Update to df3, improve cleanup

app.py

@@ -3,7 +3,7 @@ import math
 import os
 import tempfile
 import time
-from typing import Optional, Tuple, Union
+from typing import List, Optional, Tuple, Union
 
 import gradio as gr
 import matplotlib.pyplot as plt
@@ -19,7 +19,7 @@ from df.enhance import enhance, init_df, load_audio, save_audio
 from df.io import resample
 
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-model, df, _ = init_df("./DeepFilterNet2", config_allow_defaults=True)
+model, df, _ = init_df(config_allow_defaults=True)
 model = model.to(device=device).eval()
 
 fig_noisy: plt.Figure
@@ -100,7 +100,7 @@ def load_audio_gradio(
     return audio, meta
 
 
-def demo_fn(speech_upl: str, noise_type: str, snr: int, mic_input: str):
+def demo_fn(speech_upl: str, noise_type: str, snr: int, mic_input: Optional[str] = None):
     if mic_input:
         speech_upl = mic_input
     sr = config("sr", 48000, int, section="df")
@@ -147,16 +147,10 @@ def demo_fn(speech_upl: str, noise_type: str, snr: int, mic_input: str):
     ax_enh.clear()
     noisy_im = spec_im(sample, sr=sr, figure=fig_noisy, ax=ax_noisy)
     enh_im = spec_im(enhanced, sr=sr, figure=fig_enh, ax=ax_enh)
-    # Cleanup some old wav files
-    if os.path.exists("/tmp"):
-        days = 1
-        for f in glob.glob("/tmp/*wav"):
-            is_old = (time.time() - os.path.getmtime(f)) / 3600 > 24 * days
-            if is_old and f not in (enhanced_wav, noisy_wav):
-                try:
-                    os.remove(f)
-                except Exception as e:
-                    print(f"failed to remove file {f}: {e}")
+    filter = [speech_upl, noisy_wav, enhanced_wav]
+    if mic_input is not None and mic_input != "":
+        filter.append(mic_input)
+    cleanup_tmp(filter)
     return noisy_wav, noisy_im, enhanced_wav, enh_im
 
 
@@ -257,6 +251,19 @@ def spec_im(
     return Image.frombytes("RGB", figure.canvas.get_width_height(), figure.canvas.tostring_rgb())
 
 
+def cleanup_tmp(filter: List[str] = [], hours_keep=2):
+    # Cleanup some old wav files
+    if os.path.exists("/tmp"):
+        for f in glob.glob("/tmp/*"):
+            is_old = (time.time() - os.path.getmtime(f)) / 3600 > hours_keep
+            if is_old and f not in filter:
+                try:
+                    os.remove(f)
+                    logger.info(f"Removed file {f}")
+                except Exception as e:
+                    logger.warning(f"failed to remove file {f}: {e}")
+
+
 def toggle(choice):
     if choice == "mic":
         return gr.update(visible=True, value=None), gr.update(visible=False, value=None)
@@ -320,5 +327,5 @@ with gr.Blocks() as demo:
     ),
     gr.Markdown(open("usage.md").read())
 
-
+cleanup_tmp()
 demo.launch(enable_queue=True)