Created using Colaboratory
This commit is contained in:
Eloi Moliner Juanpere
parent
f88e6259fa
commit
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167
colab/demo.ipynb
167
colab/demo.ipynb
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "view-in-github",
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"colab_type": "text"
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},
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"source": [
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"<a href=\"https://colab.research.google.com/github/eloimoliner/denoising-historical-recordings/blob/colab/colab/demo.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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]
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},
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{
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"cell_type": "markdown",
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"source": [
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@ -21,130 +11,34 @@
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "dd70762d",
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "dd70762d",
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"outputId": "24457550-e127-4d73-db47-297147b68f09"
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"outputs": [
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{
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"output_type": "stream",
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"text": [
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"Cloning into 'denoising-historical-recordings'...\n",
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"remote: Enumerating objects: 181, done.\u001b[K\n",
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"remote: Counting objects: 100% (181/181), done.\u001b[K\n",
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"remote: Compressing objects: 100% (157/157), done.\u001b[K\n",
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"remote: Total 181 (delta 64), reused 98 (delta 16), pack-reused 0\u001b[K\n",
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"Receiving objects: 100% (181/181), 104.80 KiB | 17.47 MiB/s, done.\n",
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"Resolving deltas: 100% (64/64), done.\n",
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"--2022-01-20 14:40:36-- https://github.com/eloimoliner/denoising-historical-recordings/releases/download/v0.0/checkpoint.zip\n",
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"Resolving github.com (github.com)... 140.82.112.3\n",
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"--2022-01-20 14:40:36-- https://objects.githubusercontent.com/github-production-release-asset-2e65be/401385223/354cec4e-d8be-4126-8b32-9e6509bca537?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWNJYAX4CSVEH53A%2F20220120%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20220120T144036Z&X-Amz-Expires=300&X-Amz-Signature=1cf02e4ae397a518db9da71aad3dfc7dcb844c520bbfc49398ca6a54171ad637&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=401385223&response-content-disposition=attachment%3B%20filename%3Dcheckpoint.zip&response-content-type=application%2Foctet-stream\n",
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"Resolving objects.githubusercontent.com (objects.githubusercontent.com)... 185.199.110.133, 185.199.108.133, 185.199.111.133, ...\n",
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"Connecting to objects.githubusercontent.com (objects.githubusercontent.com)|185.199.110.133|:443... connected.\n",
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"HTTP request sent, awaiting response... 200 OK\n",
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"Length: 264031940 (252M) [application/octet-stream]\n",
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"Saving to: ‘checkpoint.zip’\n",
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"\n",
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"checkpoint.zip 100%[===================>] 251.80M 215MB/s in 1.2s \n",
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"\n",
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"2022-01-20 14:40:38 (215 MB/s) - ‘checkpoint.zip’ saved [264031940/264031940]\n",
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"\n",
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"Archive: checkpoint.zip\n",
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" inflating: denoising-historical-recordings/experiments/trained_model/checkpoint \n",
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" inflating: denoising-historical-recordings/experiments/trained_model/checkpoint.data-00000-of-00001 \n",
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" inflating: denoising-historical-recordings/experiments/trained_model/checkpoint.index \n"
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]
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}
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],
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"cell_type": "markdown",
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"source": [
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"### Instructions for running:\n",
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"\n",
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"* Make sure to use a GPU runtime, click: __Runtime >> Change Runtime Type >> GPU__\n",
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"* Press ▶️ on the left of each of the cells\n",
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"* View the code: Double-click any of the cells\n",
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"* Hide the code: Double click the right side of the cell\n"
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],
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"metadata": {
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"id": "8UON6ncSApA9"
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},
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"id": "8UON6ncSApA9"
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},
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{
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"cell_type": "code",
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"source": [
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"#@title #Install and Import\n",
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"\n",
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"#@markdown Installing the required data and dependencies. This step might take some minutes\n",
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"\n",
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"#download the files\n",
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"! git clone https://github.com/eloimoliner/denoising-historical-recordings.git\n",
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"! wget https://github.com/eloimoliner/denoising-historical-recordings/releases/download/v0.0/checkpoint.zip\n",
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"! unzip checkpoint.zip -d denoising-historical-recordings/experiments/trained_model/"
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]
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},
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{
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"cell_type": "code",
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"source": [
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"! unzip checkpoint.zip -d denoising-historical-recordings/experiments/trained_model/\n",
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"\n",
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"%cd denoising-historical-recordings\n",
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"\n",
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"%cd denoising-historical-recordings"
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],
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "HmHRpa5eloy2",
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"outputId": "8666da99-94e0-4ed2-afca-f9e31b37c84c"
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},
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"id": "HmHRpa5eloy2",
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"execution_count": 2,
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"/content/denoising-historical-recordings\n"
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]
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}
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]
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},
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{
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"cell_type": "code",
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"source": [
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""
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],
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"metadata": {
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"id": "gvd6KZkTlyhR"
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},
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"id": "gvd6KZkTlyhR",
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"execution_count": 12,
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"outputs": []
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},
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{
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"cell_type": "code",
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"source": [
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""
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],
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "nmic9hVzmSj6",
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"outputId": "4d1a91d8-e994-48d3-d27b-f3c0b933b60e"
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},
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"id": "nmic9hVzmSj6",
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"execution_count": 3,
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"Collecting hydra-core==0.11.3\n",
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" Downloading hydra_core-0.11.3-py3-none-any.whl (72 kB)\n",
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"\u001b[?25l\r\u001b[K |████▌ | 10 kB 34.0 MB/s eta 0:00:01\r\u001b[K |█████████ | 20 kB 38.2 MB/s eta 0:00:01\r\u001b[K |█████████████▋ | 30 kB 43.5 MB/s eta 0:00:01\r\u001b[K |██████████████████▏ | 40 kB 47.4 MB/s eta 0:00:01\r\u001b[K |██████████████████████▊ | 51 kB 33.6 MB/s eta 0:00:01\r\u001b[K |███████████████████████████▎ | 61 kB 36.8 MB/s eta 0:00:01\r\u001b[K |███████████████████████████████▉| 71 kB 27.7 MB/s eta 0:00:01\r\u001b[K |████████████████████████████████| 72 kB 649 kB/s \n",
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"\u001b[?25hCollecting omegaconf<1.5,>=1.4\n",
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" Downloading omegaconf-1.4.1-py3-none-any.whl (14 kB)\n",
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"Requirement already satisfied: PyYAML in /usr/local/lib/python3.7/dist-packages (from omegaconf<1.5,>=1.4->hydra-core==0.11.3) (3.13)\n",
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"Requirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from omegaconf<1.5,>=1.4->hydra-core==0.11.3) (1.15.0)\n",
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"Installing collected packages: omegaconf, hydra-core\n",
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"Successfully installed hydra-core-0.11.3 omegaconf-1.4.1\n"
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]
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}
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]
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},
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{
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"cell_type": "code",
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"source": [
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"#install dependencies\n",
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"! pip install hydra-core==0.11.3\n",
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"\n",
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" return denoised_data"
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],
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"metadata": {
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"cellView": "form",
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"id": "TQBDTmO4mUBx"
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},
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"id": "TQBDTmO4mUBx",
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{
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"cell_type": "code",
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"source": [
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"#@title #Upload file to denoise\n",
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"\n",
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"#@markdown Execute this cell to upload a single audio recording you would like to denoise (accepted extensions: .wav, .flac, .mp3)\n",
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"from google.colab import files\n",
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"uploaded=files.upload()"
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],
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"base_uri": "https://localhost:8080/",
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"height": 72
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},
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"cellView": "form",
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"id": "50Kmdy6AtbhW",
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"outputId": "2d05860c-536d-45f8-92b4-d2ba6f5a54c5"
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},
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{
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"cell_type": "code",
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"source": [
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"#@title #Denoise\n",
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"\n",
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"#@markdown Execute this cell to denoise the uploaded file\n",
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"for fn in uploaded.keys():\n",
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" print('Denoising uploaded file \"{name}\"'.format(\n",
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" name=fn))\n",
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"cellView": "form",
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"id": "0po6zpvrylc2",
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"outputId": "173f5355-2939-41fe-c702-591aa752fc7e"
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},
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{
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"cell_type": "code",
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"source": [
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"#@title #Download\n",
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"\n",
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"#@markdown Execute this cell to download the denoised recording\n",
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"files.download(wav_output_name)"
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],
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"metadata": {
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"base_uri": "https://localhost:8080/",
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"height": 17
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},
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"cellView": "form",
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"id": "3tEshWBezYvf",
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"outputId": "54588c26-0b3c-42bf-aca2-8316ab54603f"
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},
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},
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"colab": {
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"name": "demo.ipynb",
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"provenance": [],
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"include_colab_link": true
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"provenance": []
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},
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"accelerator": "GPU"
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},
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