OWW model tester

attempts to find models that would stop OWW from starting

wyoming-openwakeword/test_oww_models.py

@@ -0,0 +1,73 @@
+
+#!/usr/bin/env python3
+import os
+import time
+import argparse
+from pathlib import Path
+
+def try_import_tflite():
+    try:
+        from tflite_runtime.interpreter import Interpreter
+        return Interpreter
+    except ImportError:
+        try:
+            from ai_edge_litert.interpreter import Interpreter
+            return Interpreter
+        except ImportError:
+            raise ImportError("Neither tflite_runtime nor ai_edge_litert is installed.")
+
+def test_model(model_path, Interpreter):
+    try:
+        start = time.time()
+        interpreter = Interpreter(model_path=str(model_path))
+        interpreter.allocate_tensors()
+        elapsed = time.time() - start
+        return True, f"OK (loaded in {elapsed:.2f}s)"
+    except Exception as e:
+        return False, f"FAIL ({str(e)})"
+
+def main():
+    parser = argparse.ArgumentParser(description="Test all TFLite models in a directory.")
+    parser.add_argument("--models-dir", type=str, default=str(Path.home() / "wyoming-openwakeword" / "wyoming_openwakeword" / "models"),
+                        help="Path to the models directory")
+    parser.add_argument("--skip-non-detection", action="store_true",
+                        help="Skip known non-detection models (embedding_model.tflite, melspectrogram.tflite)")
+    parser.add_argument("--quiet", action="store_true", help="Only show failures")
+    parser.add_argument("--csv", type=str, help="Output results to CSV file")
+
+    args = parser.parse_args()
+    models_dir = Path(args.models_dir)
+
+    Interpreter = try_import_tflite()
+
+    if not models_dir.exists():
+        print(f"Models directory not found: {models_dir}")
+        return
+
+    skip_list = {"embedding_model.tflite", "melspectrogram.tflite"}
+    results = []
+
+    for model_file in sorted(models_dir.glob("*.tflite")):
+        if args.skip_non_detection and model_file.name in skip_list:
+            if not args.quiet:
+                print(f"SKIP {model_file.name}")
+            continue
+
+        ok, message = test_model(model_file, Interpreter)
+        results.append((model_file.name, ok, message))
+
+        if not args.quiet or not ok:
+            status = "PASS" if ok else "FAIL"
+            print(f"{status} {model_file.name}: {message}")
+
+    if args.csv:
+        import csv
+        with open(args.csv, "w", newline="") as f:
+            writer = csv.writer(f)
+            writer.writerow(["Model", "Status", "Message"])
+            for name, ok, msg in results:
+                writer.writerow([name, "PASS" if ok else "FAIL", msg])
+        print(f"Results written to {args.csv}")
+
+if __name__ == "__main__":
+    main()

wyoming-openwakeword/test_oww_models.txt

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+cd wyoming-openwakeword/
+source .venv/bin/activate
+python3 ~/linux-voice-assistant/wyoming-openwakeword/test_oww_models.py --skip-non-detection --models-dir /home/pi/wyoming-openwakeword/wyoming_openwakeword/models 
+deactivate
+
+
+
+# basic
+python3 test_oww_models.py
+
+# skip non-detection models
+python3 test_oww_models.py --skip-non-detection
+
+# specify a custom folder
+python3 test_oww_models.py --models-dir /home/pi/wyoming-openwakeword/wyoming_openwakeword/models
+
+# quiet mode + CSV
+python3 test_oww_models.py --quiet --csv /home/pi/model_check.csv
+