats.frameCount = 0;
        this.performanceStats.lastFpsUpdate = performance.now();

        // Start inference loop
        this.runInferenceLoop();
        console.log('Inference started');
      }

      /**
       * Stop continuous inference
       */
      stopInference() {
        this.state.isInferenceRunning = false;
        this.elements.toggleInference.textContent = 'Start Detection';
        this.elements.toggleInference.className = 'btn btn-success';
        this.updateInferenceStatus('Detection: Off');

        // Cancel animation frame
        if (this.inferenceLoopId) {
          cancelAnimationFrame(this.inferenceLoopId);
          this.inferenceLoopId = null;
        }

        // Clear overlay
        const ctx = this.elements.overlayCanvas.getContext('2d');
        ctx.clearRect(0, 0, this.elements.overlayCanvas.width, this.elements.overlayCanvas.height);
        console.log('Inference stopped');
      }

      /**
       * Main inference loop
       */
      async runInferenceLoop() {
        if (!this.state.isInferenceRunning) {
          return;
        }
        try {
          // Process video frame
          const result = await this.modelInference.processVideoFrame(this.elements.videoElement);
          if (result && result.mask) {
            // Draw segmentation overlay
            ImageUtils.drawSegmentationOverlay(result.mask, this.modelInference.inputWidth, this.modelInference.inputHeight, this.elements.overlayCanvas, result.shouldRotateBack);

            // Update performance stats
            this.updatePerformanceStats(result.stats);
          }
        } catch (error) {
          console.error('Inference loop error:', error);
          // Don't stop inference for individual frame errors
        }

        // Schedule next frame
        if (this.state.isInferenceRunning) {
          this.inferenceLoopId = requestAnimationFrame(() => this.runInferenceLoop());
        }
      }

      /**
       * Update performance statistics display
       */
      updatePerformanceStats(inferenceStats) {
        this.performanceStats.frameCount++;
        const now = performance.now();

        // Update FPS every second
        if (now - this.performanceStats.lastFpsUpdate >= 1000) {
          this.performanceStats.fps = this.performanceStats.frameCount;
          this.performanceStats.frameCount = 0;
          this.performanceStats.lastFpsUpdate = now;

          // Update UI
          this.elements.fpsInfo.textContent = `FPS: ${this.performanceStats.fps}`;
        }
      }

      /**
       * Update resolution information display
       */
      updateResolutionInfo(streamInfo) {
        const resText = `Resolution: ${streamInfo.width}x${streamInfo.height}${streamInfo.rotated ? ' (rotated)' : ''}`;
        this.elements.resolutionInfo.textContent = resText;
      }

      /**
       * Update inference status display
       */
      updateInferenceStatus(status) {
        this.elements.inferenceStatus.textContent = status;

        // Update status styling
        this.elements.inferenceStatus.className = 'status-inactive';
        if (status.includes('Running')) {
          this.elements.inferenceStatus.className = 'status-active';
        } else if (status.includes('Processing')) {
          this.elements.inferenceStatus.className = 'status-processing';
        }
      }

      /**
       * Update acceleration information display
       */
      updateAccelerationInfo() {
        if (!this.elements.accelerationInfo) return;
        const accelerationInfo = this.modelInference.getAccelerationInfo();

        // Create acceleration status text
        let accelerationText = `Acceleration: ${accelerationInfo.activeProvider.toUpperCase()}`;

        // Add GPU info if available
        if (accelerationInfo.gpuInfo && accelerationInfo.activeProvider !== 'wasm') {
          const gpu = accelerationInfo.gpuInfo;
          const vendor = gpu.vendor.includes('Google') ? gpu.renderer.split(' ')[0] : gpu.vendor;
          accelerationText += ` (${vendor})`;
        }

        // Add note if using CPU fallback due to GPU limitations
        if (accelerationInfo.activeProvider === 'wasm') {
          if (accelerationInfo.webglError && accelerationInfo.webglError.includes('cannot resolve operator')) {
            accelerationText += ' (GPU unsupported operators)';
          } else if (accelerationInfo.supportsWebGL || accelerationInfo.supportsWebGPU) {
            accelerationText += ' (GPU provider failed)';
          } else {
            accelerationText += ' (No GPU support)';
          }
        }
        this.elements.accelerationInfo.textContent = accelerationText;

        // Update styling based on acceleration type
        this.elements.accelerationInfo.className = 'acceleration-info';
        if (accelerationInfo.activeProvider === 'webgpu') {
          this.elements.accelerationInfo.classList.add('acceleration-webgpu');
        } else if (accelerationInfo.activeProvider === 'webgl') {
          this.elements.accelerationInfo.classList.add('acceleration-webgl');
        } else {
          this.elements.accelerationInfo.classList.add('acceleration-wasm');
        }
      }

      /**
       * Show loading indicator
       */
      showLoading() {
        let message = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : 'Loading...';
        this.elements.loadingText.textContent = message;
        this.elements.loadingIndicator.style.display = 'block';
        this.elements.cameraSelection.style.display = 'none';
        this.elements.videoContainer.style.display = 'none';
        this.elements.errorDisplay.style.display = 'none';
      }

      /**
       * Hide loading indicator
       */
      hideLoading() {
        this.elements.loadingIndicator.style.display = 'none';
      }

      /**
       * Show camera selection
       */
      showCameraSelection() {
        this.stopInference();
        this.cameraManager.stopCamera();
        this.state.isCameraActive = false;
        this.elements.cameraSelection.style.display = 'block';
        this.elements.videoContainer.style.display = 'none';
        this.elements.errorDisplay.style.display = 'none';
      }

      /**
       * Hide camera selection
       */
      hideCameraSelection() {
        this.elements.cameraSelection.style.display = 'none';
      }

      /**
       * Show video container
       */
      showVideoContainer() {
        this.elements.videoContainer.style.display = 'block';
        this.elements.errorDisplay.style.display = 'none';
      }

      /**
       * Show error message
       */
      showError(title, message) {
        this.elements.errorMessage.innerHTML = `<strong>${title}</strong><br>${message}`;
        this.elements.errorDisplay.style.display = 'block';
        this.elements.loadingIndicator.style.display = 'none';
        this.elements.cameraSelection.style.display = 'none';
        this.elements.videoContainer.style.display = 'none';
        this.state.currentError = {
          title,
          message
        };
      }

      /**
       * Hide error display
       */
      hideError() {
        this.elements.errorDisplay.style.display = 'none';
        this.state.currentError = null;
      }

      /**
       * Clean up resources
       */
      cleanup() {
        console.log('Cleaning up application...');
        this.stopInference();
        this.cameraManager.dispose();
        this.modelInference.dispose();
        this.state = {
          isInitialized: false,
          isModelLoaded: false,
          isCameraActive: false,
          isInferenceRunning: false,
          currentError: null
        };
      }
    }

    // Initialize application when DOM is loaded
    document.addEventListener('DOMContentLoaded', () => {
      const app = new CardSegmentationApp();
      app.init();

      // Make app globally available for debugging
      window.cardSegmentationApp = app;
    });

})();
//# sourceMappingURL=bundle.js.map