update shazam and liblrc services. adding text synchronizations

core/separate.py

@@ -1,4 +1,11 @@
-"""Vocal separation via unblend (Mel-Band RoFormer)."""
+"""Vocal separation via unblend (Mel-Band RoFormer).
+
+Two entry points:
+
+- separate_vocals()       single file, subprocess per call (sequential mode)
+- separate_vocals_batch() many files in ONE subprocess, model loaded once
+                          (staged mode — big speedup on batches)
+"""
 from __future__ import annotations
 
 import os
@@ -6,6 +13,19 @@ import subprocess
 from pathlib import Path
 
 
+def _build_env(custom_kernels: bool) -> dict:
+    env = os.environ.copy()
+    env["UNBLEND_CUSTOM_KERNELS"] = "1" if custom_kernels else "0"
+    return env
+
+
+def _check_result(result: subprocess.CompletedProcess, what: str) -> None:
+    if result.returncode != 0:
+        raise RuntimeError(
+            f"unblend failed ({what}):\n{result.stderr.strip()[:1200]}"
+        )
+
+
 def separate_vocals(
     input_wav: Path,
     work_dir: Path,
@@ -13,8 +33,9 @@ def separate_vocals(
     isolate_stem: str = "vocals",
     unblend_path: str = "unblend",
     custom_kernels: bool = False,
+    device: str = "cuda",
 ) -> Path:
-    """Separate the isolated stem from input_wav. Returns path to the stem WAV."""
+    """Separate one file. Returns path to the isolated stem WAV."""
     work_dir.mkdir(parents=True, exist_ok=True)
     output_pattern = work_dir / "{track}" / "{stem}.wav"
     cmd = [
@@ -22,15 +43,10 @@ def separate_vocals(
         "-m", model,
         "-o", str(output_pattern),
         "--isolate-stem", isolate_stem,
+        "--device", device,
     ]
-    env = os.environ.copy()
-    env["UNBLEND_CUSTOM_KERNELS"] = "1" if custom_kernels else "0"
-
-    result = subprocess.run(cmd, capture_output=True, text=True, env=env)
-    if result.returncode != 0:
-        raise RuntimeError(
-            f"unblend failed for {input_wav.name}:\n{result.stderr.strip()[:800]}"
-        )
+    result = subprocess.run(cmd, capture_output=True, text=True, env=_build_env(custom_kernels))
+    _check_result(result, input_wav.name)
 
     candidates = sorted(work_dir.rglob(f"{isolate_stem}.wav"))
     if not candidates:
@@ -38,3 +54,62 @@ def separate_vocals(
             f"unblend finished but stem '{isolate_stem}.wav' was not found in {work_dir}"
         )
     return candidates[0]
+
+
+def separate_vocals_batch(
+    input_wavs: list[Path],
+    work_root: Path,
+    model: str = "bs_roformer_anvuew",
+    isolate_stem: str = "vocals",
+    unblend_path: str = "unblend",
+    custom_kernels: bool = False,
+    device: str = "cuda",
+) -> dict[Path, Path]:
+    """Separate many files in one unblend invocation.
+
+    Input WAVs are expected to live in distinct directories
+    (e.g. <work_root>/<stem>/convert.wav). The output pattern uses {parent}
+    so each result lands next to its input as <parent>/vocals.wav.
+
+    Returns: {input_path: vocal_path}
+    """
+    if not input_wavs:
+        return {}
+
+    work_root.mkdir(parents=True, exist_ok=True)
+    output_pattern = work_root / "{parent}" / "{stem}.wav"
+
+    cmd = [
+        unblend_path, "separate",
+        *[str(p) for p in input_wavs],
+        "-m", model,
+        "-o", str(output_pattern),
+        "--isolate-stem", isolate_stem,
+        "--device", device,
+    ]
+
+    result = subprocess.run(cmd, capture_output=True, text=True, env=_build_env(custom_kernels))
+    _check_result(result, f"{len(input_wavs)} files")
+
+    mapping: dict[Path, Path] = {}
+    missing: list[Path] = []
+    for src in input_wavs:
+        candidate = src.parent / f"{isolate_stem}.wav"
+        if candidate.exists():
+            mapping[src] = candidate
+        else:
+            missing.append(src)
+
+    if missing:
+        # Fallback: search anywhere under work_root
+        found = sorted(work_root.rglob(f"{isolate_stem}.wav"))
+        if len(found) == len(input_wavs):
+            for src, dst in zip(input_wavs, found):
+                mapping[src] = dst
+        else:
+            names = ", ".join(p.name for p in missing[:3])
+            raise RuntimeError(
+                f"unblend finished but outputs missing for {len(missing)} file(s): {names}"
+            )
+
+    return mapping