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app.py

@@ -59,59 +59,54 @@ model.eval()
    
 @spaces.GPU
 def enhance(path):
-    wav_np, orig_sr = librosa.load(path, sr=None)
-    if orig_sr!=SR: wav_np=librosa.resample(wav_np, orig_sr, SR)
-    wav = torch.from_numpy(wav_np).float().to(device)
-    norm= torch.sqrt(len(wav)/torch.sum(wav**2)); wav=(wav*norm).unsqueeze(0)
-    amp,pha,_ = mag_phase_stft(wav,**stft_cfg,compress_factor=model_cfg["compress_factor"])
-    amp_g,pha_g = model(amp,pha)
-    out = mag_phase_istft(amp_g,pha_g,**stft_cfg,compress_factor=model_cfg["compress_factor"])
-    out=(out/norm).squeeze().cpu().numpy()
-    if orig_sr!=SR: out=librosa.resample(out,SR,orig_sr)
+    # load & resample
+    wav, orig_sr = librosa.load(path, sr=None)
+    if orig_sr != SR: wav = librosa.resample(wav, orig_sr, SR)
+    # normalize + to-tensor
+    x = torch.from_numpy(wav).float().to(device)
+    norm = torch.sqrt(len(x)/torch.sum(x**2)); x=(x*norm).unsqueeze(0)
+    # STFT → model → ISTFT
+    amp,pha,_ = mag_phase_stft(x, **stft_cfg, compress_factor=model_cfg["compress_factor"])
+    amp2,pha2 = model(amp,pha)
+    out = mag_phase_istft(amp2,pha2, **stft_cfg, compress_factor=model_cfg["compress_factor"])
+    out = (out/norm).squeeze().cpu().numpy()
+    # back to orig_sr
+    if orig_sr != SR: out = librosa.resample(out, SR, orig_sr)
+    # save
     sf.write("enhanced.wav", out, orig_sr)
-
+    # spectrogram
     D = librosa.stft(out, n_fft=1024, hop_length=512)
     S = librosa.amplitude_to_db(np.abs(D), ref=np.max)
     fig,ax=plt.subplots(figsize=(6,3))
-    librosa.display.specshow(S,sr=orig_sr,hop_length=512,x_axis="time",y_axis="hz",ax=ax)
+    librosa.display.specshow(S, sr=orig_sr, hop_length=512, x_axis="time", y_axis="hz", ax=ax)
     ax.set_title("Enhanced Spectrogram"); plt.colorbar(format="%+2.0f dB",ax=ax)
     return "enhanced.wav", fig
 
-# — custom CSS to remove all borders and style panels —
 CSS = """
-.gr-block {padding:2rem;}
-#input-audio .gradio-component, #output-audio .gradio-component, #spec-plot .gradio-component {
-  border:1px solid #ddd; border-radius:8px; background:#fafafa; padding:1rem;
-}
-#input-audio label, #output-audio label, #spec-plot label {font-weight:600; color:#333;}
-#run-btn {width:100%; margin-top:1rem;}
+#title, #subtitle {text-align:center;}
+.duplicate-button {margin:1em auto; display:block;}
+#in-audio .gradio-component {border:2px dashed #888; border-radius:8px;}
+#run {width:100%; margin-top:0.5em;}
 """
 
-with gr.Blocks(css=CSS, theme=gr.themes.Default()) as demo:
-    gr.HTML("<h2 style='text-align:center;'>🎧 SEMamba: Speech Enhancement</h2>")
-    gr.HTML("<p style='text-align:center;color:#555;'>Upload or record noisy speech, then click Enhance to clean it.</p>")
+with gr.Blocks(css=CSS, theme="soft") as demo:
+    gr.HTML("<h1 id='title'>🎧 SEMamba: Speech Enhancement</h1>")
+    gr.HTML("<p id='subtitle'>Upload or record your noisy clip, hit Enhance, and see the spectrogram.</p>")
+    gr.DuplicateButton(value="Duplicate Space for private use", elem_classes="duplicate-button")
 
     with gr.Row():
-        with gr.Column():
-            input_audio = gr.Audio(
+        with gr.Column(scale=1):
+            audio_in = gr.Audio(
                 sources=["upload","microphone"],
                 type="filepath",
-                label="Input Audio",
-                elem_id="input-audio"
-            )
-            run_btn = gr.Button("Enhance", variant="primary", elem_id="run-btn")
-
-        with gr.Column():
-            output_audio = gr.Audio(
-                type="filepath",
-                label="Enhanced Audio",
-                elem_id="output-audio"
-            )
-            spec_plot = gr.Plot(
-                label="Enhanced Spectrogram",
-                elem_id="spec-plot"
+                label="Your Noisy Audio",
+                elem_id="in-audio"
             )
+            run_btn = gr.Button("Enhance Now 🚀", variant="primary", elem_id="run")
+        with gr.Column(scale=1):
+            audio_out = gr.Audio(type="filepath", label="Enhanced Audio")
+            spec_out  = gr.Plot(label="Spectrogram")
 
-    run_btn.click(enhance, inputs=input_audio, outputs=[output_audio, spec_plot])
+    run_btn.click(enhance, inputs=audio_in, outputs=[audio_out, spec_out])
 
 demo.launch()