Created using Colaboratory
This commit is contained in:
Eloi Moliner Juanpere
parent
4fb2c52fbb
commit
f88e6259fa
257
colab/demo.ipynb
257
colab/demo.ipynb
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"execution_count": 2,
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"execution_count": 1,
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"id": "dd70762d",
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"id": "dd70762d",
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"metadata": {
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"metadata": {
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"colab": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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"base_uri": "https://localhost:8080/"
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"id": "dd70762d",
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"name": "stdout",
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"name": "stdout",
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"text": [
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"text": [
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"Cloning into 'denoising-historical-recordings'...\n",
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"Cloning into 'denoising-historical-recordings'...\n",
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"remote: Enumerating objects: 177, done.\u001b[K\n",
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"remote: Enumerating objects: 181, done.\u001b[K\n",
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"remote: Total 177 (delta 63), reused 99 (delta 16), pack-reused 0\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% (177/177), 97.29 KiB | 4.86 MiB/s, done.\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% (63/63), 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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"HTTP request sent, awaiting response... 302 Found\n",
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"Location: 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 [following]\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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"checkpoint.zip 100%[===================>] 251.80M 215MB/s in 1.2s \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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"base_uri": "https://localhost:8080/"
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"id": "HmHRpa5eloy2",
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"cell_type": "code",
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"cell_type": "code",
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"source": [
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"source": [
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"#install dependencies\n",
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""
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"! pip install hydra-core==0.11.3"
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],
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],
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"metadata": {
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"metadata": {
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"colab": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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"id": "nmic9hVzmSj6",
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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 19.6 MB/s eta 0:00:01\r\u001b[K |█████████ | 20 kB 12.0 MB/s eta 0:00:01\r\u001b[K |█████████████▋ | 30 kB 8.9 MB/s eta 0:00:01\r\u001b[K |██████████████████▏ | 40 kB 7.9 MB/s eta 0:00:01\r\u001b[K |██████████████████████▊ | 51 kB 5.3 MB/s eta 0:00:01\r\u001b[K |███████████████████████████▎ | 61 kB 5.4 MB/s eta 0:00:01\r\u001b[K |███████████████████████████████▉| 71 kB 5.7 MB/s eta 0:00:01\r\u001b[K |████████████████████████████████| 72 kB 372 kB/s \n",
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"\u001b[?25hCollecting omegaconf<1.5,>=1.4\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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" Downloading omegaconf-1.4.1-py3-none-any.whl (14 kB)\n",
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"Requirement already satisfied: six in /usr/local/lib/python3.7/site-packages (from omegaconf<1.5,>=1.4->hydra-core==0.11.3) (1.15.0)\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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"Collecting PyYAML\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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" Downloading PyYAML-6.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (596 kB)\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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"\u001b[?25hInstalling collected packages: PyYAML, omegaconf, hydra-core\n",
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"Successfully installed PyYAML-6.0 hydra-core-0.11.3 omegaconf-1.4.1\n"
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"cell_type": "code",
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"source": [
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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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"#All the code goes here\n",
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"import unet\n",
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"import unet\n",
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"import tensorflow as tf\n",
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"import tensorflow as tf\n",
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"import soundfile as sf\n",
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"import soundfile as sf\n",
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"from tqdm import tqdm\n",
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"from tqdm import tqdm\n",
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"import scipy.signal\n",
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"import scipy.signal\n",
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"import hydra\n",
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"import hydra\n",
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"import os"
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"import os\n",
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],
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"metadata": {
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"id": "TQBDTmO4mUBx"
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"id": "TQBDTmO4mUBx",
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"execution_count": 17,
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"cell_type": "code",
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"source": [
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"#workaround to load hydra conf file\n",
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"#workaround to load hydra conf file\n",
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"import yaml\n",
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"import yaml\n",
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"from pathlib import Path\n",
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"from pathlib import Path\n",
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" __setattr__ = dict.__setitem__\n",
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" __setattr__ = dict.__setitem__\n",
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" __delattr__ = dict.__delitem__\n",
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" __delattr__ = dict.__delitem__\n",
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"args=dotdict(args)\n",
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"args=dotdict(args)\n",
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"unet_args=dotdict(args.unet)"
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],
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"metadata": {
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"id": "yMI9sIUYo9Lp"
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"cell_type": "code",
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"source": [
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"path_experiment=str(args.path_experiment)\n",
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"path_experiment=str(args.path_experiment)\n",
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"\n",
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"\n",
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"unet_model = unet.build_model_denoise(unet_args=unet_args)\n",
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"unet_model = unet.build_model_denoise(unet_args=unet_args)\n",
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"\n",
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"\n",
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"ckpt=os.path.join(\"/content/denoising-historical-recordings\",path_experiment, 'checkpoint')\n",
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"ckpt=os.path.join(\"/content/denoising-historical-recordings\",path_experiment, 'checkpoint')\n",
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"unet_model.load_weights(ckpt)"
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"unet_model.load_weights(ckpt)\n",
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],
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"\n",
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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"id": "cbdPyEpAp7s0",
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"id": "cbdPyEpAp7s0",
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"execution_count": 67,
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"output_type": "execute_result",
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"data": {
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"text/plain": [
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"<tensorflow.python.training.tracking.util.CheckpointLoadStatus at 0x7f1d0d679dd0>"
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"metadata": {},
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{
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"source": [
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"def do_stft(noisy):\n",
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"def do_stft(noisy):\n",
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" \n",
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" \n",
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" window_fn = tf.signal.hamming_window\n",
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" pred_cpx=data[...,0] + 1j * data[...,1]\n",
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" pred_cpx=data[...,0] + 1j * data[...,1]\n",
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" pred_time=tf.signal.inverse_stft(pred_cpx, win_size, hop_size, window_fn=inv_window_fn)\n",
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" pred_time=tf.signal.inverse_stft(pred_cpx, win_size, hop_size, window_fn=inv_window_fn)\n",
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" return pred_time\n"
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" return pred_time\n",
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],
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"metadata": {
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"id": "iDJGN-1_taXR"
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"id": "iDJGN-1_taXR",
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"execution_count": 79,
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"def denoise_audio(audio):\n",
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" Upload widget is only available when the cell has been executed in the\n",
|
" Upload widget is only available when the cell has been executed in the\n",
|
||||||
" current browser session. Please rerun this cell to enable.\n",
|
" current browser session. Please rerun this cell to enable.\n",
|
||||||
" </output>\n",
|
" </output>\n",
|
||||||
@ -393,25 +358,21 @@
|
|||||||
"for fn in uploaded.keys():\n",
|
"for fn in uploaded.keys():\n",
|
||||||
" print('Denoising uploaded file \"{name}\"'.format(\n",
|
" print('Denoising uploaded file \"{name}\"'.format(\n",
|
||||||
" name=fn))\n",
|
" name=fn))\n",
|
||||||
" denoise_data=denoise_audio(fn)"
|
" denoise_data=denoise_audio(fn)\n",
|
||||||
|
" basename=os.path.splitext(fn)[0]\n",
|
||||||
|
" wav_output_name=basename+\"_denoised\"+\".wav\"\n",
|
||||||
|
" sf.write(wav_output_name, denoise_data, 44100)"
|
||||||
],
|
],
|
||||||
"metadata": {
|
"metadata": {
|
||||||
"colab": {
|
"colab": {
|
||||||
"base_uri": "https://localhost:8080/"
|
"base_uri": "https://localhost:8080/"
|
||||||
},
|
},
|
||||||
"id": "0po6zpvrylc2",
|
"id": "0po6zpvrylc2",
|
||||||
"outputId": "0d2b228e-dad8-40f8-f10a-118ea115180d"
|
"outputId": "173f5355-2939-41fe-c702-591aa752fc7e"
|
||||||
},
|
},
|
||||||
"id": "0po6zpvrylc2",
|
"id": "0po6zpvrylc2",
|
||||||
"execution_count": null,
|
"execution_count": 6,
|
||||||
"outputs": [
|
"outputs": [
|
||||||
{
|
|
||||||
"output_type": "stream",
|
|
||||||
"name": "stderr",
|
|
||||||
"text": [
|
|
||||||
"\r 0%| | 0/41 [00:00<?, ?it/s]"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
{
|
||||||
"output_type": "stream",
|
"output_type": "stream",
|
||||||
"name": "stdout",
|
"name": "stdout",
|
||||||
@ -424,20 +385,103 @@
|
|||||||
"output_type": "stream",
|
"output_type": "stream",
|
||||||
"name": "stderr",
|
"name": "stderr",
|
||||||
"text": [
|
"text": [
|
||||||
" 71%|███████ | 29/41 [09:59<04:09, 20.77s/it]"
|
"100%|██████████| 41/41 [00:30<00:00, 1.34it/s]\n"
|
||||||
]
|
]
|
||||||
}
|
}
|
||||||
]
|
]
|
||||||
},
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"source": [
|
||||||
|
"\n",
|
||||||
|
"files.download(wav_output_name)"
|
||||||
|
],
|
||||||
|
"metadata": {
|
||||||
|
"colab": {
|
||||||
|
"base_uri": "https://localhost:8080/",
|
||||||
|
"height": 17
|
||||||
|
},
|
||||||
|
"id": "3tEshWBezYvf",
|
||||||
|
"outputId": "54588c26-0b3c-42bf-aca2-8316ab54603f"
|
||||||
|
},
|
||||||
|
"id": "3tEshWBezYvf",
|
||||||
|
"execution_count": 7,
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"output_type": "display_data",
|
||||||
|
"data": {
|
||||||
|
"application/javascript": [
|
||||||
|
"\n",
|
||||||
|
" async function download(id, filename, size) {\n",
|
||||||
|
" if (!google.colab.kernel.accessAllowed) {\n",
|
||||||
|
" return;\n",
|
||||||
|
" }\n",
|
||||||
|
" const div = document.createElement('div');\n",
|
||||||
|
" const label = document.createElement('label');\n",
|
||||||
|
" label.textContent = `Downloading \"${filename}\": `;\n",
|
||||||
|
" div.appendChild(label);\n",
|
||||||
|
" const progress = document.createElement('progress');\n",
|
||||||
|
" progress.max = size;\n",
|
||||||
|
" div.appendChild(progress);\n",
|
||||||
|
" document.body.appendChild(div);\n",
|
||||||
|
"\n",
|
||||||
|
" const buffers = [];\n",
|
||||||
|
" let downloaded = 0;\n",
|
||||||
|
"\n",
|
||||||
|
" const channel = await google.colab.kernel.comms.open(id);\n",
|
||||||
|
" // Send a message to notify the kernel that we're ready.\n",
|
||||||
|
" channel.send({})\n",
|
||||||
|
"\n",
|
||||||
|
" for await (const message of channel.messages) {\n",
|
||||||
|
" // Send a message to notify the kernel that we're ready.\n",
|
||||||
|
" channel.send({})\n",
|
||||||
|
" if (message.buffers) {\n",
|
||||||
|
" for (const buffer of message.buffers) {\n",
|
||||||
|
" buffers.push(buffer);\n",
|
||||||
|
" downloaded += buffer.byteLength;\n",
|
||||||
|
" progress.value = downloaded;\n",
|
||||||
|
" }\n",
|
||||||
|
" }\n",
|
||||||
|
" }\n",
|
||||||
|
" const blob = new Blob(buffers, {type: 'application/binary'});\n",
|
||||||
|
" const a = document.createElement('a');\n",
|
||||||
|
" a.href = window.URL.createObjectURL(blob);\n",
|
||||||
|
" a.download = filename;\n",
|
||||||
|
" div.appendChild(a);\n",
|
||||||
|
" a.click();\n",
|
||||||
|
" div.remove();\n",
|
||||||
|
" }\n",
|
||||||
|
" "
|
||||||
|
],
|
||||||
|
"text/plain": [
|
||||||
|
"<IPython.core.display.Javascript object>"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"metadata": {}
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"output_type": "display_data",
|
||||||
|
"data": {
|
||||||
|
"application/javascript": [
|
||||||
|
"download(\"download_3e3ca242-937f-408e-a16c-4aa5bb2b9e50\", \"Carmen-Habanera_(Love_is_Like_a_Woo_-_Marguerite_D'Alvarez_noisy_input_denoised.wav\", 17961334)"
|
||||||
|
],
|
||||||
|
"text/plain": [
|
||||||
|
"<IPython.core.display.Javascript object>"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"metadata": {}
|
||||||
|
}
|
||||||
|
]
|
||||||
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"source": [
|
"source": [
|
||||||
""
|
""
|
||||||
],
|
],
|
||||||
"metadata": {
|
"metadata": {
|
||||||
"id": "3tEshWBezYvf"
|
"id": "v_FuSJ4J-WO-"
|
||||||
},
|
},
|
||||||
"id": "3tEshWBezYvf",
|
"id": "v_FuSJ4J-WO-",
|
||||||
"execution_count": null,
|
"execution_count": null,
|
||||||
"outputs": []
|
"outputs": []
|
||||||
}
|
}
|
||||||
@ -464,7 +508,8 @@
|
|||||||
"name": "demo.ipynb",
|
"name": "demo.ipynb",
|
||||||
"provenance": [],
|
"provenance": [],
|
||||||
"include_colab_link": true
|
"include_colab_link": true
|
||||||
}
|
},
|
||||||
|
"accelerator": "GPU"
|
||||||
},
|
},
|
||||||
"nbformat": 4,
|
"nbformat": 4,
|
||||||
"nbformat_minor": 5
|
"nbformat_minor": 5
|
||||||
|
|||||||
Loading…
Reference in New Issue
Block a user