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aed1d05 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 | #!/usr/bin/env python3
"""
Validate generated MIDI files for quality.
Checks:
- File integrity (can be parsed)
- Note count and distribution
- Pitch diversity
- Temporal structure
- Velocity patterns
"""
import argparse
import json
from pathlib import Path
from collections import Counter
import numpy as np
import pretty_midi
from tqdm import tqdm
def analyze_midi(midi_path: str) -> dict:
"""Analyze a single MIDI file."""
try:
pm = pretty_midi.PrettyMIDI(midi_path)
except Exception as e:
return {"valid": False, "error": str(e)}
# Collect all notes
all_notes = []
for inst in pm.instruments:
all_notes.extend(inst.notes)
if len(all_notes) == 0:
return {"valid": False, "error": "No notes found"}
# Extract features
pitches = [n.pitch for n in all_notes]
velocities = [n.velocity for n in all_notes]
durations = [n.end - n.start for n in all_notes]
starts = [n.start for n in all_notes]
# Pitch analysis
unique_pitches = len(set(pitches))
pitch_range = max(pitches) - min(pitches)
pitch_mean = np.mean(pitches)
pitch_std = np.std(pitches)
# Velocity analysis
velocity_mean = np.mean(velocities)
velocity_std = np.std(velocities)
# Duration analysis
duration_mean = np.mean(durations)
duration_std = np.std(durations)
# Temporal analysis
total_duration = pm.get_end_time()
note_density = len(all_notes) / total_duration if total_duration > 0 else 0
# Repetition analysis
pitch_counter = Counter(pitches)
most_common_pitch_ratio = pitch_counter.most_common(1)[0][1] / len(pitches)
return {
"valid": True,
"note_count": len(all_notes),
"unique_pitches": unique_pitches,
"pitch_range": pitch_range,
"pitch_mean": round(pitch_mean, 2),
"pitch_std": round(pitch_std, 2),
"velocity_mean": round(velocity_mean, 2),
"velocity_std": round(velocity_std, 2),
"duration_mean": round(duration_mean, 4),
"duration_std": round(duration_std, 4),
"total_duration": round(total_duration, 2),
"note_density": round(note_density, 2),
"most_common_pitch_ratio": round(most_common_pitch_ratio, 4),
"num_instruments": len(pm.instruments),
}
def validate_batch(
midi_dir: str,
output_path: str = None,
min_notes: int = 20,
max_notes: int = 2000,
min_unique_pitches: int = 5,
min_duration: float = 5.0,
max_repetition_ratio: float = 0.5,
):
"""Validate a batch of MIDI files."""
midi_dir = Path(midi_dir)
midi_files = list(midi_dir.rglob("*.mid")) + list(midi_dir.rglob("*.midi"))
print(f"Found {len(midi_files)} MIDI files")
results = {
"total": len(midi_files),
"valid": 0,
"invalid": 0,
"passed_quality": 0,
"failed_quality": 0,
"files": [],
}
quality_failures = Counter()
for midi_path in tqdm(midi_files, desc="Validating"):
analysis = analyze_midi(str(midi_path))
analysis["path"] = str(midi_path)
if not analysis.get("valid"):
results["invalid"] += 1
analysis["quality_passed"] = False
quality_failures["parse_error"] += 1
else:
results["valid"] += 1
# Quality checks
failed = []
if analysis["note_count"] < min_notes:
failed.append("too_few_notes")
if analysis["note_count"] > max_notes:
failed.append("too_many_notes")
if analysis["unique_pitches"] < min_unique_pitches:
failed.append("low_pitch_diversity")
if analysis["total_duration"] < min_duration:
failed.append("too_short")
if analysis["most_common_pitch_ratio"] > max_repetition_ratio:
failed.append("too_repetitive")
if failed:
results["failed_quality"] += 1
analysis["quality_passed"] = False
analysis["quality_failures"] = failed
for f in failed:
quality_failures[f] += 1
else:
results["passed_quality"] += 1
analysis["quality_passed"] = True
results["files"].append(analysis)
# Summary stats
valid_analyses = [f for f in results["files"] if f.get("valid")]
if valid_analyses:
results["summary"] = {
"avg_notes": round(np.mean([f["note_count"] for f in valid_analyses]), 1),
"avg_unique_pitches": round(np.mean([f["unique_pitches"] for f in valid_analyses]), 1),
"avg_duration": round(np.mean([f["total_duration"] for f in valid_analyses]), 1),
"avg_note_density": round(np.mean([f["note_density"] for f in valid_analyses]), 2),
}
results["quality_failure_counts"] = dict(quality_failures)
# Print summary
print("\n" + "="*60)
print("Validation Summary")
print("="*60)
print(f"Total files: {results['total']}")
print(f"Valid (parseable): {results['valid']} ({results['valid']/results['total']*100:.1f}%)")
print(f"Invalid: {results['invalid']}")
print(f"Passed quality: {results['passed_quality']} ({results['passed_quality']/results['total']*100:.1f}%)")
print(f"Failed quality: {results['failed_quality']}")
if valid_analyses:
print(f"\nValid file statistics:")
print(f" Avg notes: {results['summary']['avg_notes']}")
print(f" Avg unique pitches: {results['summary']['avg_unique_pitches']}")
print(f" Avg duration: {results['summary']['avg_duration']}s")
print(f" Avg note density: {results['summary']['avg_note_density']} notes/s")
if quality_failures:
print(f"\nQuality failure breakdown:")
for reason, count in quality_failures.most_common():
print(f" {reason}: {count}")
# Save results
if output_path:
with open(output_path, "w") as f:
json.dump(results, f, indent=2)
print(f"\nResults saved to {output_path}")
return results
def main():
parser = argparse.ArgumentParser(description="Validate MIDI files")
parser.add_argument(
"midi_dir",
type=str,
help="Directory containing MIDI files",
)
parser.add_argument(
"--output",
type=str,
default="validation_results.json",
help="Output JSON file path",
)
parser.add_argument(
"--min-notes",
type=int,
default=20,
help="Minimum note count",
)
parser.add_argument(
"--max-notes",
type=int,
default=2000,
help="Maximum note count",
)
args = parser.parse_args()
validate_batch(
args.midi_dir,
args.output,
min_notes=args.min_notes,
max_notes=args.max_notes,
)
if __name__ == "__main__":
main()
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