├── .gitignore ├── postcss.config.js ├── src ├── tflite │ ├── tflite_web_api_cc.wasm │ ├── tflite_web_api_cc_simd.wasm │ └── content_detection_mobilenet_v3.tflite ├── img │ ├── hero-screenshot-anime4k-small.png │ ├── play.svg │ ├── download-icon.svg │ ├── refresh.svg │ ├── chrome.svg │ ├── full-screen.svg │ ├── question.svg │ ├── folder.svg │ ├── logo.svg │ ├── edge.svg │ ├── loading.svg │ └── utils.py ├── index.css ├── videoEncoder.js ├── demuxer_mp4.js ├── lib │ └── image-compare-viewer.min.css ├── weights │ ├── cnn-2x-s-an.json │ ├── cnn-2x-s-3d.json │ ├── cnn-2x-s-rl.json │ ├── cnn-2x-m-an.json │ ├── cnn-2x-m-3d.json │ └── cnn-2x-m-rl.json ├── worker.js ├── index.html └── index.js ├── tailwind.config.js ├── README.md ├── package.json ├── Gruntfile.js └── webpack.config.js /.gitignore: -------------------------------------------------------------------------------- 1 | node_modules 2 | .idea 3 | dist 4 | /yarn-error.log 5 | -------------------------------------------------------------------------------- /postcss.config.js: -------------------------------------------------------------------------------- 1 | module.exports = { 2 | plugins: { 3 | tailwindcss: {}, 4 | autoprefixer: {}, 5 | }, 6 | } -------------------------------------------------------------------------------- /src/tflite/tflite_web_api_cc.wasm: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sb2702/free-ai-video-upscaler/HEAD/src/tflite/tflite_web_api_cc.wasm -------------------------------------------------------------------------------- /src/tflite/tflite_web_api_cc_simd.wasm: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sb2702/free-ai-video-upscaler/HEAD/src/tflite/tflite_web_api_cc_simd.wasm -------------------------------------------------------------------------------- /src/img/hero-screenshot-anime4k-small.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sb2702/free-ai-video-upscaler/HEAD/src/img/hero-screenshot-anime4k-small.png -------------------------------------------------------------------------------- /src/tflite/content_detection_mobilenet_v3.tflite: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sb2702/free-ai-video-upscaler/HEAD/src/tflite/content_detection_mobilenet_v3.tflite -------------------------------------------------------------------------------- /src/index.css: -------------------------------------------------------------------------------- 1 | 2 | @tailwind base; 3 | @tailwind components; 4 | @tailwind utilities; 5 | 6 | video { 7 | width: 100%; 8 | height: 100%; 9 | object-fit: fill; 10 | } 11 | 12 | #loading{ 13 | width: 100%; 14 | } 15 | 16 | #download-link{ 17 | position: relative; 18 | margin: auto; 19 | width: 100%; 20 | display: flex; 21 | } -------------------------------------------------------------------------------- /src/img/play.svg: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /src/img/download-icon.svg: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /tailwind.config.js: -------------------------------------------------------------------------------- 1 | /** @type {import('tailwindcss').Config} */ 2 | module.exports = { 3 | content: ["./src/**/*.{html,js}"], 4 | theme: { 5 | extend: { 6 | fontFamily: { 7 | 'manrope': ['Manrope', 'sans-serif'], 8 | }, 9 | colors: { 10 | 'primary': '#1e3a8a', 11 | 'text-primary': '#1e3a8a', 12 | 'primary-blue': '#1e3a8a', 13 | 'light-blue': '#bfdbfe', 14 | 'gray-light': '#F5F5F5', 15 | 'gray-border': '#c8c8d5', 16 | 'gray-text': '#999', 17 | } 18 | }, 19 | }, 20 | plugins: [], 21 | } -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Free AI Video Upscaler 2 | 3 | A simple, quick and free no-nonsense tool for upscaling video with AI upscaling algorithms like [Anime4K](https://github.com/bloc97/Anime4K) right in your browser- no signups, no downloads just choose a video and download your upscaled video after it's done processing. 4 | 5 | You can get started at 👉 [Free AI Video Upscaler](https://free.upscaler.video/) 👈 6 | 7 | 8 | 9 | Based on my [WebSR](https://github.com/sb2702/websr) SDK. 10 | -------------------------------------------------------------------------------- /src/img/refresh.svg: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /src/img/chrome.svg: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /src/img/full-screen.svg: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /src/img/question.svg: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /src/videoEncoder.js: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | self.onmessage = ({data}) => { 6 | 7 | if(data.cmd === 'init'){ 8 | 9 | self.videoEncoder = new VideoEncoder({ 10 | output: (chunk, meta) => { 11 | 12 | const buffer = new ArrayBuffer(chunk.byteLength); 13 | 14 | chunk.copyTo(buffer); 15 | 16 | postMessage({ 17 | cmd: 'encoded', 18 | buffer: buffer, 19 | type: chunk.type, 20 | timestamp: chunk.timestamp, 21 | duration: chunk.duration, 22 | meta: meta 23 | }, [buffer]) 24 | 25 | 26 | }, 27 | error: (e) => { 28 | postMessage({ 29 | cmd: 'error', 30 | msg: e.message 31 | }) 32 | } 33 | }); 34 | 35 | 36 | self.videoEncoder.configure(data.config); 37 | 38 | 39 | } else if(data.cmd === 'encode'){ 40 | 41 | const upscaled_frame = new VideoFrame(data.bitmap,{ timestamp: data.timestamp}); 42 | 43 | self.videoEncoder.encode(upscaled_frame, { keyFrame: data.isKeyFrame}); 44 | 45 | upscaled_frame.close(); 46 | 47 | 48 | } else if (data.cmd === 'flush'){ 49 | 50 | self.videoEncoder.flush(); 51 | } 52 | 53 | 54 | } 55 | -------------------------------------------------------------------------------- /package.json: -------------------------------------------------------------------------------- 1 | { 2 | "name": "free-video-upscaler", 3 | "version": "0.0.1", 4 | "description": "Free tool to upscale videos in the browser", 5 | "main": "src/main.js", 6 | "scripts": { 7 | "build": "webpack", 8 | "serve": "webpack-dev-server" 9 | }, 10 | "repository": { 11 | "type": "git", 12 | "url": "git+https://github.com/sb2702/free-ai-video-upscaler.git" 13 | }, 14 | "author": "Sam Bhattacharyya", 15 | "license": "MIT", 16 | "bugs": { 17 | "url": "https://github.com/sb2702/free-ai-video-upscaler/issues" 18 | }, 19 | "homepage": "https://github.com/sb2702/free-ai-video-upscaler#readme", 20 | "dependencies": { 21 | "@babel/core": "^7.1.6", 22 | "@popperjs/core": "^2.11.8", 23 | "@tensorflow/tfjs-backend-cpu": "^4.15.0", 24 | "@tensorflow/tfjs-core": "^4.15.0", 25 | "@tensorflow/tfjs-tflite": "0.0.1-alpha.9", 26 | "alpinejs": "3.4.2", 27 | "babel-loader": "^9.1.3", 28 | "bootstrap": "^5.3.2", 29 | "clean-webpack-plugin": "^4.0.0", 30 | "copy-webpack-plugin": "^11.0.0", 31 | "grunt": "^1.6.1", 32 | "grunt-aws-s3": "^2.0.2", 33 | "grunt-cloudfront": "^0.2.2", 34 | "html-webpack-plugin": "^5.5.4", 35 | "jquery": "^3.7.1", 36 | "mp4-muxer": "^3.0.2", 37 | "mp4box": "^0.5.2", 38 | "popper.js": "^1.16.1", 39 | "style-loader": "^3.3.3", 40 | "webpack": "^5.89.0", 41 | "webpack-cli": "^5.1.4", 42 | "webpack-dev-server": "^4.15.1" 43 | }, 44 | "devDependencies": { 45 | "autoprefixer": "^10.4.21", 46 | "css-loader": "^6.8.1", 47 | "postcss": "^8.5.6", 48 | "postcss-loader": "^8.1.1", 49 | "tailwindcss": "^3.4.17" 50 | } 51 | } 52 | -------------------------------------------------------------------------------- /Gruntfile.js: -------------------------------------------------------------------------------- 1 | 2 | module.exports = function (grunt) { 3 | 4 | 5 | grunt.loadNpmTasks('grunt-aws-s3'); 6 | grunt.loadNpmTasks('grunt-cloudfront'); 7 | 8 | 9 | grunt.initConfig({ 10 | 11 | aws_s3: { 12 | options: { 13 | accessKeyId: process.env.AWS_KEY_PERSONAL, 14 | secretAccessKey: process.env.AWS_SECRET_PERSONAL, 15 | region: 'us-east-1', 16 | uploadConcurrency: 5, // 5 simultaneous uploads 17 | downloadConcurrency: 5 // 5 simultaneous downloads 18 | }, 19 | production: { 20 | options: { 21 | bucket: 'free.upscaler.video', 22 | differential: true // Only uploads the files that have changed 23 | }, 24 | files: [ 25 | {expand: true, 26 | cwd: 'dist/', 27 | src: ['**', '!*~'], 28 | dest: '/'} 29 | ] 30 | }, 31 | }, 32 | 33 | cloudfront: { 34 | options: { 35 | region:'us-east-1', // your AWS region 36 | distributionId:"E1PI5O74ZD5EVI", // DistributionID where files are stored 37 | listInvalidations:true, // if you want to see the status of invalidations 38 | listDistributions:false, // if you want to see your distributions list in the console 39 | version:"1.0", // if you want to invalidate a specific version (file-1.0.js), 40 | credentials: { 41 | accessKeyId: process.env.AWS_KEY_PERSONAL, 42 | secretAccessKey: process.env.AWS_SECRET_PERSONAL, 43 | } 44 | 45 | }, 46 | production: { 47 | CallerReference: Date.now().toString(), 48 | Paths: { 49 | Quantity: 1, 50 | Items: [ '/*' ] 51 | } 52 | }, 53 | }, 54 | 55 | 56 | 57 | 58 | }); 59 | 60 | grunt.registerTask('push', ['aws_s3:production', 'cloudfront:production']); 61 | 62 | 63 | 64 | }; 65 | -------------------------------------------------------------------------------- /src/img/folder.svg: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /webpack.config.js: -------------------------------------------------------------------------------- 1 | const path = require('path'); 2 | const webpack = require('webpack'); 3 | 4 | const CopyWebpackPlugin = require('copy-webpack-plugin'); 5 | const { CleanWebpackPlugin } = require('clean-webpack-plugin'); 6 | const HtmlWebpackPlugin = require('html-webpack-plugin'); 7 | 8 | 9 | module.exports = { 10 | entry: [ "./src/index.js", './src/worker.js'], 11 | output: { 12 | libraryExport: "default", 13 | path: path.resolve(__dirname, './dist'), 14 | filename: "main.js" 15 | }, 16 | module: { 17 | 18 | rules: [ 19 | { 20 | test: /\.js$/, 21 | exclude: /node_modules/, 22 | use: { 23 | loader: "babel-loader" 24 | }, 25 | }, 26 | 27 | { 28 | test: /\.css$/i, 29 | use: ["style-loader", "css-loader", "postcss-loader"], 30 | } 31 | 32 | ], 33 | 34 | }, 35 | 36 | plugins: [ 37 | 38 | new HtmlWebpackPlugin({ 39 | template: 'src/index.html' 40 | }), 41 | 42 | new CleanWebpackPlugin({ 43 | cleanStaleWebpackAssets: false 44 | }), 45 | new CopyWebpackPlugin( { 46 | patterns: [ 47 | { from: "src/*.js", to: path.basename('[name].js') }, 48 | { from: "src/img/*.svg", to: path.basename('[name].svg') }, 49 | { from: "src/img/*.png", to: path.basename('[name].png') }, 50 | { from: "src/tflite/**", to: path.basename('[name][ext]') }, 51 | 52 | ] 53 | }) 54 | 55 | ], 56 | resolve: { 57 | extensions: [".ts", ".tsx", ".js", ".css"] 58 | }, 59 | 60 | devServer: { 61 | static: { 62 | directory: path.join(__dirname, 'dist'), 63 | }, 64 | compress: true, 65 | port: 8080, 66 | allowedHosts: "all", 67 | }, 68 | 69 | mode: 'development' 70 | 71 | }; 72 | -------------------------------------------------------------------------------- /src/img/logo.svg: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | -------------------------------------------------------------------------------- /src/img/edge.svg: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /src/demuxer_mp4.js: -------------------------------------------------------------------------------- 1 | import MP4Box from 'mp4box' 2 | import {DataStream} from 'mp4box' 3 | 4 | 5 | // Demuxes the first video track of an MP4 file using MP4Box, calling 6 | // `onConfig()` and `onChunk()` with appropriate WebCodecs objects. 7 | class MP4Demuxer { 8 | onConfig = null; 9 | onData = null; 10 | setStatus = null; 11 | file = null; 12 | 13 | constructor(buffer, type, {onConfig, onData, setStatus}) { 14 | this.onConfig = onConfig; 15 | this.onData = onData; 16 | this.setStatus = setStatus; 17 | 18 | this.type = type; 19 | // Configure an MP4Box File for demuxing. 20 | this.file = MP4Box.createFile(); 21 | this.file.onError = error => setStatus("demux", error); 22 | this.file.onReady = this.onReady.bind(this); 23 | this.file.onSamples = this.onSamples.bind(this); 24 | buffer.fileStart = 0; 25 | this.file.appendBuffer(buffer); 26 | this.file.flush(); 27 | 28 | } 29 | 30 | // Get the appropriate `description` for a specific track. Assumes that the 31 | // track is H.264, H.265, VP8, VP9, or AV1. 32 | description(track) { 33 | const trak = this.file.getTrackById(track.id); 34 | for (const entry of trak.mdia.minf.stbl.stsd.entries) { 35 | const box = entry.avcC || entry.hvcC || entry.vpcC || entry.av1C; 36 | if (box) { 37 | const stream = new DataStream(undefined, 0, DataStream.BIG_ENDIAN); 38 | box.write(stream); 39 | return new Uint8Array(stream.buffer, 8); // Remove the box header. 40 | } 41 | } 42 | throw new Error("avcC, hvcC, vpcC, or av1C box not found"); 43 | } 44 | 45 | onReady(info) { 46 | this.setStatus("demux", "Ready"); 47 | 48 | 49 | const track = this.type === 'video'? info.videoTracks[0] : info.audioTracks[0]; 50 | let config ={}; 51 | 52 | if(track.type === 'video'){ 53 | config = { 54 | codec: track.codec, 55 | codedHeight: track.video.height, 56 | codedWidth: track.video.width, 57 | description: this.description(track), 58 | } 59 | } else { 60 | config = { 61 | codec: track.codec, 62 | sampleRate: track.audio.sample_rate, 63 | numberOfChannels: track.audio.channel_count 64 | } 65 | } 66 | 67 | this.onConfig(config); 68 | 69 | this.file.setExtractionOptions(track.id); 70 | this.file.start(); 71 | } 72 | 73 | onSamples(track_id, ref, samples) { 74 | // Generate and emit an EncodedVideoChunk for each demuxed sample. 75 | 76 | const chunks = []; 77 | 78 | const Chunk = this.type === 'video'? EncodedVideoChunk : EncodedAudioChunk; 79 | 80 | for (const sample of samples) { 81 | 82 | chunks.push(new Chunk({ 83 | type: sample.is_sync ? "key" : "delta", 84 | timestamp: 1e6 * sample.cts / sample.timescale, 85 | duration: 1e6 * sample.duration / sample.timescale, 86 | data: sample.data 87 | })); 88 | 89 | } 90 | 91 | this.onData(chunks); 92 | } 93 | 94 | flush(){ 95 | 96 | this.file.flush(); 97 | } 98 | } 99 | 100 | export { 101 | MP4Demuxer 102 | } -------------------------------------------------------------------------------- /src/img/loading.svg: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 | 50 | 51 | -------------------------------------------------------------------------------- /src/lib/image-compare-viewer.min.css: -------------------------------------------------------------------------------- 1 | .icv{position:relative;overflow:hidden;cursor:row-resize}.icv__icv--vertical{cursor:row-resize}.icv__icv--horizontal{cursor:col-resize}.icv__img{pointer-events:none;-o-user-select:none;-moz-user-select:none;-webkit-user-select:none;-ms-user-select:none;user-select:none;max-width:none;width:100%;margin:0 !important;padding:0 !important;border:0 !important;border-radius:0 !important;top:0;display:block}.icv__is--fluid .icv__img{display:none}.icv__img-a{height:auto;position:static;z-index:1;left:0px}.icv__img-b{height:100%;position:absolute;z-index:2;left:auto;right:0px;width:auto}.icv__icv--vertical .icv__img-b{width:100%;height:auto}.icv__imposter{z-index:4;position:absolute;top:0px;left:0px;width:100%;height:100%}.icv__wrapper{position:absolute;width:100%;height:100%;right:0px;top:0px;overflow:hidden;background-size:cover;background-position:center center;z-index:3}.icv__is--fluid .icv__wrapper,.icv__icv--vertical .icv__wrapper{width:100% !important}.icv__is--fluid .icv__wrapper,.icv__icv--horizontal .icv__wrapper{height:100% !important}.icv__fluidwrapper{background-size:cover;background-position:center;position:absolute;top:0;left:0;width:100%;height:100%}.icv__control{position:absolute;display:-webkit-box;display:-ms-flexbox;display:flex;-webkit-box-orient:vertical;-webkit-box-direction:normal;-ms-flex-direction:column;flex-direction:column;-webkit-box-pack:center;-ms-flex-pack:center;justify-content:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;-webkit-box-sizing:border-box;box-sizing:border-box;height:100%;top:0px;z-index:5}.icv__icv--vertical .icv__control{-webkit-box-orient:horizontal;-webkit-box-direction:normal;-ms-flex-direction:row;flex-direction:row;left:0;width:100%}.icv__control-line{height:50%;width:2px;z-index:6}.icv__icv--vertical .icv__control-line{width:50%}.icv__theme-wrapper{width:100%;height:100%;display:-webkit-box;display:-ms-flexbox;display:flex;-webkit-box-pack:justify;-ms-flex-pack:justify;justify-content:space-between;-webkit-box-align:center;-ms-flex-align:center;align-items:center;position:absolute;-webkit-transition:all 0.1s ease-out 0s;transition:all 0.1s ease-out 0s;z-index:5}.icv__icv--vertical .icv__theme-wrapper{-webkit-box-orient:vertical;-webkit-box-direction:normal;-ms-flex-direction:column;flex-direction:column}.icv__arrow-wrapper{display:-webkit-box;display:-ms-flexbox;display:flex;-webkit-box-pack:center;-ms-flex-pack:center;justify-content:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;-webkit-transition:all 0.1s ease-out 0s;transition:all 0.1s ease-out 0s}.icv__arrow-a{-webkit-transform:scale(1.5) rotateZ(180deg);transform:scale(1.5) rotateZ(180deg);height:20px;width:20px;-webkit-filter:drop-shadow(0px 3px 5px rgba(0,0,0,0.33));filter:drop-shadow(0px -3px 5px rgba(0,0,0,0.33))}.icv__arrow-b{-webkit-transform:scale(1.5) rotateZ(0deg);transform:scale(1.5) rotateZ(0deg);height:20px;width:20px;-webkit-filter:drop-shadow(0px 3px 5px rgba(0,0,0,0.33));filter:drop-shadow(0px 3px 5px rgba(0,0,0,0.33))}.icv__circle{width:50px;height:50px;-webkit-box-sizing:border-box;box-sizing:border-box;-ms-flex-negative:0;flex-shrink:0;border-radius:999px}.icv__label{position:absolute;bottom:1rem;z-index:12;background:rgba(0,0,0,0.33);color:white;border-radius:3px;padding:0.5rem 0.75rem;font-size:0.85rem;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none}.icv__label.vertical{bottom:auto;left:1rem}.icv__label.on-hover{-webkit-transform:scale(0);transform:scale(0);-webkit-transition:0.25s cubic-bezier(0.68, 0.26, 0.58, 1.22);transition:0.25s cubic-bezier(0.68, 0.26, 0.58, 1.22)}.icv:hover .icv__label.on-hover{-webkit-transform:scale(1);transform:scale(1)}.icv__label-before{left:1rem}.icv__label-after{right:1rem}.icv__label-before.vertical{top:1rem}.icv__label-after.vertical{bottom:1rem;right:auto}.icv__body{-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none} 2 | 3 | 4 | /*# sourceMappingURL=image-compare-viewer.min.css.map*/ -------------------------------------------------------------------------------- /src/img/utils.py: -------------------------------------------------------------------------------- 1 | from PIL import Image 2 | import IPython 3 | from io import BytesIO 4 | import numpy as np 5 | import math 6 | import os 7 | import tensorflow as tf 8 | 9 | 10 | #Takes as input an image/array of size [height, width, channels] with range of 0-255 11 | def show_image(img, width=None, height=None, fmt='png'): 12 | if width is None: 13 | width = img.shape[-2] 14 | if height is None: 15 | height = img.shape[-3] 16 | f = BytesIO() 17 | Image.fromarray(np.clip(np.array(img), 0, 255).astype(np.uint8)).save(f, fmt) 18 | IPython.display.display(IPython.display.Image(data=f.getvalue(), width=width, height=height)) 19 | 20 | #Takes as input images of size [batch, height, width, channels] with range of 0-255 21 | def show_images(images, show_max=5, scale=1, val_range=[0, 255]): 22 | 23 | #Convert to numpy array, force eager execution when using tensorflow 24 | images = np.array(images) 25 | #Normalize images 26 | images = np.clip(((images - val_range[0]) / (val_range[1] - val_range[0])) * 255, 0, 255).astype(np.uint8) 27 | 28 | #Adding channel missing axis automatically 29 | if images.shape[-1] != 3 and images.shape[-1] != 1: 30 | if len(images.shape) > 3: 31 | return 32 | images = images[...,np.newaxis] 33 | 34 | #Adding batch missing axis automatically 35 | if len(images.shape) == 3: 36 | images = images[np.newaxis,...] 37 | 38 | #Compute max numbers of images to show 39 | show_max = min(show_max, len(images)) 40 | 41 | #Concatenate images in x-axis (horizontally) 42 | images = np.concatenate(images[:show_max], axis=-2) 43 | 44 | #Remove extra axis if necessary 45 | if images.shape[-1] == 1: 46 | images = images[..., 0] 47 | 48 | show_image(images, images.shape[1]*scale, images.shape[0]*scale) 49 | 50 | def check_is_image(obj): 51 | if tf.is_tensor(obj): 52 | tshape = tf.shape(obj) 53 | if len(tshape) == 3: 54 | if tshape[-1] == 1 or tshape[-1] == 3: 55 | return True 56 | return False 57 | 58 | def check_is_batch(obj): 59 | if tf.is_tensor(obj): 60 | tshape = tf.shape(obj) 61 | if len(tshape) == 4: 62 | if tshape[-1] == 1 or tshape[-1] == 3: 63 | return True 64 | return False 65 | 66 | def recursive_max_horizontal_size(tree): 67 | if check_is_batch(tree) or check_is_image(tree): 68 | return tf.shape(tree)[-3] 69 | else: 70 | max_val = 0 71 | for ex in tree: 72 | max_val = max(recursive_max_horizontal_size(ex), max_val) 73 | return max_val 74 | 75 | def preview_dataset(dataset, show_max=5, scale=1, normalize_scale=True, val_range=[0, 255]): 76 | dataset_example = list(dataset.prefetch(tf.data.AUTOTUNE).take(show_max)) #Take from dataset, might be slow and unoptimized if dataset is not created from generator... 77 | 78 | target_size = recursive_max_horizontal_size(dataset_example) if normalize_scale else None 79 | return preview_dataset_list(dataset_example, min(show_max, len(dataset_example)), scale, float(target_size), val_range) 80 | 81 | 82 | def preview_dataset_list(dataset_list, show_max, scale, target_size, val_range): 83 | #Take a single example out of dataset 84 | dataset_example = dataset_list[0] 85 | 86 | #Dataset gives out a tensor 87 | if tf.is_tensor(dataset_example): 88 | 89 | #Compute scaled size if asked 90 | tshape = tf.shape(dataset_example) 91 | if target_size is not None and len(tshape) >= 3: 92 | scale = target_size / float(tshape[-3]) * scale 93 | 94 | #If it is a batch 95 | if check_is_batch(dataset_example): 96 | #Show the batch directly 97 | show_images(dataset_example, show_max, scale, val_range) 98 | #If not a batch 99 | elif check_is_image(dataset_example): 100 | #Show list 101 | show_images(dataset_list, show_max, scale, val_range) 102 | 103 | #Dataset does not give out a tensor 104 | else: 105 | #Call function recursively with inner pairs 106 | for k in range(len(dataset_example)): 107 | sublist = [dataset_list[i][k] for i in range(len(dataset_list))] 108 | preview_dataset_list(sublist, show_max, scale, target_size, val_range) 109 | 110 | 111 | 112 | def get_gaussian_kernel(shape=(7, 7), sigma=1.0): 113 | m, n = [(sh - 1.0) / 2.0 for sh in shape] 114 | x = tf.expand_dims(tf.range(-n, n + 1,dtype=tf.float32), 1) 115 | y = tf.expand_dims(tf.range(-m, m + 1,dtype=tf.float32), 0) 116 | 117 | h = tf.exp(tf.math.divide_no_nan(-((x*x) + (y*y)), 2 * sigma * sigma)) 118 | h = tf.math.divide_no_nan(h,tf.reduce_sum(h)) 119 | return h 120 | 121 | def get_lanczos_kernel(shape=(7, 7), sigma=1.0): 122 | m, n = [(sh - 1.0) / 2.0 for sh in shape] 123 | x = tf.expand_dims(tf.range(-n, n + 1,dtype=tf.float32), 1) 124 | y = tf.expand_dims(tf.range(-m, m + 1,dtype=tf.float32), 0) 125 | 126 | d = tf.math.sqrt((x * x) + (y * y)) 127 | h = tf.experimental.numpy.sinc(d) * tf.experimental.numpy.sinc(d / sigma) 128 | h = tf.math.divide_no_nan(h, tf.reduce_sum(h)) 129 | return h 130 | 131 | def gaussian_blur_no_pad(inp, shape=(7, 7), sigma=1.0): 132 | 133 | #Add axis if rank is 3 instead of 4 134 | imgshape = tf.shape(inp) 135 | if len(imgshape) == 3: 136 | inp = inp[tf.newaxis,...] 137 | 138 | in_channel = tf.shape(inp)[-1] 139 | k = get_gaussian_kernel(shape, sigma) 140 | k = tf.expand_dims(k, axis=-1) 141 | k = tf.repeat(k, in_channel, axis=-1) 142 | k = tf.reshape(k, (*shape, in_channel, 1)) 143 | conv = tf.nn.depthwise_conv2d(inp, k, strides=[1,1,1,1], padding="VALID") 144 | 145 | #Remove axis if added beforehand 146 | if len(imgshape) == 3: 147 | conv = conv[0] 148 | 149 | return conv 150 | 151 | def lanczos_ring_no_pad(inp, shape=(7, 7), sigma=1.0): 152 | 153 | #Add axis if rank is 3 instead of 4 154 | imgshape = tf.shape(inp) 155 | if len(imgshape) == 3: 156 | inp = inp[tf.newaxis,...] 157 | 158 | in_channel = tf.shape(inp)[-1] 159 | k = get_lanczos_kernel(shape, sigma) 160 | k = tf.expand_dims(k, axis=-1) 161 | k = tf.repeat(k, in_channel, axis=-1) 162 | k = tf.reshape(k, (*shape, in_channel, 1)) 163 | conv = tf.nn.depthwise_conv2d(inp, k, strides=[1,1,1,1], padding="VALID") 164 | 165 | #Remove axis if added beforehand 166 | if len(imgshape) == 3: 167 | conv = conv[0] 168 | 169 | return conv 170 | 171 | #Shape should be odd integer to prevent padding errors 172 | def degrade_ring(img, sigma, shape=(7, 7), do_clip=True): 173 | 174 | #Padding to preserve size of the input, pad with reflect to prevent image mean shift 175 | img = tf.pad(img, [[shape[0]//2, shape[0]//2], [shape[1]//2, shape[1]//2], [0, 0]], mode="REFLECT") 176 | img = lanczos_ring_no_pad(img, shape, sigma) 177 | 178 | if do_clip: 179 | img = tf.clip_by_value(img, 0, 1) 180 | 181 | return img 182 | 183 | #Shape should be odd integer to prevent padding errors 184 | def degrade_blur_gaussian(img, sigma, shape=(7, 7), do_clip=True): 185 | 186 | #Padding to preserve size of the input, pad with reflect to prevent image mean shift 187 | img = tf.pad(img, [[shape[0]//2, shape[0]//2], [shape[1]//2, shape[1]//2], [0, 0]], mode="REFLECT") 188 | img = gaussian_blur_no_pad(img, shape, sigma) 189 | 190 | if do_clip: 191 | img = tf.clip_by_value(img, 0, 1) 192 | 193 | return img 194 | 195 | def degrade_noise_gaussian(img, sigma, color=True, low_freq_sigma=None, low_freq_shape=(7, 7), do_clip=True): 196 | 197 | imgshape = tf.shape(img) 198 | if color: 199 | rg = tf.random.normal(imgshape, mean=0, stddev=rs) 200 | else: 201 | rg = tf.random.normal(imgshape[:-1], mean=0, stddev=rs)[..., tf.newaxis] 202 | 203 | #Low frequency blur if requested 204 | if low_freq_sigma is not None: 205 | rg = degrade_blur_gaussian(rg, low_freq_sigma, low_freq_shape, do_clip=False) 206 | 207 | img = img + rg 208 | 209 | if do_clip: 210 | img = tf.clip_by_value(img, 0, 1) 211 | 212 | return img 213 | 214 | def degrade_rgb_to_yuv(img, jpeg_factor=None, chroma_subsampling=True, chroma_method="area", do_clip=True): 215 | img_yuv = tf.image.rgb_to_yuv(img) 216 | img_y, img_u, img_v = tf.split(img_yuv, 3, axis=-1) 217 | 218 | imgshape = tf.shape(img) 219 | yuvshape = tf.shape(img_yuv) 220 | 221 | if chroma_subsampling: 222 | img_u = tf.image.resize(img_u, [yuvshape[-3]//2, yuvshape[-2]//2], method=chroma_method) 223 | img_v = tf.image.resize(img_v, [yuvshape[-3]//2, yuvshape[-2]//2], method=chroma_method) 224 | 225 | if jpeg_factor is not None: 226 | img_y = tf.image.adjust_jpeg_quality(img_y, jpeg_factor) 227 | 228 | img_u = img_u + 0.5 229 | img_v = img_v + 0.5 230 | 231 | if jpeg_factor is not None: 232 | img_u = tf.image.adjust_jpeg_quality(img_u, jpeg_factor) 233 | img_v = tf.image.adjust_jpeg_quality(img_v, jpeg_factor) 234 | 235 | if do_clip: 236 | img_y = tf.clip_by_value(img_y, 0, 1) 237 | img_u = tf.clip_by_value(img_u, 0, 1) 238 | img_v = tf.clip_by_value(img_v, 0, 1) 239 | 240 | return (img_y, img_u, img_v) 241 | 242 | def degrade_yuv_to_rgb(img, chroma_method="bicubic", do_clip=True): 243 | img_y, img_u, img_v = img 244 | img_uv = tf.concat([img_u, img_v], axis=-1) 245 | 246 | yshape = tf.shape(img_y) 247 | uvshape = tf.shape(img_uv) 248 | 249 | if yshape[-3] != uvshape[-3] or yshape[-2] != uvshape[-2]: 250 | img_uv = tf.image.resize(img_uv, [yshape[-3], yshape[-2]], method=chroma_method) 251 | 252 | img_uv = img_uv - 0.5 253 | img_yuv = tf.concat([img_y, img_uv], axis=-1) 254 | 255 | img = tf.image.yuv_to_rgb(img_yuv) 256 | 257 | if do_clip: 258 | img = tf.clip_by_value(img, 0, 1) 259 | 260 | return img -------------------------------------------------------------------------------- /src/weights/cnn-2x-s-an.json: 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0.09636715, -0.009355378, -0.08328378, -0.018469354, -0.3793854, 0.0123696355, -0.11376425, 0.023209028, -0.04596226, 0.019992355, 0.0005862636, 0.022716032, -0.0073214257, -0.08092167, 0.029061595, -0.12437811, -0.025695901, -0.056365624, -0.015389642, -0.03804987, 0.045304283, 0.0009684118, -0.0012951726, 0.011638488, -0.06881104], "bias": [0.01088573, 0.012155733, 0.011036726, 0.012341176]}, "pixel_shuffle": {"name": "pixel_shuffle", "type": "pixel_shuffle", "inputs": ["conv2d_last_tf"], "output": "canvas"}}} -------------------------------------------------------------------------------- /src/worker.js: -------------------------------------------------------------------------------- 1 | 2 | import {MP4Demuxer} from "./demuxer_mp4"; 3 | import {ArrayBufferTarget, FileSystemWritableFileStreamTarget, Muxer} from "mp4-muxer"; 4 | import WebSR from "../../websr/"; 5 | 6 | 7 | let gpu; 8 | let websr; 9 | let upscaled_canvas; 10 | let original_canvas; 11 | let resolution; 12 | let ctx; 13 | 14 | 15 | 16 | 17 | function getMP4Data(data, type, duration) { 18 | 19 | console.log("Fetching chunks"); 20 | 21 | return new Promise(function (resolve, reject) { 22 | 23 | let configToReturn; 24 | let dataToReturn =[]; 25 | let lastChunk = false; 26 | 27 | 28 | 29 | 30 | 31 | 32 | const demuxer = new MP4Demuxer(data, type, { 33 | onConfig(config) { 34 | configToReturn = config; 35 | if(configToReturn && lastChunk) return resolve({config: configToReturn, encoded_chunks: dataToReturn}); 36 | }, 37 | onData(chunks) { 38 | 39 | for(let chunk of chunks){ 40 | dataToReturn.push(chunk); 41 | } 42 | 43 | let last_time = chunks[chunks.length-1].timestamp/(1000*1000); 44 | 45 | 46 | if(Math.abs(duration - last_time) < 1) lastChunk = true; 47 | 48 | if(configToReturn && lastChunk) return resolve({config: configToReturn, encoded_chunks: dataToReturn}); 49 | }, 50 | setStatus: function (){} 51 | }); 52 | 53 | 54 | }); 55 | 56 | 57 | } 58 | 59 | 60 | const weights = require('./weights/cnn-2x-m-rl.json'); 61 | 62 | 63 | async function isSupported(){ 64 | gpu = await WebSR.initWebGPU(); 65 | 66 | postMessage({cmd: 'isSupported', data: gpu !== false}); 67 | } 68 | 69 | 70 | 71 | async function init(config){ 72 | 73 | if(!gpu) gpu = await WebSR.initWebGPU(); 74 | 75 | websr = new WebSR({ 76 | network_name: "anime4k/cnn-2x-m", 77 | weights, 78 | resolution: config.resolution, 79 | gpu: gpu, 80 | canvas: config.upscaled 81 | }); 82 | 83 | resolution = config.resolution; 84 | upscaled_canvas = config.upscaled; 85 | original_canvas = config.original; 86 | 87 | 88 | ctx = original_canvas.getContext('bitmaprenderer'); 89 | 90 | 91 | 92 | const bitmap2 = await createImageBitmap(config.bitmap, { 93 | resizeHeight: config.resolution.height*2, 94 | resizeWidth: config.resolution.width*2, 95 | }); 96 | await websr.render(config.bitmap); 97 | 98 | ctx.transferFromImageBitmap(bitmap2) 99 | 100 | 101 | } 102 | 103 | 104 | self.onmessage = async function (event){ 105 | 106 | 107 | if(!event.data.cmd) return; 108 | 109 | 110 | if(event.data.cmd === 'init'){ 111 | await init(event.data.data); 112 | } else if(event.data.cmd === 'isSupported'){ 113 | await isSupported(); 114 | } else if (event.data.cmd === 'process'){ 115 | await initRecording(event.data.data, event.data.duration, event.data.handle) 116 | } else if(event.data.cmd === 'network'){ 117 | await switchNetwork(event.data.data.name, event.data.data.weights, event.data.data.bitmap) 118 | } 119 | 120 | 121 | 122 | } 123 | 124 | async function switchNetwork(name, weights, bitmap){ 125 | 126 | 127 | websr.switchNetwork(name, weights); 128 | 129 | 130 | await websr.render(bitmap); 131 | 132 | } 133 | 134 | 135 | async function initRecording( data, duration, handle){ 136 | 137 | 138 | 139 | let bitrate = 5e6 * (resolution.width*resolution.height*4)/(1280*720); 140 | 141 | let videoData; 142 | let audioData; 143 | let writer; 144 | 145 | 146 | if(handle){ 147 | writer = await handle.createWritable(); 148 | } 149 | 150 | 151 | try { 152 | audioData = await getMP4Data(data, 'audio', duration); 153 | 154 | } catch (e) { 155 | console.log('No audio track found, skipping....'); 156 | 157 | } 158 | 159 | 160 | console.log("Audio data", audioData); 161 | 162 | try{ 163 | console.log("Truing to send data"); 164 | videoData = await getMP4Data(data, 'video', duration); 165 | } catch (e) { 166 | console.warn('No video data found'); 167 | postMessage({cmd: 'error', data: 'No video found'}); 168 | 169 | } 170 | 171 | console.log("Video data") 172 | const config = videoData.config; 173 | const encoded_chunks = videoData.encoded_chunks; 174 | 175 | 176 | const target = writer ? new FileSystemWritableFileStreamTarget(writer) : new ArrayBufferTarget(); 177 | 178 | 179 | const muxerOptions = 180 | { 181 | target: target, 182 | video: { 183 | codec: 'avc', 184 | width: resolution.width*2, 185 | height: resolution.height*2 186 | }, 187 | firstTimestampBehavior: 'offset', 188 | fastStart: 'in-memory' 189 | }; 190 | 191 | if(audioData){ 192 | muxerOptions.audio = { 193 | 194 | codec: 'aac', 195 | numberOfChannels: audioData.config.numberOfChannels, 196 | sampleRate: audioData.config.sampleRate 197 | 198 | } 199 | } 200 | 201 | 202 | const muxer = new Muxer(muxerOptions); 203 | 204 | 205 | let codec_string = resolution.width*resolution.height *4 > 921600 ? 'avc1.42003e': 'avc1.42001f'; 206 | 207 | 208 | 209 | const videoEncoderConfig = { 210 | codec: codec_string, 211 | width: resolution.width*2, 212 | height: resolution.height*2, 213 | bitrate: Math.round(bitrate), 214 | framerate: 1e6/videoData.encoded_chunks[0].duration, 215 | }; 216 | 217 | 218 | 219 | 220 | 221 | const decode_callbacks = []; 222 | 223 | // Set up a VideoDecoer. 224 | const decoder = new VideoDecoder({ 225 | output(frame) { 226 | 227 | const callback = decode_callbacks.shift(); 228 | callback(frame); 229 | }, 230 | error(e) { 231 | console.log("Decoder error"); 232 | console.log(e); 233 | 234 | postMessage({cmd: 'error', data: e.message}); 235 | 236 | } 237 | }); 238 | 239 | 240 | const encode_callbacks = []; 241 | 242 | const encoder = new VideoEncoder({ 243 | output: (chunk, meta) => { 244 | const callback = encode_callbacks.shift(); 245 | 246 | try { 247 | muxer.addVideoChunk(chunk, meta); 248 | } catch (e) { 249 | 250 | 251 | console.log("Muxing error"); 252 | console.log(e); 253 | postMessage({cmd: 'error', data: e.message}); 254 | } 255 | 256 | 257 | callback(); 258 | }, 259 | error: (e) => { 260 | 261 | console.log("Encoder error"); 262 | console.log(e); 263 | postMessage({cmd: 'error', data: e.message}); 264 | 265 | } 266 | }); 267 | 268 | 269 | encoder.configure(videoEncoderConfig); 270 | 271 | decoder.configure(config); 272 | 273 | 274 | const decode_promises = []; 275 | 276 | const decoder_buffer_length =20; 277 | 278 | for (let i = 0; i < Math.min(encoded_chunks.length, decoder_buffer_length); i ++){ 279 | 280 | let chunk = encoded_chunks[i]; 281 | 282 | decode_promises.push(new Promise(function (resolve, reject) { 283 | const callback = function (frame){ resolve(frame);} 284 | decode_callbacks.push(callback); 285 | })); 286 | 287 | try{ 288 | decoder.decode(chunk); 289 | 290 | console.log("Decodded queue size", decoder.decodeQueueSize); 291 | } catch (e) { 292 | 293 | console.log("Decoder Error"); 294 | console.log(e); 295 | 296 | postMessage({cmd: 'error', data: e.message}); 297 | } 298 | 299 | } 300 | 301 | const encode_promises = []; 302 | 303 | const start_time = performance.now(); 304 | 305 | let last_decode = performance.now(); 306 | 307 | let flush_check = setInterval(function () { 308 | 309 | if(performance.now() - last_decode > decoder_buffer_length && (encoded_chunks.length - current_frame < 10)) decoder.flush() 310 | 311 | }, 100); 312 | 313 | let current_frame; 314 | 315 | for (let i =0; i < decode_promises.length; i++){ 316 | 317 | const decode_promise = decode_promises[i]; 318 | const source_chunk = encoded_chunks[i]; 319 | 320 | const frame = await decode_promise; 321 | last_decode = performance.now(); 322 | 323 | 324 | const bitmap2 = await createImageBitmap(frame, 325 | { 326 | resizeHeight: resolution.height*2, 327 | resizeWidth: resolution.width*2,}); 328 | 329 | 330 | let render_promise = websr.render(frame); 331 | ctx.transferFromImageBitmap(bitmap2); 332 | //render_promise; 333 | 334 | // await websr.context.device.queue.onSubmittedWorkDone(); 335 | 336 | 337 | 338 | 339 | current_frame = i; 340 | 341 | const new_frame = new VideoFrame(upscaled_canvas,{ timestamp: frame.timestamp, duration: frame.duration, alpha: "discard"}); 342 | 343 | let progress = Math.floor((frame.timestamp/(1000*1000))/duration*100); 344 | 345 | let time_elapsed = performance.now() - start_time; 346 | 347 | if(time_elapsed > 1000){ 348 | const processing_rate = ((frame.timestamp/(1000*1000))/duration*100)/time_elapsed; 349 | let eta = Math.round(((100-progress)/processing_rate)/1000); 350 | 351 | postMessage({cmd: 'eta', data: prettyTime(eta)}) 352 | 353 | 354 | } else { 355 | postMessage({cmd: 'eta', data: 'calculating...'}) 356 | } 357 | 358 | 359 | postMessage({cmd: 'progress', data: progress}) 360 | 361 | 362 | 363 | encode_promises.push(new Promise(function (resolve, reject) { 364 | const callback = function (){ resolve();} 365 | encode_callbacks.push(callback); 366 | })); 367 | 368 | 369 | 370 | 371 | try{ 372 | 373 | 374 | 375 | if(encoder.encodeQueueSize >= 20){ 376 | await new Promise(function (resolve) { 377 | 378 | function check(){ 379 | if(encoder.encodeQueueSize < 20){ 380 | resolve(); 381 | } else { 382 | setTimeout(check, 100); 383 | } 384 | } 385 | 386 | check(); 387 | }) 388 | } 389 | 390 | 391 | encoder.encode(new_frame, {keyFrame: source_chunk.type === 'key'}); 392 | 393 | 394 | } catch (e) { 395 | 396 | 397 | console.log("Encoding error"); 398 | console.log(e); 399 | postMessage({cmd: 'error', data: e.message}); 400 | } 401 | 402 | 403 | frame.close(); 404 | new_frame.close(); 405 | 406 | 407 | if( i +decoder_buffer_length < encoded_chunks.length){ 408 | 409 | let chunk = encoded_chunks[i+decoder_buffer_length]; 410 | 411 | 412 | 413 | decode_promises.push(new Promise(function (resolve, reject) { 414 | const callback = function (frame){ resolve(frame);} 415 | decode_callbacks.push(callback); 416 | })); 417 | 418 | try{ 419 | 420 | decoder.decode(chunk); 421 | } catch (e) { 422 | } 423 | 424 | 425 | last_decode = performance.now(); 426 | } 427 | 428 | } 429 | 430 | clearInterval(flush_check); 431 | 432 | let last_encode = performance.now(); 433 | 434 | flush_check = setInterval(function () { 435 | 436 | if(performance.now() - last_encode > 1000) encoder.flush() 437 | 438 | }, 100); 439 | 440 | 441 | for (let i =0; i < encode_promises.length; i++){ 442 | 443 | const encode_promise = encode_promises[i]; 444 | await encode_promise; 445 | last_encode = performance.now(); 446 | 447 | } 448 | 449 | clearInterval(flush_check); 450 | 451 | 452 | try{ 453 | 454 | if(audioData) { 455 | 456 | const source_audio_chunks = audioData.encoded_chunks; 457 | 458 | for (let audio_chunk of source_audio_chunks){ 459 | muxer.addAudioChunk(audio_chunk); 460 | } 461 | 462 | } 463 | 464 | 465 | muxer.finalize(); 466 | 467 | 468 | if(writer){ 469 | await writer.close(); 470 | 471 | postMessage({cmd: 'finished', data: null}, []); 472 | } else{ 473 | 474 | postMessage({cmd: 'finished', data: muxer.target.buffer}, [muxer.target.buffer]); 475 | } 476 | 477 | 478 | 479 | 480 | 481 | } catch (e) { 482 | 483 | 484 | console.log("Err finishing"); 485 | console.log(e); 486 | 487 | postMessage({cmd: 'error', data: e.message}); 488 | 489 | } 490 | 491 | 492 | 493 | 494 | 495 | } 496 | 497 | 498 | 499 | 500 | 501 | function prettyTime(secs){ 502 | var sec_num = parseInt(secs, 10) 503 | var hours = Math.floor(sec_num / 3600) 504 | var minutes = Math.floor(sec_num / 60) % 60 505 | var seconds = sec_num % 60 506 | 507 | return [hours,minutes,seconds] 508 | .map(v => v < 10 ? "0" + v : v) 509 | .filter((v,i) => v !== "00" || i > 0) 510 | .join(":") 511 | } 512 | -------------------------------------------------------------------------------- /src/index.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 9 | 10 | 13 | 14 | 15 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 31 | Free AI Video Upscaler, no signup or installation required 32 | 33 | 44 | 45 | 46 | 47 | 48 | 54 | 55 | 56 | 57 | 58 |

Free AI Video Upscaler

59 |

Upscale videos with AI for free, right in your browser - no signups, installation or config necessary. It is fast, free and open source, but the quality is not as good as GPU-powered AI Upscaling software. 60 |

61 | 62 | 63 | This is a quick, free no-nonsense tool for upscaling videos with AI right in the browser. There is no software to install, and no registration or sign up required. All you need to do is input a video, and your browser will do all of the AI Upscaling and video processing. This software tool is completely free and open source, and works particularly well for animated content. 64 | I built it because from previous experience as a casual user who just wants to upscale a few videos you have around, it's surprisingly frustrating. There are paid tools like Topaz Labs which are excellent but also overkill for non-professional work, or open source projects like Video2X which require a lot of setup and configuration. This tool, in contrast, is designed to be quick, fast, free, simple and easy to use. It is based on my WebSR project, which is an open-source WebSDK for applying real-time super resolution to videos on the web. It works by porting several open source AI Upscaling algorithms like Anime4K and RealESRGAN into WebGPU. The WebSR SDK then allows you to easily apply these AI Upscaling (Super resolution) algorithms to each frame of a video directly in the browser. 65 | 66 |

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Your browser does not support , a required browser feature for this tool.

Try using the latest version of You can use the latest Chrome browser Chrome or You can use the latest Edge browser Edge on a 💻 Laptop or 🖥️ Desktop. 75 |

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For what it's worth, here's how it's supposed to work [YouTube link]

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88 | 89 | Loading 90 |
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An error ocurred while processing the video:

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Choose a video to upscale

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Upscaling to x. Output: ~

125 |

If you're looking for better quality upscaling, consider Fast AI Video Upscaler (fast, easy, paid) or Video2x (free, requires GPU and installation/config)

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136 | Upscaling Network 137 | 139 | 140 | 142 | 143 |   144 | 145 | 147 |   148 | 149 | 151 |
156 | Content Style 157 | 159 | 160 | 162 | 163 |   164 | 165 | 167 |   168 | 169 | 171 | 172 |
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Upscaling .Estimated time left:

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If you like the tool, please consider giving a like
on this YouTube video, it helps more people discover Free AI Video Upscaler

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233 |
234 | Souce code on Github.     © Sam Bhattacharyya 2025 235 |
236 | 237 |
238 | Issues, questions or suggestions, go here 239 |
240 | 241 |
242 | 243 | 244 | 245 | -------------------------------------------------------------------------------- /src/index.js: -------------------------------------------------------------------------------- 1 | import WebSR from '@websr/websr'; 2 | import { Muxer, ArrayBufferTarget, FileSystemWritableFileStreamTarget } from 'mp4-muxer'; 3 | import Alpine from 'alpinejs' 4 | import ImageCompare from './lib/image-compare-viewer.min'; 5 | import { MP4Demuxer } from "./demuxer_mp4"; 6 | 7 | 8 | import 'bootstrap'; 9 | import 'bootstrap/dist/css/bootstrap.min.css'; 10 | import "./index.css"; 11 | import "./lib/image-compare-viewer.min.css" 12 | const worker = new Worker(new URL('./worker.js', import.meta.url)); 13 | const progressVideo = document.createElement('video'); 14 | const progressCanvas = document.createElement('canvas'); 15 | const progressCtx = progressCanvas.getContext('2d'); 16 | 17 | let eta = ''; 18 | let pip = null; 19 | 20 | progressVideo.width = progressCanvas.width; 21 | progressVideo.height =progressCanvas.height; 22 | progressVideo.autoplay = true; 23 | progressVideo.muted = true; 24 | progressVideo.style.width = '300px'; 25 | progressVideo.style.height = '150px'; 26 | progressVideo.style.position = 'fixed'; 27 | progressVideo.style.top = '0px'; 28 | progressVideo.style.left = '0px'; 29 | progressVideo.style.visibility = 'hidden'; 30 | 31 | 32 | progressCanvas.style.visibility = 'hidden'; 33 | progressCanvas.id = "progress-canvas"; 34 | document.body.appendChild(progressCanvas); 35 | document.body.appendChild(progressVideo) 36 | 37 | 38 | let upscaled_canvas; 39 | let original_canvas; 40 | let video; 41 | let ctx; 42 | 43 | let size = 'medium'; 44 | let content = 'rl'; 45 | 46 | 47 | let tfliteModelP; 48 | let tfliteModel; 49 | 50 | let download_name; 51 | let data; 52 | let gpu; 53 | let websr; 54 | 55 | const weights = { 56 | 'large': 57 | { 58 | 'rl': require('./weights/cnn-2x-l-rl.json'), 59 | 'an': require('./weights/cnn-2x-l-an.json'), 60 | '3d': require('./weights/cnn-2x-l-3d.json'), 61 | }, 62 | 'medium': 63 | { 64 | 'rl': require('./weights/cnn-2x-m-rl.json'), 65 | 'an': require('./weights/cnn-2x-m-an.json'), 66 | '3d': require('./weights/cnn-2x-m-3d.json'), 67 | }, 68 | 'small': 69 | { 70 | 'rl': require('./weights/cnn-2x-s-rl.json'), 71 | 'an': require('./weights/cnn-2x-s-an.json'), 72 | '3d': require('./weights/cnn-2x-s-3d.json'), 73 | } 74 | } 75 | 76 | 77 | const networks = { 78 | 'small': { 79 | name: "anime4k/cnn-2x-s", 80 | }, 81 | 'medium': { 82 | name: "anime4k/cnn-2x-m", 83 | }, 84 | 'large': { 85 | name: "anime4k/cnn-2x-l", 86 | } 87 | } 88 | 89 | 90 | 91 | function uuidv4() { 92 | return "10000000-1000-4000-8000-100000000000".replace(/[018]/g, c => 93 | (c ^ crypto.getRandomValues(new Uint8Array(1))[0] & 15 >> c / 4).toString(16) 94 | ); 95 | } 96 | 97 | document.addEventListener("DOMContentLoaded", index); 98 | 99 | let tf; 100 | let tflite; 101 | let user_id; 102 | 103 | //=================== Initial Load =========================== 104 | 105 | 106 | function identify_user(){ 107 | 108 | 109 | user_id = localStorage.getItem("user_id"); 110 | 111 | if(!user_id) { 112 | user_id = uuidv4(); 113 | localStorage.setItem("user_id", user_id); 114 | } 115 | 116 | Sprig('setUserId', user_id); 117 | } 118 | 119 | 120 | async function index() { 121 | 122 | Alpine.store('state', 'init'); 123 | 124 | Alpine.start(); 125 | document.body.style.display = "block"; 126 | 127 | 128 | upscaled_canvas = document.getElementById("upscaled"); 129 | original_canvas = document.getElementById('original'); 130 | 131 | if(!"VideoEncoder" in window) return showUnsupported("WebCodecs"); 132 | 133 | if(! window.showSaveFilePicker) return showUnsupported("File Write System API") 134 | 135 | 136 | 137 | worker.postMessage({cmd: 'isSupported'}) 138 | 139 | 140 | window.chooseFile = chooseFile; 141 | 142 | try{ 143 | await import( '@tensorflow/tfjs-backend-cpu'); 144 | tf = await import('@tensorflow/tfjs-core'); 145 | tflite = await import('@tensorflow/tfjs-tflite'); 146 | 147 | tfliteModelP = tflite.loadTFLiteModel('./content_detection_mobilenet_v3.tflite', {numThreads: 1, enableProfiling: false, maxProfilingBufferEntries: 1024}); 148 | identify_user(); 149 | 150 | } catch (e) { 151 | Sentry.captureException(e); 152 | } 153 | 154 | 155 | 156 | 157 | 158 | } 159 | 160 | function showUnsupported(text) { 161 | Alpine.store('component', text); 162 | Alpine.store('state', 'unsupported'); 163 | 164 | gtag('event', 'unsupported', {}); 165 | } 166 | 167 | function chooseFile(e) { 168 | const input = document.createElement('input'); 169 | input.type = 'file'; 170 | input.onchange = loadVideo; 171 | input.accept = "video/mp4"; 172 | input.click(); 173 | } 174 | 175 | //=================== Preview =========================== 176 | 177 | 178 | function loadVideo(input){ 179 | 180 | const file = input.target.files[0]; 181 | 182 | const reader = new FileReader(); 183 | 184 | Alpine.store('state', 'loading'); 185 | 186 | reader.onload = function (e) { 187 | data = reader.result; 188 | 189 | setupPreview(data); 190 | } 191 | 192 | reader.readAsArrayBuffer(file); 193 | 194 | download_name = file.name.split(".")[0] + "-upscaled.mp4"; 195 | Alpine.store('download_name', download_name); 196 | Alpine.store('filename', file.name); 197 | 198 | 199 | gtag('event', 'load_video', {}); 200 | } 201 | 202 | 203 | 204 | async function setupPreview(data) { 205 | 206 | 207 | video = document.createElement('video'); 208 | 209 | 210 | const fileBlob = new Blob([data], {type: "video/mp4"}); 211 | 212 | video.src = URL.createObjectURL(fileBlob); 213 | 214 | 215 | 216 | const imageCompare = document.getElementById('image-compare-outer'); 217 | 218 | 219 | 220 | video.onloadeddata = async function (){ 221 | 222 | 223 | 224 | Alpine.store('width', video.videoWidth); 225 | Alpine.store('height', video.videoHeight); 226 | upscaled_canvas.width = video.videoWidth*2; 227 | upscaled_canvas.height = video.videoHeight*2; 228 | original_canvas.width = video.videoWidth*2; 229 | original_canvas.height = video.videoHeight*2; 230 | 231 | 232 | imageCompare.style.height = '318px'; 233 | imageCompare.style.width = `${Math.round(video.videoWidth/video.videoHeight*318)}px` 234 | imageCompare.style.margin = 'auto'; 235 | imageCompare.style.position = 'relative'; 236 | 237 | 238 | new ImageCompare(document.getElementById('image-compare')).mount(); 239 | video.currentTime = video.duration * 0.2 || 0; 240 | if(video.requestVideoFrameCallback) video.requestVideoFrameCallback(showPreview); 241 | else requestAnimationFrame(showPreview); 242 | 243 | } 244 | 245 | 246 | 247 | 248 | async function showPreview(){ 249 | 250 | gtag('event', 'preview', {}); 251 | 252 | const fullScreenButton = document.getElementById('full-screen'); 253 | 254 | 255 | window.initRecording = initRecording; 256 | window.fullScreenPreview = fullScreenPreview; 257 | 258 | const bitmap = await createImageBitmap(video); 259 | 260 | 261 | const upscaled = upscaled_canvas.transferControlToOffscreen(); 262 | const original = original_canvas.transferControlToOffscreen(); 263 | 264 | 265 | worker.postMessage({cmd: "init", data: { 266 | bitmap, 267 | upscaled, 268 | original, 269 | resolution: { 270 | width: video.videoWidth, 271 | height: video.videoHeight 272 | } 273 | 274 | }}, [bitmap, upscaled, original]); 275 | 276 | 277 | // video.style.height = '100%'; 278 | 279 | const contentDetectionCanvas = document.createElement('canvas'); 280 | contentDetectionCanvas.width = 224; 281 | contentDetectionCanvas.height = 224; 282 | const contentDetectionCtx = contentDetectionCanvas.getContext('2d', {willReadFrequently: true}); 283 | 284 | let detected= null; 285 | 286 | 287 | async function detectContentType(){ 288 | 289 | const preds = { 290 | 'animation': [], 291 | 'rl': [] 292 | } 293 | 294 | for (let i=0; i < 5; i++){ 295 | 296 | video.currentTime = (i/10 + 0.1)*video.duration; 297 | 298 | if(video.requestVideoFrameCallback) await new Promise((resolve => video.requestVideoFrameCallback(resolve))); 299 | else await new Promise((resolve => requestAnimationFrame(resolve))); 300 | 301 | 302 | contentDetectionCtx.drawImage(video, video.videoWidth/2-112, video.videoHeight/2-112, 224, 224, 0, 0, 224, 224 ); 303 | 304 | const img = tf.browser.fromPixels(contentDetectionCanvas); 305 | 306 | 307 | const input = tf.div(tf.expandDims(img), 255); 308 | 309 | let outputTensor = tfliteModel.predict(input); 310 | 311 | const values = outputTensor.dataSync(); 312 | 313 | preds['animation'].push(values[0]); 314 | preds['rl'].push(values[1]); 315 | 316 | 317 | } 318 | video.currentTime = video.duration * 0.2 || 0; 319 | 320 | if(video.requestVideoFrameCallback) await new Promise((resolve => video.requestVideoFrameCallback(resolve))); 321 | else await new Promise((resolve => requestAnimationFrame(resolve))); 322 | 323 | 324 | const animation_score = preds['animation'].reduce((partialSum, a)=> partialSum +a, 0); 325 | const rl_score = preds['rl'].reduce((partialSum, a)=> partialSum +a, 0); 326 | 327 | const unk_thresh = 2; 328 | 329 | if(animation_score - rl_score > unk_thresh) return 'an' 330 | else if (rl_score - animation_score > unk_thresh) return 'rl'; 331 | else return null; 332 | 333 | 334 | 335 | } 336 | 337 | 338 | try{ 339 | tfliteModel = await tfliteModelP; 340 | 341 | detected = await detectContentType(); 342 | } catch (e) { 343 | 344 | console.warn('Unable to load TFLite Model'); 345 | } 346 | 347 | 348 | 349 | if(detected){ 350 | content = detected; 351 | await updateNetwork(); 352 | Alpine.store('style', content); 353 | } else { 354 | // Just a guess 355 | // I tried training a 3 class network, but it was producing really innacurate results compared to just real life vs 2d animation 356 | // Decided I'd rather do a good job on 2d animations and real life, and then show a menu if it's maybe something else or we don't know 357 | content = '3d'; 358 | await updateNetwork(); 359 | Alpine.store('style', 'unknown'); 360 | } 361 | 362 | 363 | 364 | 365 | 366 | 367 | 368 | 369 | 370 | function setFullScreenLocation(){ 371 | const containerWidth = Math.round(video.videoWidth/video.videoHeight*318); 372 | const containerHeight = 318; 373 | 374 | // Position at bottom-right of the preview container (with small padding) 375 | fullScreenButton.style.left = `${imageCompare.offsetLeft + containerWidth - 20}px`; 376 | fullScreenButton.style.top = `${imageCompare.offsetTop + containerHeight - 20}px`; 377 | } 378 | 379 | setTimeout(setFullScreenLocation, 20); 380 | setTimeout(setFullScreenLocation, 60); 381 | setTimeout(setFullScreenLocation, 200); 382 | 383 | 384 | 385 | 386 | 387 | imageCompare.addEventListener('fullscreenchange', function () { 388 | if(!document.fullscreenElement){ 389 | // Reset canvas styles 390 | upscaled_canvas.style.width = ``; 391 | upscaled_canvas.style.height = ``; 392 | original_canvas.style.width = ``; 393 | original_canvas.style.height = ``; 394 | 395 | // Reset container styles to original preview dimensions 396 | const imageCompareOuter = document.getElementById('image-compare-outer'); 397 | const imageCompareInner = document.getElementById('image-compare'); 398 | 399 | // Reset outer container 400 | imageCompareOuter.style.width = ``; 401 | imageCompareOuter.style.height = ``; 402 | imageCompareOuter.style.backgroundColor = ``; 403 | imageCompareOuter.style.display = ``; 404 | imageCompareOuter.style.justifyContent = ``; 405 | imageCompareOuter.style.alignItems = ``; 406 | 407 | // Reset inner container to original preview size 408 | imageCompareInner.style.height = '318px'; 409 | imageCompareInner.style.width = `${Math.round(video.videoWidth/video.videoHeight*318)}px`; 410 | imageCompareInner.style.margin = 'auto'; 411 | imageCompareInner.style.position = 'relative'; 412 | } 413 | }); 414 | 415 | let bitrate = getBitrate(); 416 | 417 | const estimated_size = (bitrate/8)*video.duration + (128/8)*video.duration; // Assume 128 kbps audio 418 | 419 | if(estimated_size > 100*1024*1024){ 420 | Alpine.store('target', 'writer'); 421 | } else { 422 | Alpine.store('target', 'blob'); 423 | } 424 | 425 | const quota = (await navigator.storage.estimate()).quota; 426 | 427 | if(estimated_size > quota){ 428 | return showError(`The video is too big. It would output a file of ${humanFileSize(estimated_size)} but the browser can only write files up to ${humanFileSize(quota)}`); 429 | } 430 | 431 | 432 | Alpine.store('size', humanFileSize(estimated_size)) 433 | 434 | 435 | function canvasFullScreen(){ 436 | // Calculate aspect ratios 437 | const videoAspectRatio = video.videoWidth / video.videoHeight; 438 | const screenAspectRatio = window.innerWidth / window.innerHeight; 439 | 440 | let displayWidth, displayHeight; 441 | 442 | const imageCompareOuter = document.getElementById('image-compare-outer'); 443 | const imageCompareInner = document.getElementById('image-compare'); 444 | 445 | // If video is wider than screen, fit to width (letterbox on top/bottom) 446 | if (videoAspectRatio > screenAspectRatio) { 447 | displayWidth = window.innerWidth; 448 | displayHeight = window.innerWidth / videoAspectRatio; 449 | } 450 | // If video is taller than screen, fit to height (pillarbox on sides) 451 | else { 452 | displayWidth = window.innerHeight * videoAspectRatio; 453 | displayHeight = window.innerHeight; 454 | } 455 | 456 | // Style the outer container to fill screen with black background and center content 457 | imageCompareOuter.style.width = `${window.innerWidth}px`; 458 | imageCompareOuter.style.height = `${window.innerHeight}px`; 459 | imageCompareOuter.style.backgroundColor = 'black'; 460 | imageCompareOuter.style.display = 'flex'; 461 | imageCompareOuter.style.justifyContent = 'center'; 462 | imageCompareOuter.style.alignItems = 'center'; 463 | 464 | 465 | console.log("Image Compare Outer", imageCompareOuter); 466 | console.log("Image Compare Inner", imageCompareInner); 467 | // Size the inner container to maintain aspect ratio 468 | imageCompareInner.style.width = `${displayWidth}px`; 469 | imageCompareInner.style.height = `${displayHeight}px`; 470 | 471 | // Let the canvases fill their parent container 472 | upscaled_canvas.style.width = `${displayWidth}px`; 473 | upscaled_canvas.style.height = `${displayHeight}px`; 474 | original_canvas.style.width = `${displayWidth}px`; 475 | original_canvas.style.height = `${displayHeight}px`; 476 | } 477 | 478 | async function fullScreenPreview(e) { 479 | imageCompare.requestFullscreen(); 480 | setTimeout(canvasFullScreen, 20); 481 | setTimeout(canvasFullScreen, 60); 482 | setTimeout(canvasFullScreen, 200); 483 | 484 | } 485 | 486 | 487 | Alpine.store('state', 'preview'); 488 | 489 | 490 | Sprig('setAttributes',{ 491 | content: content, 492 | width: video.videoWidth, 493 | height: video.videoHeight 494 | }); 495 | 496 | setTimeout(function () { 497 | Sprig('identifyAndTrack', { 498 | eventName: 'preview', 499 | userId: user_id, 500 | 501 | }); 502 | 503 | gtag('event', 'sprig', {}); 504 | 505 | 506 | }, 5000); 507 | 508 | 509 | window.switchNetworkSize = async function(el){ 510 | if(el.value !== size){ 511 | size = el.value; 512 | 513 | await updateNetwork(); 514 | } 515 | } 516 | 517 | window.switchNetworkStyle = async function(el){ 518 | if(el.value !== content){ 519 | content = el.value; 520 | 521 | await updateNetwork(); 522 | } 523 | } 524 | 525 | 526 | 527 | } 528 | 529 | } 530 | 531 | 532 | worker.onmessage = function (event) { 533 | 534 | if(event.data.cmd === 'isSupported'){ 535 | 536 | 537 | const supported = event.data.data; 538 | 539 | 540 | if(!supported) return showUnsupported("WebGPU"); 541 | 542 | 543 | } else if(event.data.cmd === 'progress'){ 544 | Alpine.store('progress', event.data.data); 545 | Alpine.store('state', 'processing'); 546 | 547 | 548 | progressView(event.data.data) 549 | 550 | 551 | } else if (event.data.cmd === 'process'){ 552 | 553 | } else if(event.data.cmd === 'error'){ 554 | 555 | showError(event.data.data); 556 | 557 | if(pip){ 558 | document.exitPictureInPicture(); 559 | } 560 | 561 | } else if(event.data.cmd === 'eta'){ 562 | 563 | Alpine.store('eta', event.data.data) 564 | eta = event.data.data; 565 | 566 | } else if(event.data.cmd === 'finished'){ 567 | Alpine.store('state', 'complete'); 568 | const blob = new Blob([event.data.data], {type: "video/mp4"}); 569 | Alpine.store('download_url', window.URL.createObjectURL(blob)); 570 | 571 | if(pip){ 572 | document.exitPictureInPicture(); 573 | } 574 | } 575 | 576 | 577 | } 578 | 579 | 580 | function progressView(progress){ 581 | 582 | 583 | const w = progressCanvas.width; 584 | const h =progressCanvas.height; 585 | 586 | progressCtx.clearRect(0, 0, w, h); 587 | 588 | progressCtx.fillStyle = "white"; 589 | progressCtx.fillRect(0, 0, w, h); 590 | 591 | progressCtx.fillStyle = "#bfdbfe"; 592 | progressCtx.fillRect(0, 0, Math.round(w*progress/100), h); 593 | progressCtx.font = "bold 32px Manrope"; 594 | progressCtx.textAlign = 'center'; 595 | 596 | progressCtx.fillStyle = "#232554"; 597 | progressCtx.fillText('Free AI Video Upscaler', w/2, 50); 598 | 599 | progressCtx.font = "14px Manrope"; 600 | progressCtx.textAlign = 'center'; 601 | 602 | progressCtx.fillText(download_name, w/2, 80); 603 | 604 | progressCtx.font = "bold 48px Manrope"; 605 | progressCtx.textAlign = 'center'; 606 | 607 | progressCtx.fillStyle = "#2563eb"; 608 | progressCtx.fillText(`${progress}%`, w/2, h/2+30); 609 | 610 | 611 | progressCtx.font = "14px Manrope"; 612 | progressCtx.textAlign = 'center'; 613 | progressCtx.fillStyle = "#232554"; 614 | progressCtx.fillText(`Time remaining: ${eta}`, w/2, h/2 + 80); 615 | 616 | } 617 | 618 | async function updateNetwork(){ 619 | 620 | 621 | const bitmap = await createImageBitmap(video) 622 | 623 | worker.postMessage({cmd: 'network', data: { 624 | name: networks[size].name, 625 | bitmap, 626 | weights:weights[size][content] 627 | }}) 628 | 629 | 630 | } 631 | 632 | 633 | //=================== Process =========================== 634 | 635 | async function initRecording(){ 636 | 637 | 638 | Alpine.store('state', 'loading'); 639 | 640 | const stream = progressCanvas.captureStream(); 641 | progressVideo.srcObject = stream; 642 | 643 | 644 | progressVideo.onloadedmetadata= async function(){ 645 | 646 | console.log("Loaded data") 647 | pip = await progressVideo.requestPictureInPicture(); 648 | 649 | progressCanvas.width = pip.width; 650 | progressCanvas.height = pip.height; 651 | } 652 | 653 | 654 | 655 | let bitrate = getBitrate(); 656 | const estimated_size = (bitrate/8)*video.duration + (128/8)*video.duration; // Assume 128 kbps audio 657 | 658 | let handle; 659 | 660 | // Max Blob size - 100 MB 661 | if(estimated_size > 100*1024*1024){ 662 | try{ 663 | handle = await showFilePicker(); 664 | } catch (e) { 665 | console.warn("User aborted request"); 666 | return Alpine.store('state', 'preview'); 667 | } 668 | 669 | } 670 | 671 | 672 | worker.postMessage({cmd: "process", data, duration: video.duration, handle}, [data]); 673 | 674 | 675 | 676 | 677 | 678 | 679 | 680 | 681 | } 682 | 683 | function showError(message){ 684 | Alpine.store('state', 'error'); 685 | Alpine.store('error', message); 686 | 687 | } 688 | 689 | 690 | function getBitrate() { 691 | 692 | return 5e6 * (video.videoWidth*video.videoHeight*4)/(1280*720); 693 | } 694 | 695 | function humanFileSize(bytes, si=false, dp=1) { 696 | const thresh = si ? 1000 : 1024; 697 | 698 | if (Math.abs(bytes) < thresh) { 699 | return bytes + ' B'; 700 | } 701 | 702 | const units = si 703 | ? ['kB', 'MB', 'GB', 'TB', 'PB', 'EB', 'ZB', 'YB'] 704 | : ['KiB', 'MiB', 'GiB', 'TiB', 'PiB', 'EiB', 'ZiB', 'YiB']; 705 | let u = -1; 706 | const r = 10**dp; 707 | 708 | do { 709 | bytes /= thresh; 710 | ++u; 711 | } while (Math.round(Math.abs(bytes) * r) / r >= thresh && u < units.length - 1); 712 | 713 | 714 | return bytes.toFixed(dp) + ' ' + units[u]; 715 | } 716 | 717 | 718 | 719 | function prettyTime(secs){ 720 | var sec_num = parseInt(secs, 10) 721 | var hours = Math.floor(sec_num / 3600) 722 | var minutes = Math.floor(sec_num / 60) % 60 723 | var seconds = sec_num % 60 724 | 725 | return [hours,minutes,seconds] 726 | .map(v => v < 10 ? "0" + v : v) 727 | .filter((v,i) => v !== "00" || i > 0) 728 | .join(":") 729 | } 730 | 731 | async function showFilePicker(){ 732 | const handle = await window.showSaveFilePicker({ 733 | startIn: 'videos', 734 | suggestedName: download_name, 735 | types: [{ 736 | description: 'Video File', 737 | accept: {'video/mp4' :['.mp4']} 738 | }], 739 | }); 740 | 741 | 742 | return handle 743 | } 744 | 745 | 746 | 747 | 748 | 749 | 750 | 751 | 752 | 753 | 754 | 755 | 756 | -------------------------------------------------------------------------------- /src/weights/cnn-2x-m-an.json: -------------------------------------------------------------------------------- 1 | {"name": "anime4k/cnn-2x-m", "layers": {"conv2d_tf": {"name": "conv2d_tf", "type": "conv", "inputs": ["input_image"], "output": "conv2d_tf", "weights": [-0.072145514, 0.00028308097, -0.02246936, 0.024812723, -0.07055249, -0.026193684, 0.06250765, 0.10273287, 0.023989726, 0.059850752, 0.12388443, -0.05610249, 0.0, 0.0, 0.0, 0.0, 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