Update app.py

app.py

@@ -170,6 +170,34 @@ def main():
                                     file_name="output.mp3",
                                     mime="audio/mpeg",
                                 )
+            if detect_watermark_button:
+                with st.spinner("Detecting..."):
+                    # result, message = detector.detect_watermark(watermarked_audio, sample_rate=default_sr, message_threshold=0.5)
+                    # st.markdown("Probability of audio being watermarked: ")
+                    # st.markdown(result)
+                    # st.markdown("This is likely a watermarked audio!")
+                    # print(f"\nThis is likely a watermarked audio: {result}")
+
+                    #Run on an unwatermarked audio
+
+                    if file_extension in [".wav", ".flac"]: 
+                        wav, sample_rate = torchaudio.load("test.wav")
+                        wav= wav.unsqueeze(0)
+
+                    elif file_extension == ".mp3":
+                        # Load an MP3 file
+                        audio = AudioSegment.from_mp3("test.mp3")
+                        # Export it as a WAV file
+                        audio.export("test.wav", format="wav")
+                        wav, sample_rate = torchaudio.load("test.wav")
+                        wav= wav.unsqueeze(0)
+                        
+                    result2, message2 = detector.detect_watermark(wav, sample_rate=default_sr, message_threshold=0.5)
+                    print(f"This is likely an unwatermarked audio: {result2}")
+                    st.markdown("Probability of audio being watermarked: ")
+                    st.markdown(result2)
+                    st.markdown("This is likely an unwatermarked audio!")
+
     except RuntimeError:
         st.error("Please input audio with one channel (mono-channel)")
         
@@ -318,33 +346,33 @@ def main():
     #         #     #st.markdown(size)
 
                 
-    #         if detect_watermark_button:
-    #             with st.spinner("Detecting..."):
-    #                 # result, message = detector.detect_watermark(watermarked_audio, sample_rate=default_sr, message_threshold=0.5)
-    #                 # st.markdown("Probability of audio being watermarked: ")
-    #                 # st.markdown(result)
-    #                 # st.markdown("This is likely a watermarked audio!")
-    #                 # print(f"\nThis is likely a watermarked audio: {result}")
-
-    #                 #Run on an unwatermarked audio
-
-    #                 if file_extension in [".wav", ".flac"]: 
-    #                     wav, sample_rate = torchaudio.load("test.wav")
-    #                     wav= wav.unsqueeze(0)
-
-    #                 elif file_extension == ".mp3":
-    #                     # Load an MP3 file
-    #                     audio = AudioSegment.from_mp3("test.mp3")
-    #                     # Export it as a WAV file
-    #                     audio.export("test.wav", format="wav")
-    #                     wav, sample_rate = torchaudio.load("test.wav")
-    #                     wav= wav.unsqueeze(0)
+            if detect_watermark_button:
+                with st.spinner("Detecting..."):
+                    # result, message = detector.detect_watermark(watermarked_audio, sample_rate=default_sr, message_threshold=0.5)
+                    # st.markdown("Probability of audio being watermarked: ")
+                    # st.markdown(result)
+                    # st.markdown("This is likely a watermarked audio!")
+                    # print(f"\nThis is likely a watermarked audio: {result}")
+
+                    #Run on an unwatermarked audio
+
+                    if file_extension in [".wav", ".flac"]: 
+                        wav, sample_rate = torchaudio.load("test.wav")
+                        wav= wav.unsqueeze(0)
+
+                    elif file_extension == ".mp3":
+                        # Load an MP3 file
+                        audio = AudioSegment.from_mp3("test.mp3")
+                        # Export it as a WAV file
+                        audio.export("test.wav", format="wav")
+                        wav, sample_rate = torchaudio.load("test.wav")
+                        wav= wav.unsqueeze(0)
                         
-    #                 result2, message2 = detector.detect_watermark(wav, sample_rate=default_sr, message_threshold=0.5)
-    #                 print(f"This is likely an unwatermarked audio: {result2}")
-    #                 st.markdown("Probability of audio being watermarked: ")
-    #                 st.markdown(result2)
-    #                 st.markdown("This is likely an unwatermarked audio!")
+                    result2, message2 = detector.detect_watermark(wav, sample_rate=default_sr, message_threshold=0.5)
+                    print(f"This is likely an unwatermarked audio: {result2}")
+                    st.markdown("Probability of audio being watermarked: ")
+                    st.markdown(result2)
+                    st.markdown("This is likely an unwatermarked audio!")
 
 
 if __name__ == "__main__":