projectlosangeles
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Master_MIDI_Dataset_Search_and_Filter.ipynb
ADDED
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1 |
+
{
|
2 |
+
"cells": [
|
3 |
+
{
|
4 |
+
"cell_type": "markdown",
|
5 |
+
"metadata": {
|
6 |
+
"gradient": {
|
7 |
+
"editing": false,
|
8 |
+
"id": "ac5a4cf0-d9d2-47b5-9633-b53f8d99a4d2",
|
9 |
+
"kernelId": ""
|
10 |
+
},
|
11 |
+
"id": "SiTIpPjArIyr"
|
12 |
+
},
|
13 |
+
"source": [
|
14 |
+
"# Master MIDI Dataset Search and Filter (ver. 1.0)\n",
|
15 |
+
"\n",
|
16 |
+
"***\n",
|
17 |
+
"\n",
|
18 |
+
"Powered by tegridy-tools: https://github.com/asigalov61/tegridy-tools\n",
|
19 |
+
"\n",
|
20 |
+
"***\n",
|
21 |
+
"\n",
|
22 |
+
"#### Project Los Angeles\n",
|
23 |
+
"\n",
|
24 |
+
"#### Tegridy Code 2023\n",
|
25 |
+
"\n",
|
26 |
+
"***"
|
27 |
+
]
|
28 |
+
},
|
29 |
+
{
|
30 |
+
"cell_type": "markdown",
|
31 |
+
"metadata": {
|
32 |
+
"gradient": {
|
33 |
+
"editing": false,
|
34 |
+
"id": "fa0a611c-1803-42ae-bdf6-a49b5a4e781b",
|
35 |
+
"kernelId": ""
|
36 |
+
},
|
37 |
+
"id": "gOd93yV0sGd2"
|
38 |
+
},
|
39 |
+
"source": [
|
40 |
+
"# (SETUP ENVIRONMENT)"
|
41 |
+
]
|
42 |
+
},
|
43 |
+
{
|
44 |
+
"cell_type": "code",
|
45 |
+
"execution_count": null,
|
46 |
+
"metadata": {
|
47 |
+
"cellView": "form",
|
48 |
+
"gradient": {
|
49 |
+
"editing": false,
|
50 |
+
"id": "a1a45a91-d909-4fd4-b67a-5e16b971d179",
|
51 |
+
"kernelId": ""
|
52 |
+
},
|
53 |
+
"id": "fX12Yquyuihc"
|
54 |
+
},
|
55 |
+
"outputs": [],
|
56 |
+
"source": [
|
57 |
+
"#@title Install all dependencies (run only once per session)\n",
|
58 |
+
"\n",
|
59 |
+
"!git clone https://github.com/asigalov61/tegridy-tools\n",
|
60 |
+
"!pip install huggingface_hub\n",
|
61 |
+
"!pip install tqdm"
|
62 |
+
]
|
63 |
+
},
|
64 |
+
{
|
65 |
+
"cell_type": "code",
|
66 |
+
"execution_count": null,
|
67 |
+
"metadata": {
|
68 |
+
"gradient": {
|
69 |
+
"editing": false,
|
70 |
+
"id": "b8207b76-9514-4c07-95db-95a4742e52c5",
|
71 |
+
"kernelId": ""
|
72 |
+
},
|
73 |
+
"id": "z7n9vnKmug1J",
|
74 |
+
"cellView": "form"
|
75 |
+
},
|
76 |
+
"outputs": [],
|
77 |
+
"source": [
|
78 |
+
"#@title Import all needed modules\n",
|
79 |
+
"\n",
|
80 |
+
"print('Loading core modules... Please wait...')\n",
|
81 |
+
"import os\n",
|
82 |
+
"import copy\n",
|
83 |
+
"from collections import Counter\n",
|
84 |
+
"import random\n",
|
85 |
+
"import pickle\n",
|
86 |
+
"from tqdm import tqdm\n",
|
87 |
+
"import pprint\n",
|
88 |
+
"import statistics\n",
|
89 |
+
"import shutil\n",
|
90 |
+
"\n",
|
91 |
+
"print('Creating IO dirs... Please wait...')\n",
|
92 |
+
"\n",
|
93 |
+
"if not os.path.exists('/content/Main-MIDI-Dataset'):\n",
|
94 |
+
" os.makedirs('/content/Main-MIDI-Dataset')\n",
|
95 |
+
"\n",
|
96 |
+
"if not os.path.exists('/content/Master-MIDI-Dataset'):\n",
|
97 |
+
" os.makedirs('/content/Master-MIDI-Dataset')\n",
|
98 |
+
"\n",
|
99 |
+
"if not os.path.exists('/content/Output-MIDI-Dataset'):\n",
|
100 |
+
" os.makedirs('/content/Output-MIDI-Dataset')\n",
|
101 |
+
"\n",
|
102 |
+
"print('Loading TMIDIX module...')\n",
|
103 |
+
"os.chdir('/content/tegridy-tools/tegridy-tools')\n",
|
104 |
+
"\n",
|
105 |
+
"import TMIDIX\n",
|
106 |
+
"\n",
|
107 |
+
"print('Done!')\n",
|
108 |
+
"\n",
|
109 |
+
"from huggingface_hub import hf_hub_download\n",
|
110 |
+
"\n",
|
111 |
+
"os.chdir('/content/')\n",
|
112 |
+
"print('Enjoy! :)')"
|
113 |
+
]
|
114 |
+
},
|
115 |
+
{
|
116 |
+
"cell_type": "markdown",
|
117 |
+
"metadata": {
|
118 |
+
"gradient": {
|
119 |
+
"editing": false,
|
120 |
+
"id": "20b8698a-0b4e-4fdb-ae49-24d063782e77",
|
121 |
+
"kernelId": ""
|
122 |
+
},
|
123 |
+
"id": "ObPxlEutsQBj"
|
124 |
+
},
|
125 |
+
"source": [
|
126 |
+
"# (PREP MAIN MIDI DATASET)"
|
127 |
+
]
|
128 |
+
},
|
129 |
+
{
|
130 |
+
"cell_type": "code",
|
131 |
+
"source": [
|
132 |
+
"#@title Download main MIDI dataset\n",
|
133 |
+
"print('=' * 70)\n",
|
134 |
+
"print('Downloading Los Angeles MIDI Dataset...Please wait...')\n",
|
135 |
+
"print('=' * 70)\n",
|
136 |
+
"\n",
|
137 |
+
"hf_hub_download(repo_id='projectlosangeles/Los-Angeles-MIDI-Dataset', \n",
|
138 |
+
" filename='Los-Angeles-MIDI-Dataset-Ver-2-0-CC-BY-NC-SA.zip',\n",
|
139 |
+
" repo_type=\"dataset\",\n",
|
140 |
+
" local_dir='/content/Main-MIDI-Dataset', \n",
|
141 |
+
" local_dir_use_symlinks=False)\n",
|
142 |
+
"print('=' * 70)\n",
|
143 |
+
"print('Done! Enjoy! :)')\n",
|
144 |
+
"print('=' * 70)"
|
145 |
+
],
|
146 |
+
"metadata": {
|
147 |
+
"cellView": "form",
|
148 |
+
"id": "7aItlhq9cRxZ"
|
149 |
+
},
|
150 |
+
"execution_count": null,
|
151 |
+
"outputs": []
|
152 |
+
},
|
153 |
+
{
|
154 |
+
"cell_type": "code",
|
155 |
+
"source": [
|
156 |
+
"#@title Unzip main MIDI dataset\n",
|
157 |
+
"%cd /content/Main-MIDI-Dataset/\n",
|
158 |
+
"\n",
|
159 |
+
"print('=' * 70)\n",
|
160 |
+
"print('Unzipping Los Angeles MIDI Dataset...Please wait...')\n",
|
161 |
+
"!unzip 'Los-Angeles-MIDI-Dataset-Ver-2-0-CC-BY-NC-SA.zip'\n",
|
162 |
+
"print('=' * 70)\n",
|
163 |
+
"\n",
|
164 |
+
"print('Done! Enjoy! :)')\n",
|
165 |
+
"print('=' * 70)\n",
|
166 |
+
"%cd /content/"
|
167 |
+
],
|
168 |
+
"metadata": {
|
169 |
+
"cellView": "form",
|
170 |
+
"id": "zMF4vdMNDYYg"
|
171 |
+
},
|
172 |
+
"execution_count": null,
|
173 |
+
"outputs": []
|
174 |
+
},
|
175 |
+
{
|
176 |
+
"cell_type": "code",
|
177 |
+
"source": [
|
178 |
+
"#@title Create main MIDI dataset files list\n",
|
179 |
+
"print('=' * 70)\n",
|
180 |
+
"print('Creating dataset files list...')\n",
|
181 |
+
"dataset_addr = \"/content/Main-MIDI-Dataset/MIDIs\"\n",
|
182 |
+
"\n",
|
183 |
+
"# os.chdir(dataset_addr)\n",
|
184 |
+
"filez = list()\n",
|
185 |
+
"for (dirpath, dirnames, filenames) in os.walk(dataset_addr):\n",
|
186 |
+
" filez += [os.path.join(dirpath, file) for file in filenames]\n",
|
187 |
+
"\n",
|
188 |
+
"if filez == []:\n",
|
189 |
+
" print('Could not find any MIDI files. Please check Dataset dir...')\n",
|
190 |
+
" print('=' * 70)\n",
|
191 |
+
"\n",
|
192 |
+
"print('=' * 70)\n",
|
193 |
+
"print('Randomizing file list...')\n",
|
194 |
+
"random.shuffle(filez)\n",
|
195 |
+
"print('=' * 70)\n",
|
196 |
+
"\n",
|
197 |
+
"LAMD_files_list = []\n",
|
198 |
+
"\n",
|
199 |
+
"for f in tqdm(filez):\n",
|
200 |
+
" LAMD_files_list.append([f.split('/')[-1].split('.mid')[0], f])\n",
|
201 |
+
"print('Done!')\n",
|
202 |
+
"print('=' * 70)"
|
203 |
+
],
|
204 |
+
"metadata": {
|
205 |
+
"cellView": "form",
|
206 |
+
"id": "btrUDk8MDfdw"
|
207 |
+
},
|
208 |
+
"execution_count": null,
|
209 |
+
"outputs": []
|
210 |
+
},
|
211 |
+
{
|
212 |
+
"cell_type": "code",
|
213 |
+
"source": [
|
214 |
+
"#@title Load main MIDI dataset metadata\n",
|
215 |
+
"print('=' * 70)\n",
|
216 |
+
"print('Loading LAMDa data...Please wait...')\n",
|
217 |
+
"print('=' * 70)\n",
|
218 |
+
"print('Loading LAMDa META-DATA...')\n",
|
219 |
+
"meta_data = pickle.load(open('/content/Main-MIDI-Dataset/META_DATA/LAMDa_META_DATA.pickle', 'rb'))\n",
|
220 |
+
"print('Done!')"
|
221 |
+
],
|
222 |
+
"metadata": {
|
223 |
+
"cellView": "form",
|
224 |
+
"id": "Mv-pjxbrIqi2"
|
225 |
+
},
|
226 |
+
"execution_count": null,
|
227 |
+
"outputs": []
|
228 |
+
},
|
229 |
+
{
|
230 |
+
"cell_type": "markdown",
|
231 |
+
"source": [
|
232 |
+
"# (SEARCH AND FILTER)\n",
|
233 |
+
"\n",
|
234 |
+
"### DO NOT FORGET TO UPLOAD YOUR MASTER DATASET TO \"Master-MIDI-Dataset\" FOLDER"
|
235 |
+
],
|
236 |
+
"metadata": {
|
237 |
+
"id": "iaeqXuIHI0_T"
|
238 |
+
}
|
239 |
+
},
|
240 |
+
{
|
241 |
+
"cell_type": "code",
|
242 |
+
"source": [
|
243 |
+
"#@title Master MIDI Dataset Search and Filter\n",
|
244 |
+
"\n",
|
245 |
+
"#@markdown NOTE: You can stop the search at any time to render partial results\n",
|
246 |
+
"\n",
|
247 |
+
"number_of_top_ratios_MIDIs_to_collect = 10 #@param {type:\"slider\", min:1, max:20, step:1}\n",
|
248 |
+
"\n",
|
249 |
+
"#@markdown Match ratio control option\n",
|
250 |
+
"\n",
|
251 |
+
"maximum_match_ratio_to_search_for = 1 #@param {type:\"slider\", min:0, max:1, step:0.01}\n",
|
252 |
+
"\n",
|
253 |
+
"#@markdown MIDI pitches search options\n",
|
254 |
+
"\n",
|
255 |
+
"pitches_counts_cutoff_threshold_ratio = 0 #@param {type:\"slider\", min:0, max:1, step:0.05}\n",
|
256 |
+
"search_transposed_pitches = False #@param {type:\"boolean\"}\n",
|
257 |
+
"skip_exact_matches = False #@param {type:\"boolean\"}\n",
|
258 |
+
"\n",
|
259 |
+
"#@markdown Additional search options\n",
|
260 |
+
"\n",
|
261 |
+
"add_pitches_counts_ratios = True #@param {type:\"boolean\"}\n",
|
262 |
+
"add_timings_ratios = False #@param {type:\"boolean\"}\n",
|
263 |
+
"add_durations_ratios = False #@param {type:\"boolean\"}\n",
|
264 |
+
"\n",
|
265 |
+
"print('=' * 70)\n",
|
266 |
+
"print('Master MIDI Dataset Search and Filter')\n",
|
267 |
+
"print('=' * 70)\n",
|
268 |
+
"\n",
|
269 |
+
"###########\n",
|
270 |
+
"\n",
|
271 |
+
"print('Loading MIDI files...')\n",
|
272 |
+
"print('This may take a while on a large dataset in particular.')\n",
|
273 |
+
"\n",
|
274 |
+
"dataset_addr = \"/content/Master-MIDI-Dataset\"\n",
|
275 |
+
"# os.chdir(dataset_addr)\n",
|
276 |
+
"filez = list()\n",
|
277 |
+
"for (dirpath, dirnames, filenames) in os.walk(dataset_addr):\n",
|
278 |
+
" filez += [os.path.join(dirpath, file) for file in filenames]\n",
|
279 |
+
"print('=' * 70)\n",
|
280 |
+
"\n",
|
281 |
+
"if filez == []:\n",
|
282 |
+
" print('Could not find any MIDI files. Please check Dataset dir...')\n",
|
283 |
+
" print('=' * 70)\n",
|
284 |
+
"\n",
|
285 |
+
"print('Randomizing file list...')\n",
|
286 |
+
"random.shuffle(filez)\n",
|
287 |
+
"print('=' * 70)\n",
|
288 |
+
"###################\n",
|
289 |
+
"\n",
|
290 |
+
"input_files_count = 0\n",
|
291 |
+
"files_count = 0\n",
|
292 |
+
"\n",
|
293 |
+
"for f in filez:\n",
|
294 |
+
" try:\n",
|
295 |
+
" \n",
|
296 |
+
" input_files_count += 1\n",
|
297 |
+
"\n",
|
298 |
+
" fn = os.path.basename(f)\n",
|
299 |
+
" fn1 = fn.split('.mid')[0]\n",
|
300 |
+
" ext = fn.split('.')[-1]\n",
|
301 |
+
"\n",
|
302 |
+
" if ext == 'mid' or ext == 'midi' or ext == 'kar':\n",
|
303 |
+
"\n",
|
304 |
+
" print('Processing MIDI File #', files_count+1, 'out of', len(filez))\n",
|
305 |
+
" print('MIDI file name', fn)\n",
|
306 |
+
" print('-' * 70) \n",
|
307 |
+
"\n",
|
308 |
+
" #=======================================================\n",
|
309 |
+
"\n",
|
310 |
+
" score = TMIDIX.midi2ms_score(open(f, 'rb').read())\n",
|
311 |
+
"\n",
|
312 |
+
" events_matrix = []\n",
|
313 |
+
"\n",
|
314 |
+
" itrack = 1\n",
|
315 |
+
"\n",
|
316 |
+
" while itrack < len(score):\n",
|
317 |
+
" for event in score[itrack]: \n",
|
318 |
+
" events_matrix.append(event)\n",
|
319 |
+
" itrack += 1\n",
|
320 |
+
"\n",
|
321 |
+
" # Sorting...\n",
|
322 |
+
" events_matrix.sort(key=lambda x: x[1])\n",
|
323 |
+
"\n",
|
324 |
+
" # recalculating timings\n",
|
325 |
+
" for e in events_matrix:\n",
|
326 |
+
" e[1] = int(e[1] / 10)\n",
|
327 |
+
" if e[0] == 'note':\n",
|
328 |
+
" e[2] = int(e[2] / 20)\n",
|
329 |
+
"\n",
|
330 |
+
" # final processing...\n",
|
331 |
+
"\n",
|
332 |
+
" melody_chords = []\n",
|
333 |
+
"\n",
|
334 |
+
" patches = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
|
335 |
+
"\n",
|
336 |
+
" pe = events_matrix[0]\n",
|
337 |
+
" for e in events_matrix:\n",
|
338 |
+
"\n",
|
339 |
+
" if e[0] == 'note':\n",
|
340 |
+
" # ['note', start_time, duration, channel, note, velocity]\n",
|
341 |
+
" time = max(0, min(255, e[1]-pe[1]))\n",
|
342 |
+
" duration = max(1, min(255, e[2]))\n",
|
343 |
+
" channel = max(0, min(15, e[3]))\n",
|
344 |
+
"\n",
|
345 |
+
" if e[3] != 9:\n",
|
346 |
+
" instrument = max(0, min(127, patches[e[3]]))\n",
|
347 |
+
" else:\n",
|
348 |
+
" instrument = max(128, min(255, patches[e[3]]+128))\n",
|
349 |
+
"\n",
|
350 |
+
" if e[3] != 9:\n",
|
351 |
+
"\n",
|
352 |
+
" pitch = max(1, min(127, e[4]))\n",
|
353 |
+
" else:\n",
|
354 |
+
" pitch = max(129, min(255, e[4]+128))\n",
|
355 |
+
"\n",
|
356 |
+
" if e[3] != 9:\n",
|
357 |
+
" velocity = max(1, min(127, e[5]))\n",
|
358 |
+
" else:\n",
|
359 |
+
" velocity = max(129, min(255, e[5]+128))\n",
|
360 |
+
"\n",
|
361 |
+
" melody_chords.append([time, duration, channel, instrument, pitch, velocity])\n",
|
362 |
+
"\n",
|
363 |
+
" if e[0] == 'patch_change':\n",
|
364 |
+
" # ['patch_change', dtime, channel, patch]\n",
|
365 |
+
" time = max(0, min(127, e[1]-pe[1]))\n",
|
366 |
+
" channel = max(0, min(15, e[2]))\n",
|
367 |
+
" patch = max(0, min(127, e[3]))\n",
|
368 |
+
"\n",
|
369 |
+
" patches[channel] = patch\n",
|
370 |
+
"\n",
|
371 |
+
" pe = e # Previous event\n",
|
372 |
+
"\n",
|
373 |
+
" MATRIX = [[0]*256 for i in range(38)]\n",
|
374 |
+
"\n",
|
375 |
+
" for m in melody_chords:\n",
|
376 |
+
"\n",
|
377 |
+
" MATRIX[0][m[0]] += 1\n",
|
378 |
+
" MATRIX[1][m[1]] += 1\n",
|
379 |
+
" MATRIX[2][m[2]] += 1 \n",
|
380 |
+
" MATRIX[3][m[3]] += 1\n",
|
381 |
+
" MATRIX[4][m[4]] += 1\n",
|
382 |
+
" MATRIX[5][m[5]] += 1\n",
|
383 |
+
" MATRIX[m[2]+6][m[3]] += 1\n",
|
384 |
+
" MATRIX[m[2]+22][m[4]] += 1\n",
|
385 |
+
"\n",
|
386 |
+
" #==================================================\n",
|
387 |
+
"\n",
|
388 |
+
" score = TMIDIX.midi2score(open(f, 'rb').read())\n",
|
389 |
+
"\n",
|
390 |
+
" events_matrix = []\n",
|
391 |
+
"\n",
|
392 |
+
" track_count = 0\n",
|
393 |
+
"\n",
|
394 |
+
" for s in score:\n",
|
395 |
+
" \n",
|
396 |
+
" if track_count > 0:\n",
|
397 |
+
" track = s\n",
|
398 |
+
" track.sort(key=lambda x: x[1])\n",
|
399 |
+
" events_matrix.extend(track)\n",
|
400 |
+
" else:\n",
|
401 |
+
" midi_ticks = s\n",
|
402 |
+
"\n",
|
403 |
+
" track_count += 1\n",
|
404 |
+
" \n",
|
405 |
+
" events_matrix.sort(key=lambda x: x[1])\n",
|
406 |
+
"\n",
|
407 |
+
" mult_pitches_counts = []\n",
|
408 |
+
"\n",
|
409 |
+
" for i in range(-6, 6):\n",
|
410 |
+
"\n",
|
411 |
+
" events_matrix1 = []\n",
|
412 |
+
"\n",
|
413 |
+
" for e in events_matrix:\n",
|
414 |
+
"\n",
|
415 |
+
" ev = copy.deepcopy(e)\n",
|
416 |
+
"\n",
|
417 |
+
" if e[0] == 'note':\n",
|
418 |
+
" if e[3] == 9:\n",
|
419 |
+
" ev[4] = ((e[4] % 128) + 128)\n",
|
420 |
+
" else:\n",
|
421 |
+
" ev[4] = ((e[4] % 128) + i)\n",
|
422 |
+
"\n",
|
423 |
+
" events_matrix1.append(ev)\n",
|
424 |
+
"\n",
|
425 |
+
" pitches_counts = [[y[0],y[1]] for y in Counter([y[4] for y in events_matrix1 if y[0] == 'note']).most_common()]\n",
|
426 |
+
" pitches_counts.sort(key=lambda x: x[0], reverse=True)\n",
|
427 |
+
" \n",
|
428 |
+
" mult_pitches_counts.append(pitches_counts)\n",
|
429 |
+
"\n",
|
430 |
+
" patches_list = sorted(list(set([y[3] for y in events_matrix if y[0] == 'patch_change'])))\n",
|
431 |
+
"\n",
|
432 |
+
" #==================================================\n",
|
433 |
+
"\n",
|
434 |
+
" ms_score = TMIDIX.midi2ms_score(open(f, 'rb').read())\n",
|
435 |
+
"\n",
|
436 |
+
" ms_events_matrix = []\n",
|
437 |
+
"\n",
|
438 |
+
" itrack1 = 1\n",
|
439 |
+
"\n",
|
440 |
+
" while itrack1 < len(ms_score):\n",
|
441 |
+
" for event in ms_score[itrack1]: \n",
|
442 |
+
" if event[0] == 'note':\n",
|
443 |
+
" ms_events_matrix.append(event)\n",
|
444 |
+
" itrack1 += 1\n",
|
445 |
+
"\n",
|
446 |
+
" ms_events_matrix.sort(key=lambda x: x[1])\n",
|
447 |
+
"\n",
|
448 |
+
"\n",
|
449 |
+
" chords = []\n",
|
450 |
+
" pe = ms_events_matrix[0]\n",
|
451 |
+
" cho = []\n",
|
452 |
+
" for e in ms_events_matrix:\n",
|
453 |
+
" if (e[1] - pe[1]) == 0:\n",
|
454 |
+
" if e[3] != 9:\n",
|
455 |
+
" if (e[4] % 12) not in cho:\n",
|
456 |
+
" cho.append(e[4] % 12)\n",
|
457 |
+
" else:\n",
|
458 |
+
" if len(cho) > 0:\n",
|
459 |
+
" chords.append(sorted(cho))\n",
|
460 |
+
" cho = []\n",
|
461 |
+
" if e[3] != 9:\n",
|
462 |
+
" if (e[4] % 12) not in cho:\n",
|
463 |
+
" cho.append(e[4] % 12)\n",
|
464 |
+
"\n",
|
465 |
+
" pe = e\n",
|
466 |
+
" \n",
|
467 |
+
" if len(cho) > 0:\n",
|
468 |
+
" chords.append(sorted(cho))\n",
|
469 |
+
"\n",
|
470 |
+
" ms_chords_counts = sorted([[list(key), val] for key,val in Counter([tuple(c) for c in chords if len(c) > 1]).most_common()], reverse=True, key = lambda x: x[1])\n",
|
471 |
+
"\n",
|
472 |
+
" times = []\n",
|
473 |
+
" pt = ms_events_matrix[0][1]\n",
|
474 |
+
" start = True\n",
|
475 |
+
" for e in ms_events_matrix:\n",
|
476 |
+
" if (e[1]-pt) != 0 or start == True:\n",
|
477 |
+
" times.append((e[1]-pt))\n",
|
478 |
+
" start = False\n",
|
479 |
+
" pt = e[1]\n",
|
480 |
+
" \n",
|
481 |
+
" durs = [e[2] for e in ms_events_matrix]\n",
|
482 |
+
" vels = [e[5] for e in ms_events_matrix]\n",
|
483 |
+
"\n",
|
484 |
+
" avg_time = int(sum(times) / len(times))\n",
|
485 |
+
" avg_dur = int(sum(durs) / len(durs))\n",
|
486 |
+
"\n",
|
487 |
+
" mode_time = statistics.mode(times)\n",
|
488 |
+
" mode_dur = statistics.mode(durs)\n",
|
489 |
+
"\n",
|
490 |
+
" median_time = int(statistics.median(times))\n",
|
491 |
+
" median_dur = int(statistics.median(durs))\n",
|
492 |
+
"\n",
|
493 |
+
" #=======================================================\n",
|
494 |
+
"\n",
|
495 |
+
" print('Searching for matches...Please wait...')\n",
|
496 |
+
" print('-' * 70)\n",
|
497 |
+
"\n",
|
498 |
+
" final_ratios = []\n",
|
499 |
+
"\n",
|
500 |
+
" for d in tqdm(meta_data):\n",
|
501 |
+
"\n",
|
502 |
+
" p_counts = d[1][10][1]\n",
|
503 |
+
" p_counts.sort(reverse = True, key = lambda x: x[1])\n",
|
504 |
+
" max_p_count = p_counts[0][1]\n",
|
505 |
+
" trimmed_p_counts = [y for y in p_counts if y[1] >= (max_p_count * pitches_counts_cutoff_threshold_ratio)]\n",
|
506 |
+
" total_p_counts = sum([y[1] for y in trimmed_p_counts])\n",
|
507 |
+
" \n",
|
508 |
+
" if search_transposed_pitches:\n",
|
509 |
+
" search_pitches = mult_pitches_counts\n",
|
510 |
+
" else:\n",
|
511 |
+
" search_pitches = [mult_pitches_counts[6]]\n",
|
512 |
+
"\n",
|
513 |
+
" #===================================================\n",
|
514 |
+
"\n",
|
515 |
+
" ratios_list = []\n",
|
516 |
+
"\n",
|
517 |
+
" #===================================================\n",
|
518 |
+
"\n",
|
519 |
+
" atrat = [0]\n",
|
520 |
+
"\n",
|
521 |
+
" if add_timings_ratios:\n",
|
522 |
+
"\n",
|
523 |
+
" source_times = [avg_time, \n",
|
524 |
+
" median_time, \n",
|
525 |
+
" mode_time]\n",
|
526 |
+
"\n",
|
527 |
+
" match_times = meta_data[0][1][3][1]\n",
|
528 |
+
"\n",
|
529 |
+
" times_ratios = []\n",
|
530 |
+
"\n",
|
531 |
+
" for i in range(len(source_times)):\n",
|
532 |
+
" maxtratio = max(source_times[i], match_times[i])\n",
|
533 |
+
" mintratio = min(source_times[i], match_times[i])\n",
|
534 |
+
" times_ratios.append(mintratio / maxtratio)\n",
|
535 |
+
"\n",
|
536 |
+
" avg_times_ratio = sum(times_ratios) / len(times_ratios)\n",
|
537 |
+
"\n",
|
538 |
+
" atrat[0] = avg_times_ratio\n",
|
539 |
+
"\n",
|
540 |
+
" #===================================================\n",
|
541 |
+
"\n",
|
542 |
+
" adrat = [0]\n",
|
543 |
+
"\n",
|
544 |
+
" if add_durations_ratios:\n",
|
545 |
+
"\n",
|
546 |
+
" source_durs = [avg_dur,\n",
|
547 |
+
" median_dur,\n",
|
548 |
+
" mode_dur]\n",
|
549 |
+
"\n",
|
550 |
+
" match_durs = meta_data[0][1][4][1]\n",
|
551 |
+
"\n",
|
552 |
+
" durs_ratios = []\n",
|
553 |
+
"\n",
|
554 |
+
" for i in range(len(source_durs)):\n",
|
555 |
+
" maxtratio = max(source_durs[i], match_durs[i])\n",
|
556 |
+
" mintratio = min(source_durs[i], match_durs[i])\n",
|
557 |
+
" durs_ratios.append(mintratio / maxtratio)\n",
|
558 |
+
"\n",
|
559 |
+
" avg_durs_ratio = sum(durs_ratios) / len(durs_ratios)\n",
|
560 |
+
"\n",
|
561 |
+
" adrat[0] = avg_durs_ratio\n",
|
562 |
+
"\n",
|
563 |
+
" #===================================================\n",
|
564 |
+
"\n",
|
565 |
+
" for m in search_pitches:\n",
|
566 |
+
"\n",
|
567 |
+
" sprat = []\n",
|
568 |
+
"\n",
|
569 |
+
" m.sort(reverse = True, key = lambda x: x[1])\n",
|
570 |
+
" max_pitches_count = m[0][1]\n",
|
571 |
+
" trimmed_pitches_counts = [y for y in m if y[1] >= (max_pitches_count * pitches_counts_cutoff_threshold_ratio)]\n",
|
572 |
+
" total_pitches_counts = sum([y[1] for y in trimmed_pitches_counts])\n",
|
573 |
+
"\n",
|
574 |
+
" same_pitches = set([T[0] for T in trimmed_p_counts]) & set([m[0] for m in trimmed_pitches_counts])\n",
|
575 |
+
" num_same_pitches = len(same_pitches)\n",
|
576 |
+
" same_pitches_ratio = (num_same_pitches / len(set([m[0] for m in trimmed_p_counts]+[T[0] for T in trimmed_pitches_counts])))\n",
|
577 |
+
"\n",
|
578 |
+
" if skip_exact_matches:\n",
|
579 |
+
" if same_pitches_ratio == 1:\n",
|
580 |
+
" same_pitches_ratio = 0\n",
|
581 |
+
"\n",
|
582 |
+
" sprat.append(same_pitches_ratio)\n",
|
583 |
+
"\n",
|
584 |
+
" #===================================================\n",
|
585 |
+
"\n",
|
586 |
+
" spcrat = [0]\n",
|
587 |
+
"\n",
|
588 |
+
" if add_pitches_counts_ratios:\n",
|
589 |
+
"\n",
|
590 |
+
" same_trimmed_p_counts = sorted([T for T in trimmed_p_counts if T[0] in same_pitches], reverse = True)\n",
|
591 |
+
" same_trimmed_pitches_counts = sorted([T for T in trimmed_pitches_counts if T[0] in same_pitches], reverse = True)\n",
|
592 |
+
"\n",
|
593 |
+
" same_trimmed_p_counts_ratios = [[s[0], s[1] / total_p_counts] for s in same_trimmed_p_counts]\n",
|
594 |
+
" same_trimmed_pitches_counts_ratios = [[s[0], s[1] / total_pitches_counts] for s in same_trimmed_pitches_counts]\n",
|
595 |
+
"\n",
|
596 |
+
" same_pitches_counts_ratios = []\n",
|
597 |
+
"\n",
|
598 |
+
" for i in range(len(same_trimmed_p_counts_ratios)):\n",
|
599 |
+
" mincratio = min(same_trimmed_p_counts_ratios[i][1], same_trimmed_pitches_counts_ratios[i][1])\n",
|
600 |
+
" maxcratio = max(same_trimmed_p_counts_ratios[i][1], same_trimmed_pitches_counts_ratios[i][1])\n",
|
601 |
+
" same_pitches_counts_ratios.append([same_trimmed_p_counts_ratios[i][0], mincratio / maxcratio])\n",
|
602 |
+
"\n",
|
603 |
+
" same_counts_ratios = [s[1] for s in same_pitches_counts_ratios]\n",
|
604 |
+
"\n",
|
605 |
+
" if len(same_counts_ratios) > 0:\n",
|
606 |
+
" avg_same_pitches_counts_ratio = sum(same_counts_ratios) / len(same_counts_ratios)\n",
|
607 |
+
" else:\n",
|
608 |
+
" avg_same_pitches_counts_ratio = 0\n",
|
609 |
+
"\n",
|
610 |
+
" spcrat[0] = avg_same_pitches_counts_ratio\n",
|
611 |
+
"\n",
|
612 |
+
" #===================================================\n",
|
613 |
+
"\n",
|
614 |
+
" r_list = [sprat[0]]\n",
|
615 |
+
"\n",
|
616 |
+
" if add_pitches_counts_ratios:\n",
|
617 |
+
" r_list.append(spcrat[0])\n",
|
618 |
+
" \n",
|
619 |
+
" if add_timings_ratios:\n",
|
620 |
+
" r_list.append(atrat[0])\n",
|
621 |
+
" \n",
|
622 |
+
" if add_durations_ratios:\n",
|
623 |
+
" r_list.append(adrat[0])\n",
|
624 |
+
"\n",
|
625 |
+
" ratios_list.append(r_list)\n",
|
626 |
+
"\n",
|
627 |
+
" #===================================================\n",
|
628 |
+
" \n",
|
629 |
+
" avg_ratios_list = []\n",
|
630 |
+
"\n",
|
631 |
+
" for r in ratios_list:\n",
|
632 |
+
" avg_ratios_list.append(sum(r) / len(r))\n",
|
633 |
+
"\n",
|
634 |
+
" #===================================================\n",
|
635 |
+
" \n",
|
636 |
+
" final_ratio = max(avg_ratios_list)\n",
|
637 |
+
" \n",
|
638 |
+
" if final_ratio > maximum_match_ratio_to_search_for:\n",
|
639 |
+
" final_ratio = 0\n",
|
640 |
+
"\n",
|
641 |
+
" final_ratios.append(final_ratio)\n",
|
642 |
+
"\n",
|
643 |
+
" #=======================================================\n",
|
644 |
+
"\n",
|
645 |
+
" print('-' * 70)\n",
|
646 |
+
"\n",
|
647 |
+
" max_ratios = sorted(final_ratios, reverse=True)[:number_of_top_ratios_MIDIs_to_collect]\n",
|
648 |
+
"\n",
|
649 |
+
" print('Max match ratio', max_ratios[0])\n",
|
650 |
+
" print('-' * 70)\n",
|
651 |
+
" print('Copying max ratios MIDIs...')\n",
|
652 |
+
"\n",
|
653 |
+
" for i in range(number_of_top_ratios_MIDIs_to_collect):\n",
|
654 |
+
"\n",
|
655 |
+
" max_ratio = max_ratios[i]\n",
|
656 |
+
" max_ratio_index = final_ratios.index(max_ratio)\n",
|
657 |
+
"\n",
|
658 |
+
" ffn = meta_data[max_ratio_index][0]\n",
|
659 |
+
" ffn_idx = [y[0] for y in LAMD_files_list].index(ffn)\n",
|
660 |
+
"\n",
|
661 |
+
" ff = LAMD_files_list[ffn_idx][1]\n",
|
662 |
+
"\n",
|
663 |
+
" #=======================================================\n",
|
664 |
+
" \n",
|
665 |
+
" dir_str = str(fn1)\n",
|
666 |
+
" copy_path = '/content/Output-MIDI-Dataset/'+dir_str\n",
|
667 |
+
" if not os.path.exists(copy_path):\n",
|
668 |
+
" os.mkdir(copy_path)\n",
|
669 |
+
"\n",
|
670 |
+
" shutil.copy2(f, copy_path+'/'+fn)\n",
|
671 |
+
"\n",
|
672 |
+
" fff = str(max_ratio * 100) + '_' + ffn\n",
|
673 |
+
"\n",
|
674 |
+
" shutil.copy2(ff, copy_path+'/'+fff)\n",
|
675 |
+
" \n",
|
676 |
+
" #=======================================================\n",
|
677 |
+
" \n",
|
678 |
+
" print('Done!')\n",
|
679 |
+
" print('=' * 70)\n",
|
680 |
+
"\n",
|
681 |
+
" #=======================================================\n",
|
682 |
+
"\n",
|
683 |
+
" # Processed files counter\n",
|
684 |
+
" files_count += 1\n",
|
685 |
+
" \n",
|
686 |
+
" except KeyboardInterrupt:\n",
|
687 |
+
" print('Quitting...')\n",
|
688 |
+
" print('Total number of processed MIDI files', files_count)\n",
|
689 |
+
" print('=' * 70)\n",
|
690 |
+
" break \n",
|
691 |
+
"\n",
|
692 |
+
" except Exception as ex:\n",
|
693 |
+
" print('WARNING !!!')\n",
|
694 |
+
" print('=' * 70)\n",
|
695 |
+
" print('Bad file:', f)\n",
|
696 |
+
" print('Error detected:', ex)\n",
|
697 |
+
" print('=' * 70)\n",
|
698 |
+
" continue\n",
|
699 |
+
"\n",
|
700 |
+
"print('Total number of processed MIDI files', files_count)\n",
|
701 |
+
"print('=' * 70)"
|
702 |
+
],
|
703 |
+
"metadata": {
|
704 |
+
"cellView": "form",
|
705 |
+
"id": "M0JWCPzBGNvh"
|
706 |
+
},
|
707 |
+
"execution_count": null,
|
708 |
+
"outputs": []
|
709 |
+
},
|
710 |
+
{
|
711 |
+
"cell_type": "markdown",
|
712 |
+
"metadata": {
|
713 |
+
"id": "YzCMd94Tu_gz"
|
714 |
+
},
|
715 |
+
"source": [
|
716 |
+
"# Congrats! You did it! :)"
|
717 |
+
]
|
718 |
+
}
|
719 |
+
],
|
720 |
+
"metadata": {
|
721 |
+
"colab": {
|
722 |
+
"machine_shape": "hm",
|
723 |
+
"private_outputs": true,
|
724 |
+
"provenance": []
|
725 |
+
},
|
726 |
+
"gpuClass": "standard",
|
727 |
+
"kernelspec": {
|
728 |
+
"display_name": "Python 3 (ipykernel)",
|
729 |
+
"language": "python",
|
730 |
+
"name": "python3"
|
731 |
+
},
|
732 |
+
"language_info": {
|
733 |
+
"codemirror_mode": {
|
734 |
+
"name": "ipython",
|
735 |
+
"version": 3
|
736 |
+
},
|
737 |
+
"file_extension": ".py",
|
738 |
+
"mimetype": "text/x-python",
|
739 |
+
"name": "python",
|
740 |
+
"nbconvert_exporter": "python",
|
741 |
+
"pygments_lexer": "ipython3",
|
742 |
+
"version": "3.9.7"
|
743 |
+
}
|
744 |
+
},
|
745 |
+
"nbformat": 4,
|
746 |
+
"nbformat_minor": 0
|
747 |
+
}
|
master_midi_dataset_search_and_filter.py
ADDED
@@ -0,0 +1,596 @@
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|
1 |
+
# -*- coding: utf-8 -*-
|
2 |
+
"""Master_MIDI_Dataset_Search_and_Filter.ipynb
|
3 |
+
|
4 |
+
Automatically generated by Colaboratory.
|
5 |
+
|
6 |
+
Original file is located at
|
7 |
+
https://colab.research.google.com/drive/1bHH8LjCdE2nhYOfBv4TdCltvW2PWxGol
|
8 |
+
|
9 |
+
# Master MIDI Dataset Search and Filter (ver. 1.0)
|
10 |
+
|
11 |
+
***
|
12 |
+
|
13 |
+
Powered by tegridy-tools: https://github.com/asigalov61/tegridy-tools
|
14 |
+
|
15 |
+
***
|
16 |
+
|
17 |
+
#### Project Los Angeles
|
18 |
+
|
19 |
+
#### Tegridy Code 2023
|
20 |
+
|
21 |
+
***
|
22 |
+
|
23 |
+
# (SETUP ENVIRONMENT)
|
24 |
+
"""
|
25 |
+
|
26 |
+
#@title Install all dependencies (run only once per session)
|
27 |
+
|
28 |
+
!git clone https://github.com/asigalov61/tegridy-tools
|
29 |
+
!pip install huggingface_hub
|
30 |
+
!pip install tqdm
|
31 |
+
|
32 |
+
#@title Import all needed modules
|
33 |
+
|
34 |
+
print('Loading core modules... Please wait...')
|
35 |
+
import os
|
36 |
+
import copy
|
37 |
+
from collections import Counter
|
38 |
+
import random
|
39 |
+
import pickle
|
40 |
+
from tqdm import tqdm
|
41 |
+
import pprint
|
42 |
+
import statistics
|
43 |
+
import shutil
|
44 |
+
|
45 |
+
print('Creating IO dirs... Please wait...')
|
46 |
+
|
47 |
+
if not os.path.exists('/content/Main-MIDI-Dataset'):
|
48 |
+
os.makedirs('/content/Main-MIDI-Dataset')
|
49 |
+
|
50 |
+
if not os.path.exists('/content/Master-MIDI-Dataset'):
|
51 |
+
os.makedirs('/content/Master-MIDI-Dataset')
|
52 |
+
|
53 |
+
if not os.path.exists('/content/Output-MIDI-Dataset'):
|
54 |
+
os.makedirs('/content/Output-MIDI-Dataset')
|
55 |
+
|
56 |
+
print('Loading TMIDIX module...')
|
57 |
+
os.chdir('/content/tegridy-tools/tegridy-tools')
|
58 |
+
|
59 |
+
import TMIDIX
|
60 |
+
|
61 |
+
print('Done!')
|
62 |
+
|
63 |
+
from huggingface_hub import hf_hub_download
|
64 |
+
|
65 |
+
os.chdir('/content/')
|
66 |
+
print('Enjoy! :)')
|
67 |
+
|
68 |
+
"""# (PREP MAIN MIDI DATASET)"""
|
69 |
+
|
70 |
+
#@title Download main MIDI dataset
|
71 |
+
print('=' * 70)
|
72 |
+
print('Downloading Los Angeles MIDI Dataset...Please wait...')
|
73 |
+
print('=' * 70)
|
74 |
+
|
75 |
+
hf_hub_download(repo_id='projectlosangeles/Los-Angeles-MIDI-Dataset',
|
76 |
+
filename='Los-Angeles-MIDI-Dataset-Ver-2-0-CC-BY-NC-SA.zip',
|
77 |
+
repo_type="dataset",
|
78 |
+
local_dir='/content/Main-MIDI-Dataset',
|
79 |
+
local_dir_use_symlinks=False)
|
80 |
+
print('=' * 70)
|
81 |
+
print('Done! Enjoy! :)')
|
82 |
+
print('=' * 70)
|
83 |
+
|
84 |
+
# Commented out IPython magic to ensure Python compatibility.
|
85 |
+
#@title Unzip main MIDI dataset
|
86 |
+
# %cd /content/Main-MIDI-Dataset/
|
87 |
+
|
88 |
+
print('=' * 70)
|
89 |
+
print('Unzipping Los Angeles MIDI Dataset...Please wait...')
|
90 |
+
!unzip 'Los-Angeles-MIDI-Dataset-Ver-2-0-CC-BY-NC-SA.zip'
|
91 |
+
print('=' * 70)
|
92 |
+
|
93 |
+
print('Done! Enjoy! :)')
|
94 |
+
print('=' * 70)
|
95 |
+
# %cd /content/
|
96 |
+
|
97 |
+
#@title Create main MIDI dataset files list
|
98 |
+
print('=' * 70)
|
99 |
+
print('Creating dataset files list...')
|
100 |
+
dataset_addr = "/content/Main-MIDI-Dataset/MIDIs"
|
101 |
+
|
102 |
+
# os.chdir(dataset_addr)
|
103 |
+
filez = list()
|
104 |
+
for (dirpath, dirnames, filenames) in os.walk(dataset_addr):
|
105 |
+
filez += [os.path.join(dirpath, file) for file in filenames]
|
106 |
+
|
107 |
+
if filez == []:
|
108 |
+
print('Could not find any MIDI files. Please check Dataset dir...')
|
109 |
+
print('=' * 70)
|
110 |
+
|
111 |
+
print('=' * 70)
|
112 |
+
print('Randomizing file list...')
|
113 |
+
random.shuffle(filez)
|
114 |
+
print('=' * 70)
|
115 |
+
|
116 |
+
LAMD_files_list = []
|
117 |
+
|
118 |
+
for f in tqdm(filez):
|
119 |
+
LAMD_files_list.append([f.split('/')[-1].split('.mid')[0], f])
|
120 |
+
print('Done!')
|
121 |
+
print('=' * 70)
|
122 |
+
|
123 |
+
#@title Load main MIDI dataset metadata
|
124 |
+
print('=' * 70)
|
125 |
+
print('Loading LAMDa data...Please wait...')
|
126 |
+
print('=' * 70)
|
127 |
+
print('Loading LAMDa META-DATA...')
|
128 |
+
meta_data = pickle.load(open('/content/Main-MIDI-Dataset/META_DATA/LAMDa_META_DATA.pickle', 'rb'))
|
129 |
+
print('Done!')
|
130 |
+
|
131 |
+
"""# (SEARCH AND FILTER)
|
132 |
+
|
133 |
+
### DO NOT FORGET TO UPLOAD YOUR MASTER DATASET TO "Master-MIDI-Dataset" FOLDER
|
134 |
+
"""
|
135 |
+
|
136 |
+
#@title Master MIDI Dataset Search and Filter
|
137 |
+
|
138 |
+
#@markdown NOTE: You can stop the search at any time to render partial results
|
139 |
+
|
140 |
+
number_of_top_ratios_MIDIs_to_collect = 10 #@param {type:"slider", min:1, max:20, step:1}
|
141 |
+
|
142 |
+
#@markdown Match ratio control option
|
143 |
+
|
144 |
+
maximum_match_ratio_to_search_for = 1 #@param {type:"slider", min:0, max:1, step:0.01}
|
145 |
+
|
146 |
+
#@markdown MIDI pitches search options
|
147 |
+
|
148 |
+
pitches_counts_cutoff_threshold_ratio = 0 #@param {type:"slider", min:0, max:1, step:0.05}
|
149 |
+
search_transposed_pitches = False #@param {type:"boolean"}
|
150 |
+
skip_exact_matches = False #@param {type:"boolean"}
|
151 |
+
|
152 |
+
#@markdown Additional search options
|
153 |
+
|
154 |
+
add_pitches_counts_ratios = True #@param {type:"boolean"}
|
155 |
+
add_timings_ratios = False #@param {type:"boolean"}
|
156 |
+
add_durations_ratios = False #@param {type:"boolean"}
|
157 |
+
|
158 |
+
print('=' * 70)
|
159 |
+
print('Master MIDI Dataset Search and Filter')
|
160 |
+
print('=' * 70)
|
161 |
+
|
162 |
+
###########
|
163 |
+
|
164 |
+
print('Loading MIDI files...')
|
165 |
+
print('This may take a while on a large dataset in particular.')
|
166 |
+
|
167 |
+
dataset_addr = "/content/Master-MIDI-Dataset"
|
168 |
+
# os.chdir(dataset_addr)
|
169 |
+
filez = list()
|
170 |
+
for (dirpath, dirnames, filenames) in os.walk(dataset_addr):
|
171 |
+
filez += [os.path.join(dirpath, file) for file in filenames]
|
172 |
+
print('=' * 70)
|
173 |
+
|
174 |
+
if filez == []:
|
175 |
+
print('Could not find any MIDI files. Please check Dataset dir...')
|
176 |
+
print('=' * 70)
|
177 |
+
|
178 |
+
print('Randomizing file list...')
|
179 |
+
random.shuffle(filez)
|
180 |
+
print('=' * 70)
|
181 |
+
###################
|
182 |
+
|
183 |
+
input_files_count = 0
|
184 |
+
files_count = 0
|
185 |
+
|
186 |
+
for f in filez:
|
187 |
+
try:
|
188 |
+
|
189 |
+
input_files_count += 1
|
190 |
+
|
191 |
+
fn = os.path.basename(f)
|
192 |
+
fn1 = fn.split('.mid')[0]
|
193 |
+
ext = fn.split('.')[-1]
|
194 |
+
|
195 |
+
if ext == 'mid' or ext == 'midi' or ext == 'kar':
|
196 |
+
|
197 |
+
print('Processing MIDI File #', files_count+1, 'out of', len(filez))
|
198 |
+
print('MIDI file name', fn)
|
199 |
+
print('-' * 70)
|
200 |
+
|
201 |
+
#=======================================================
|
202 |
+
|
203 |
+
score = TMIDIX.midi2ms_score(open(f, 'rb').read())
|
204 |
+
|
205 |
+
events_matrix = []
|
206 |
+
|
207 |
+
itrack = 1
|
208 |
+
|
209 |
+
while itrack < len(score):
|
210 |
+
for event in score[itrack]:
|
211 |
+
events_matrix.append(event)
|
212 |
+
itrack += 1
|
213 |
+
|
214 |
+
# Sorting...
|
215 |
+
events_matrix.sort(key=lambda x: x[1])
|
216 |
+
|
217 |
+
# recalculating timings
|
218 |
+
for e in events_matrix:
|
219 |
+
e[1] = int(e[1] / 10)
|
220 |
+
if e[0] == 'note':
|
221 |
+
e[2] = int(e[2] / 20)
|
222 |
+
|
223 |
+
# final processing...
|
224 |
+
|
225 |
+
melody_chords = []
|
226 |
+
|
227 |
+
patches = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
|
228 |
+
|
229 |
+
pe = events_matrix[0]
|
230 |
+
for e in events_matrix:
|
231 |
+
|
232 |
+
if e[0] == 'note':
|
233 |
+
# ['note', start_time, duration, channel, note, velocity]
|
234 |
+
time = max(0, min(255, e[1]-pe[1]))
|
235 |
+
duration = max(1, min(255, e[2]))
|
236 |
+
channel = max(0, min(15, e[3]))
|
237 |
+
|
238 |
+
if e[3] != 9:
|
239 |
+
instrument = max(0, min(127, patches[e[3]]))
|
240 |
+
else:
|
241 |
+
instrument = max(128, min(255, patches[e[3]]+128))
|
242 |
+
|
243 |
+
if e[3] != 9:
|
244 |
+
|
245 |
+
pitch = max(1, min(127, e[4]))
|
246 |
+
else:
|
247 |
+
pitch = max(129, min(255, e[4]+128))
|
248 |
+
|
249 |
+
if e[3] != 9:
|
250 |
+
velocity = max(1, min(127, e[5]))
|
251 |
+
else:
|
252 |
+
velocity = max(129, min(255, e[5]+128))
|
253 |
+
|
254 |
+
melody_chords.append([time, duration, channel, instrument, pitch, velocity])
|
255 |
+
|
256 |
+
if e[0] == 'patch_change':
|
257 |
+
# ['patch_change', dtime, channel, patch]
|
258 |
+
time = max(0, min(127, e[1]-pe[1]))
|
259 |
+
channel = max(0, min(15, e[2]))
|
260 |
+
patch = max(0, min(127, e[3]))
|
261 |
+
|
262 |
+
patches[channel] = patch
|
263 |
+
|
264 |
+
pe = e # Previous event
|
265 |
+
|
266 |
+
MATRIX = [[0]*256 for i in range(38)]
|
267 |
+
|
268 |
+
for m in melody_chords:
|
269 |
+
|
270 |
+
MATRIX[0][m[0]] += 1
|
271 |
+
MATRIX[1][m[1]] += 1
|
272 |
+
MATRIX[2][m[2]] += 1
|
273 |
+
MATRIX[3][m[3]] += 1
|
274 |
+
MATRIX[4][m[4]] += 1
|
275 |
+
MATRIX[5][m[5]] += 1
|
276 |
+
MATRIX[m[2]+6][m[3]] += 1
|
277 |
+
MATRIX[m[2]+22][m[4]] += 1
|
278 |
+
|
279 |
+
#==================================================
|
280 |
+
|
281 |
+
score = TMIDIX.midi2score(open(f, 'rb').read())
|
282 |
+
|
283 |
+
events_matrix = []
|
284 |
+
|
285 |
+
track_count = 0
|
286 |
+
|
287 |
+
for s in score:
|
288 |
+
|
289 |
+
if track_count > 0:
|
290 |
+
track = s
|
291 |
+
track.sort(key=lambda x: x[1])
|
292 |
+
events_matrix.extend(track)
|
293 |
+
else:
|
294 |
+
midi_ticks = s
|
295 |
+
|
296 |
+
track_count += 1
|
297 |
+
|
298 |
+
events_matrix.sort(key=lambda x: x[1])
|
299 |
+
|
300 |
+
mult_pitches_counts = []
|
301 |
+
|
302 |
+
for i in range(-6, 6):
|
303 |
+
|
304 |
+
events_matrix1 = []
|
305 |
+
|
306 |
+
for e in events_matrix:
|
307 |
+
|
308 |
+
ev = copy.deepcopy(e)
|
309 |
+
|
310 |
+
if e[0] == 'note':
|
311 |
+
if e[3] == 9:
|
312 |
+
ev[4] = ((e[4] % 128) + 128)
|
313 |
+
else:
|
314 |
+
ev[4] = ((e[4] % 128) + i)
|
315 |
+
|
316 |
+
events_matrix1.append(ev)
|
317 |
+
|
318 |
+
pitches_counts = [[y[0],y[1]] for y in Counter([y[4] for y in events_matrix1 if y[0] == 'note']).most_common()]
|
319 |
+
pitches_counts.sort(key=lambda x: x[0], reverse=True)
|
320 |
+
|
321 |
+
mult_pitches_counts.append(pitches_counts)
|
322 |
+
|
323 |
+
patches_list = sorted(list(set([y[3] for y in events_matrix if y[0] == 'patch_change'])))
|
324 |
+
|
325 |
+
#==================================================
|
326 |
+
|
327 |
+
ms_score = TMIDIX.midi2ms_score(open(f, 'rb').read())
|
328 |
+
|
329 |
+
ms_events_matrix = []
|
330 |
+
|
331 |
+
itrack1 = 1
|
332 |
+
|
333 |
+
while itrack1 < len(ms_score):
|
334 |
+
for event in ms_score[itrack1]:
|
335 |
+
if event[0] == 'note':
|
336 |
+
ms_events_matrix.append(event)
|
337 |
+
itrack1 += 1
|
338 |
+
|
339 |
+
ms_events_matrix.sort(key=lambda x: x[1])
|
340 |
+
|
341 |
+
|
342 |
+
chords = []
|
343 |
+
pe = ms_events_matrix[0]
|
344 |
+
cho = []
|
345 |
+
for e in ms_events_matrix:
|
346 |
+
if (e[1] - pe[1]) == 0:
|
347 |
+
if e[3] != 9:
|
348 |
+
if (e[4] % 12) not in cho:
|
349 |
+
cho.append(e[4] % 12)
|
350 |
+
else:
|
351 |
+
if len(cho) > 0:
|
352 |
+
chords.append(sorted(cho))
|
353 |
+
cho = []
|
354 |
+
if e[3] != 9:
|
355 |
+
if (e[4] % 12) not in cho:
|
356 |
+
cho.append(e[4] % 12)
|
357 |
+
|
358 |
+
pe = e
|
359 |
+
|
360 |
+
if len(cho) > 0:
|
361 |
+
chords.append(sorted(cho))
|
362 |
+
|
363 |
+
ms_chords_counts = sorted([[list(key), val] for key,val in Counter([tuple(c) for c in chords if len(c) > 1]).most_common()], reverse=True, key = lambda x: x[1])
|
364 |
+
|
365 |
+
times = []
|
366 |
+
pt = ms_events_matrix[0][1]
|
367 |
+
start = True
|
368 |
+
for e in ms_events_matrix:
|
369 |
+
if (e[1]-pt) != 0 or start == True:
|
370 |
+
times.append((e[1]-pt))
|
371 |
+
start = False
|
372 |
+
pt = e[1]
|
373 |
+
|
374 |
+
durs = [e[2] for e in ms_events_matrix]
|
375 |
+
vels = [e[5] for e in ms_events_matrix]
|
376 |
+
|
377 |
+
avg_time = int(sum(times) / len(times))
|
378 |
+
avg_dur = int(sum(durs) / len(durs))
|
379 |
+
|
380 |
+
mode_time = statistics.mode(times)
|
381 |
+
mode_dur = statistics.mode(durs)
|
382 |
+
|
383 |
+
median_time = int(statistics.median(times))
|
384 |
+
median_dur = int(statistics.median(durs))
|
385 |
+
|
386 |
+
#=======================================================
|
387 |
+
|
388 |
+
print('Searching for matches...Please wait...')
|
389 |
+
print('-' * 70)
|
390 |
+
|
391 |
+
final_ratios = []
|
392 |
+
|
393 |
+
for d in tqdm(meta_data):
|
394 |
+
|
395 |
+
p_counts = d[1][10][1]
|
396 |
+
p_counts.sort(reverse = True, key = lambda x: x[1])
|
397 |
+
max_p_count = p_counts[0][1]
|
398 |
+
trimmed_p_counts = [y for y in p_counts if y[1] >= (max_p_count * pitches_counts_cutoff_threshold_ratio)]
|
399 |
+
total_p_counts = sum([y[1] for y in trimmed_p_counts])
|
400 |
+
|
401 |
+
if search_transposed_pitches:
|
402 |
+
search_pitches = mult_pitches_counts
|
403 |
+
else:
|
404 |
+
search_pitches = [mult_pitches_counts[6]]
|
405 |
+
|
406 |
+
#===================================================
|
407 |
+
|
408 |
+
ratios_list = []
|
409 |
+
|
410 |
+
#===================================================
|
411 |
+
|
412 |
+
atrat = [0]
|
413 |
+
|
414 |
+
if add_timings_ratios:
|
415 |
+
|
416 |
+
source_times = [avg_time,
|
417 |
+
median_time,
|
418 |
+
mode_time]
|
419 |
+
|
420 |
+
match_times = meta_data[0][1][3][1]
|
421 |
+
|
422 |
+
times_ratios = []
|
423 |
+
|
424 |
+
for i in range(len(source_times)):
|
425 |
+
maxtratio = max(source_times[i], match_times[i])
|
426 |
+
mintratio = min(source_times[i], match_times[i])
|
427 |
+
times_ratios.append(mintratio / maxtratio)
|
428 |
+
|
429 |
+
avg_times_ratio = sum(times_ratios) / len(times_ratios)
|
430 |
+
|
431 |
+
atrat[0] = avg_times_ratio
|
432 |
+
|
433 |
+
#===================================================
|
434 |
+
|
435 |
+
adrat = [0]
|
436 |
+
|
437 |
+
if add_durations_ratios:
|
438 |
+
|
439 |
+
source_durs = [avg_dur,
|
440 |
+
median_dur,
|
441 |
+
mode_dur]
|
442 |
+
|
443 |
+
match_durs = meta_data[0][1][4][1]
|
444 |
+
|
445 |
+
durs_ratios = []
|
446 |
+
|
447 |
+
for i in range(len(source_durs)):
|
448 |
+
maxtratio = max(source_durs[i], match_durs[i])
|
449 |
+
mintratio = min(source_durs[i], match_durs[i])
|
450 |
+
durs_ratios.append(mintratio / maxtratio)
|
451 |
+
|
452 |
+
avg_durs_ratio = sum(durs_ratios) / len(durs_ratios)
|
453 |
+
|
454 |
+
adrat[0] = avg_durs_ratio
|
455 |
+
|
456 |
+
#===================================================
|
457 |
+
|
458 |
+
for m in search_pitches:
|
459 |
+
|
460 |
+
sprat = []
|
461 |
+
|
462 |
+
m.sort(reverse = True, key = lambda x: x[1])
|
463 |
+
max_pitches_count = m[0][1]
|
464 |
+
trimmed_pitches_counts = [y for y in m if y[1] >= (max_pitches_count * pitches_counts_cutoff_threshold_ratio)]
|
465 |
+
total_pitches_counts = sum([y[1] for y in trimmed_pitches_counts])
|
466 |
+
|
467 |
+
same_pitches = set([T[0] for T in trimmed_p_counts]) & set([m[0] for m in trimmed_pitches_counts])
|
468 |
+
num_same_pitches = len(same_pitches)
|
469 |
+
same_pitches_ratio = (num_same_pitches / len(set([m[0] for m in trimmed_p_counts]+[T[0] for T in trimmed_pitches_counts])))
|
470 |
+
|
471 |
+
if skip_exact_matches:
|
472 |
+
if same_pitches_ratio == 1:
|
473 |
+
same_pitches_ratio = 0
|
474 |
+
|
475 |
+
sprat.append(same_pitches_ratio)
|
476 |
+
|
477 |
+
#===================================================
|
478 |
+
|
479 |
+
spcrat = [0]
|
480 |
+
|
481 |
+
if add_pitches_counts_ratios:
|
482 |
+
|
483 |
+
same_trimmed_p_counts = sorted([T for T in trimmed_p_counts if T[0] in same_pitches], reverse = True)
|
484 |
+
same_trimmed_pitches_counts = sorted([T for T in trimmed_pitches_counts if T[0] in same_pitches], reverse = True)
|
485 |
+
|
486 |
+
same_trimmed_p_counts_ratios = [[s[0], s[1] / total_p_counts] for s in same_trimmed_p_counts]
|
487 |
+
same_trimmed_pitches_counts_ratios = [[s[0], s[1] / total_pitches_counts] for s in same_trimmed_pitches_counts]
|
488 |
+
|
489 |
+
same_pitches_counts_ratios = []
|
490 |
+
|
491 |
+
for i in range(len(same_trimmed_p_counts_ratios)):
|
492 |
+
mincratio = min(same_trimmed_p_counts_ratios[i][1], same_trimmed_pitches_counts_ratios[i][1])
|
493 |
+
maxcratio = max(same_trimmed_p_counts_ratios[i][1], same_trimmed_pitches_counts_ratios[i][1])
|
494 |
+
same_pitches_counts_ratios.append([same_trimmed_p_counts_ratios[i][0], mincratio / maxcratio])
|
495 |
+
|
496 |
+
same_counts_ratios = [s[1] for s in same_pitches_counts_ratios]
|
497 |
+
|
498 |
+
if len(same_counts_ratios) > 0:
|
499 |
+
avg_same_pitches_counts_ratio = sum(same_counts_ratios) / len(same_counts_ratios)
|
500 |
+
else:
|
501 |
+
avg_same_pitches_counts_ratio = 0
|
502 |
+
|
503 |
+
spcrat[0] = avg_same_pitches_counts_ratio
|
504 |
+
|
505 |
+
#===================================================
|
506 |
+
|
507 |
+
r_list = [sprat[0]]
|
508 |
+
|
509 |
+
if add_pitches_counts_ratios:
|
510 |
+
r_list.append(spcrat[0])
|
511 |
+
|
512 |
+
if add_timings_ratios:
|
513 |
+
r_list.append(atrat[0])
|
514 |
+
|
515 |
+
if add_durations_ratios:
|
516 |
+
r_list.append(adrat[0])
|
517 |
+
|
518 |
+
ratios_list.append(r_list)
|
519 |
+
|
520 |
+
#===================================================
|
521 |
+
|
522 |
+
avg_ratios_list = []
|
523 |
+
|
524 |
+
for r in ratios_list:
|
525 |
+
avg_ratios_list.append(sum(r) / len(r))
|
526 |
+
|
527 |
+
#===================================================
|
528 |
+
|
529 |
+
final_ratio = max(avg_ratios_list)
|
530 |
+
|
531 |
+
if final_ratio > maximum_match_ratio_to_search_for:
|
532 |
+
final_ratio = 0
|
533 |
+
|
534 |
+
final_ratios.append(final_ratio)
|
535 |
+
|
536 |
+
#=======================================================
|
537 |
+
|
538 |
+
print('-' * 70)
|
539 |
+
|
540 |
+
max_ratios = sorted(final_ratios, reverse=True)[:number_of_top_ratios_MIDIs_to_collect]
|
541 |
+
|
542 |
+
print('Max match ratio', max_ratios[0])
|
543 |
+
print('-' * 70)
|
544 |
+
print('Copying max ratios MIDIs...')
|
545 |
+
|
546 |
+
for i in range(number_of_top_ratios_MIDIs_to_collect):
|
547 |
+
|
548 |
+
max_ratio = max_ratios[i]
|
549 |
+
max_ratio_index = final_ratios.index(max_ratio)
|
550 |
+
|
551 |
+
ffn = meta_data[max_ratio_index][0]
|
552 |
+
ffn_idx = [y[0] for y in LAMD_files_list].index(ffn)
|
553 |
+
|
554 |
+
ff = LAMD_files_list[ffn_idx][1]
|
555 |
+
|
556 |
+
#=======================================================
|
557 |
+
|
558 |
+
dir_str = str(fn1)
|
559 |
+
copy_path = '/content/Output-MIDI-Dataset/'+dir_str
|
560 |
+
if not os.path.exists(copy_path):
|
561 |
+
os.mkdir(copy_path)
|
562 |
+
|
563 |
+
shutil.copy2(f, copy_path+'/'+fn)
|
564 |
+
|
565 |
+
fff = str(max_ratio * 100) + '_' + ffn
|
566 |
+
|
567 |
+
shutil.copy2(ff, copy_path+'/'+fff)
|
568 |
+
|
569 |
+
#=======================================================
|
570 |
+
|
571 |
+
print('Done!')
|
572 |
+
print('=' * 70)
|
573 |
+
|
574 |
+
#=======================================================
|
575 |
+
|
576 |
+
# Processed files counter
|
577 |
+
files_count += 1
|
578 |
+
|
579 |
+
except KeyboardInterrupt:
|
580 |
+
print('Quitting...')
|
581 |
+
print('Total number of processed MIDI files', files_count)
|
582 |
+
print('=' * 70)
|
583 |
+
break
|
584 |
+
|
585 |
+
except Exception as ex:
|
586 |
+
print('WARNING !!!')
|
587 |
+
print('=' * 70)
|
588 |
+
print('Bad file:', f)
|
589 |
+
print('Error detected:', ex)
|
590 |
+
print('=' * 70)
|
591 |
+
continue
|
592 |
+
|
593 |
+
print('Total number of processed MIDI files', files_count)
|
594 |
+
print('=' * 70)
|
595 |
+
|
596 |
+
"""# Congrats! You did it! :)"""
|