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{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"private_outputs": true,
"provenance": []
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
}
},
"cells": [
{
"cell_type": "markdown",
"source": [
"# MIDI Images Solo Piano Dataset Maker (ver. 1.0)\n",
"\n",
"***\n",
"\n",
"Powered by tegridy-tools: https://github.com/asigalov61/tegridy-tools\n",
"\n",
"***\n",
"\n",
"#### Project Los Angeles\n",
"\n",
"#### Tegridy Code 2024\n",
"\n",
"***"
],
"metadata": {
"id": "LUgrspEA-68o"
}
},
{
"cell_type": "markdown",
"source": [
"# (SETUP ENVIRONMENT)"
],
"metadata": {
"id": "7N-KXNgQ_a0h"
}
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "pxNxlyfZ8hCg",
"cellView": "form"
},
"outputs": [],
"source": [
"# @title Install dependecies\n",
"!git clone --depth 1 https://github.com/asigalov61/tegridy-tools"
]
},
{
"cell_type": "code",
"source": [
"#@title Import all needed modules\n",
"\n",
"print('=' * 70)\n",
"print('Loading core modules...')\n",
"print('Please wait...')\n",
"print('=' * 70)\n",
"\n",
"import os\n",
"import copy\n",
"import math\n",
"import statistics\n",
"import random\n",
"import pickle\n",
"import shutil\n",
"from itertools import groupby\n",
"from collections import Counter\n",
"from sklearn.metrics import pairwise_distances\n",
"from sklearn import metrics\n",
"from joblib import Parallel, delayed, parallel_config\n",
"import numpy as np\n",
"from tqdm import tqdm\n",
"from PIL import Image\n",
"import matplotlib.pyplot as plt\n",
"\n",
"print('Done!')\n",
"print('=' * 70)\n",
"print('Creating I/O dirs...')\n",
"\n",
"if not os.path.exists('/content/Dataset'):\n",
" os.makedirs('/content/Dataset')\n",
"\n",
"print('Done!')\n",
"print('=' * 70)\n",
"print('Loading tegridy-tools modules...')\n",
"print('=' * 70)\n",
"\n",
"%cd /content/tegridy-tools/tegridy-tools\n",
"\n",
"import TMIDIX\n",
"import TMELODIES\n",
"import TPLOTS\n",
"import HaystackSearch\n",
"\n",
"%cd /content/\n",
"\n",
"print('=' * 70)\n",
"print('Done!')\n",
"print('=' * 70)"
],
"metadata": {
"id": "OblKfMMT8rfM",
"cellView": "form"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"# (DOWNLOAD SAMPLE MIDI DATASET)"
],
"metadata": {
"id": "gUXM7WsN_ioe"
}
},
{
"cell_type": "code",
"source": [
"# @title Download sample MIDI dataset (POP909)\n",
"%cd /content/Dataset/\n",
"!git clone --depth 1 https://github.com/music-x-lab/POP909-Dataset\n",
"%cd /content/"
],
"metadata": {
"id": "JLm4OmOUYlEK",
"cellView": "form"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"#@title Save file list\n",
"###########\n",
"\n",
"print('=' * 70)\n",
"print('Loading MIDI files...')\n",
"print('This may take a while on a large dataset in particular...')\n",
"\n",
"dataset_addr = '/content/Dataset/'\n",
"\n",
"# os.chdir(dataset_addr)\n",
"filez = list()\n",
"for (dirpath, dirnames, filenames) in os.walk(dataset_addr):\n",
" filez += [os.path.join(dirpath, file) for file in filenames if file.endswith('.mid') or file.endswith('.midi') or file.endswith('.kar')]\n",
"print('=' * 70)\n",
"\n",
"if filez == []:\n",
" print('Could not find any MIDI files. Please check Dataset dir...')\n",
" print('=' * 70)\n",
"\n",
"print('Randomizing file list...')\n",
"random.shuffle(filez)\n",
"print('Done!')\n",
"print('=' * 70)\n",
"print('Total found MIDI files:', len(filez))\n",
"print('=' * 70)\n",
"\n",
"TMIDIX.Tegridy_Any_Pickle_File_Writer(filez, 'filez')\n",
"\n",
"print('=' * 70)"
],
"metadata": {
"cellView": "form",
"id": "AJrFrZ9grhMM"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"# (LOAD TMIDIX MIDI PROCESSOR)"
],
"metadata": {
"id": "RJeTdierAbeF"
}
},
{
"cell_type": "code",
"source": [
"#@title Load TMIDIX MIDI processor\n",
"\n",
"print('=' * 70)\n",
"print('TMIDIX MIDI Processor')\n",
"print('=' * 70)\n",
"print('Loading...')\n",
"\n",
"###########\n",
"\n",
"def TMIDIX_MIDI_Processor(midi_file):\n",
"\n",
" fn = os.path.basename(midi_file)\n",
" fn1 = fn.split('.mid')[0]\n",
"\n",
" try:\n",
"\n",
" #=======================================================\n",
" # START PROCESSING\n",
"\n",
" raw_score = TMIDIX.midi2single_track_ms_score(midi_file)\n",
"\n",
" escore_notes = TMIDIX.advanced_score_processor(raw_score, return_enhanced_score_notes=True)[0]\n",
"\n",
" escore_notes = TMIDIX.augment_enhanced_score_notes(escore_notes, timings_divider=256)\n",
"\n",
" sp_escore_notes = TMIDIX.recalculate_score_timings(TMIDIX.solo_piano_escore_notes(escore_notes, keep_drums=False))\n",
"\n",
" if sp_escore_notes:\n",
"\n",
" bmatrix = TMIDIX.escore_notes_to_binary_matrix(sp_escore_notes)\n",
"\n",
" return [fn1, bmatrix]\n",
"\n",
" else:\n",
" return [fn1, []]\n",
"\n",
" #=======================================================\n",
"\n",
" except Exception as ex:\n",
" print('WARNING !!!')\n",
" print('=' * 70)\n",
" print('Bad MIDI:', midi_file)\n",
" print('Error detected:', ex)\n",
" print('=' * 70)\n",
" return None\n",
"\n",
"print('Done!')\n",
"print('=' * 70)"
],
"metadata": {
"cellView": "form",
"id": "fBbIiUWSZA5y"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"# (PROCESS MIDIs)"
],
"metadata": {
"id": "R3QxQN6OA_jX"
}
},
{
"cell_type": "code",
"source": [
"#@title Process MIDIs with TMIDIX MIDI processor\n",
"output_folder = \"/content/MIDI-Images/\" # @param {\"type\":\"string\"}\n",
"\n",
"NUMBER_OF_PARALLEL_JOBS = 4 # Number of parallel jobs\n",
"NUMBER_OF_FILES_PER_ITERATION = 4 # Number of files to queue for each parallel iteration\n",
"SAVE_EVERY_NUMBER_OF_ITERATIONS = 128 # Save every 2560 files\n",
"\n",
"print('=' * 70)\n",
"print('TMIDIX MIDI Processor')\n",
"print('=' * 70)\n",
"print('Starting up...')\n",
"print('=' * 70)\n",
"\n",
"###########\n",
"\n",
"melody_chords_f = []\n",
"\n",
"files_count = 0\n",
"\n",
"print('Processing MIDI files...')\n",
"print('Please wait...')\n",
"print('=' * 70)\n",
"\n",
"for i in tqdm(range(0, len(filez), NUMBER_OF_FILES_PER_ITERATION)):\n",
"\n",
" with parallel_config(backend='threading', n_jobs=NUMBER_OF_PARALLEL_JOBS, verbose = 0):\n",
"\n",
" output = Parallel(n_jobs=NUMBER_OF_PARALLEL_JOBS, verbose=0)(delayed(TMIDIX_MIDI_Processor)(f) for f in filez[i:i+NUMBER_OF_FILES_PER_ITERATION])\n",
"\n",
" for o in output:\n",
"\n",
" if o is not None:\n",
" melody_chords_f.append(o)\n",
"\n",
" if i % (NUMBER_OF_FILES_PER_ITERATION * SAVE_EVERY_NUMBER_OF_ITERATIONS) == 0 and i != 0:\n",
"\n",
" print('SAVING !!!')\n",
" print('=' * 70)\n",
" print('Saving processed files...')\n",
" files_count += len(melody_chords_f)\n",
" print('=' * 70)\n",
" print('Processed so far:', files_count, 'out of', len(filez), '===', files_count / len(filez), 'good files ratio')\n",
" print('=' * 70)\n",
" print('Writing images...')\n",
" print('Please wait...')\n",
"\n",
" for mat in melody_chords_f:\n",
"\n",
" if mat[1]:\n",
"\n",
" TPLOTS.binary_matrix_to_images(mat[1],\n",
" 128,\n",
" 32,\n",
" output_folder=output_folder+str(mat[0])+'/',\n",
" output_img_prefix=str(mat[0]),\n",
" output_img_ext='.png',\n",
" verbose=False\n",
" )\n",
"\n",
" print('Done!')\n",
" print('=' * 70)\n",
" melody_chords_f = []\n",
"\n",
"print('SAVING !!!')\n",
"print('=' * 70)\n",
"print('Saving processed files...')\n",
"files_count += len(melody_chords_f)\n",
"print('=' * 70)\n",
"print('Processed so far:', files_count, 'out of', len(filez), '===', files_count / len(filez), 'good files ratio')\n",
"print('=' * 70)\n",
"print('Writing images...')\n",
"print('Please wait...')\n",
"\n",
"for mat in melody_chords_f:\n",
"\n",
" if mat[1]:\n",
"\n",
" TPLOTS.binary_matrix_to_images(mat[1],\n",
" 128,\n",
" 32,\n",
" output_folder=output_folder+str(mat[0])+'/',\n",
" output_img_prefix=str(mat[0]),\n",
" output_img_ext='.png',\n",
" verbose=False\n",
" )\n",
"\n",
"print('Done!')\n",
"print('=' * 70)"
],
"metadata": {
"cellView": "form",
"id": "15y4uzSOZX52"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"# (LOAD IMAGES)"
],
"metadata": {
"id": "GtejvUFAFocZ"
}
},
{
"cell_type": "code",
"source": [
"#@title Load created MIDI images\n",
"full_path_to_metadata_pickle_files = \"/content/MIDI-Images\" #@param {type:\"string\"}\n",
"\n",
"print('=' * 70)\n",
"print('MIDI Images Reader')\n",
"print('=' * 70)\n",
"print('Searching for images...')\n",
"\n",
"filez = list()\n",
"for (dirpath, dirnames, filenames) in os.walk(full_path_to_metadata_pickle_files):\n",
" filez += [os.path.join(dirpath, file) for file in filenames if file.endswith('.png')]\n",
"print('=' * 70)\n",
"\n",
"filez.sort()\n",
"\n",
"print('Found', len(filez), 'images!')\n",
"print('=' * 70)\n",
"print('Reading images...')\n",
"print('Please wait...')\n",
"print('=' * 70)\n",
"\n",
"fidx = 0\n",
"\n",
"all_read_images = []\n",
"\n",
"for img in tqdm(filez):\n",
"\n",
" img = Image.open(img)\n",
"\n",
" img_arr = np.array(img).tolist()\n",
"\n",
" all_read_images.append(img_arr)\n",
"\n",
" fidx += 1\n",
"\n",
"print('Done!')\n",
"print('=' * 70)\n",
"print('Loaded', fidx, 'images!')\n",
"print('=' * 70)\n",
"print('Done!')\n",
"print('=' * 70)"
],
"metadata": {
"cellView": "form",
"id": "cXpLWHG1dBB3"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"# (TEST IMAGES)"
],
"metadata": {
"id": "qbClHSmhB1NF"
}
},
{
"cell_type": "code",
"source": [
"# @title Test created MIDI images\n",
"\n",
"print('=' * 70)\n",
"\n",
"image = random.choice(all_read_images)\n",
"\n",
"escore = TMIDIX.binary_matrix_to_original_escore_notes(image)\n",
"\n",
"output_score, patches, overflow_patches = TMIDIX.patch_enhanced_score_notes(escore)\n",
"\n",
"detailed_stats = TMIDIX.Tegridy_ms_SONG_to_MIDI_Converter(output_score,\n",
" output_signature = 'MIDI Images',\n",
" output_file_name = '/content/MIDI-Images-Composition',\n",
" track_name='Project Los Angeles',\n",
" list_of_MIDI_patches=patches,\n",
" timings_multiplier=256\n",
" )\n",
"\n",
"print('=' * 70)"
],
"metadata": {
"id": "nrPDM1VQdKES",
"cellView": "form"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"# (ZIP IMAGES)"
],
"metadata": {
"id": "sIq55gvPCgJh"
}
},
{
"cell_type": "code",
"source": [
"# @title Zip created MIDI images\n",
"!zip -9 -r POP909_MIDI_Images_128_128_32_BW.zip MIDI-Images/ > /dev/null"
],
"metadata": {
"id": "tVe0REKSqJeV",
"cellView": "form"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"# Congrats! You did it! :)"
],
"metadata": {
"id": "iDdMYg4haGFn"
}
}
]
} |