Fix model loading on CPU

app.py

@@ -1,4 +1,4 @@
-# app.py (More Stable Version)
+
 
 import gradio as gr
 import torch
@@ -7,10 +7,9 @@ import torchaudio
 import os
 import time
 
-# --- Ensure model.py with your class definitions is in the same folder ---
 from model import FullModel
 
-# --- 1. Global Setup ---
+
 if not os.path.exists("user_data"): os.makedirs("user_data")
 if not os.path.exists("user_data/enrollments"): os.makedirs("user_data/enrollments")
 if not os.path.exists("user_data/verifications"): os.makedirs("user_data/verifications")
@@ -18,13 +17,12 @@ if not os.path.exists("user_data/verifications"): os.makedirs("user_data/verific
 print("Loading model...")
 DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 MODEL = FullModel().to(DEVICE)
-MODEL.load_state_dict(torch.load("speaker_verification_model.pth"))
+MODEL.load_state_dict(torch.load("speaker_verification_model.pth", map_location=torch.device('cpu')))
 MODEL.eval()
 THRESHOLD = 0.5216
 print("Model loaded successfully.")
 ENROLLED_USERS = {}
 
-# --- 2. Helper and Core Functions ---
 
 def get_embedding(waveform):
     if waveform.shape[0] > 1: waveform = torch.mean(waveform, dim=0, keepdim=True)
@@ -37,11 +35,9 @@ def enroll_speaker(audio_filepath, username):
         return "Error: No audio recorded. Please record your voice first.", gr.update()
     if not username:
         return "Please enter a username.", None
-    
-    # Load the audio from the temporary file path provided by Gradio
+
     waveform, sr = torchaudio.load(audio_filepath)
-    
-    # Save a permanent copy of the enrollment audio
+
     timestamp = int(time.time())
     filename = f"user_data/enrollments/{username}_{timestamp}.wav"
     torchaudio.save(filename, waveform, sr)
@@ -60,10 +56,9 @@ def verify_speaker(audio_filepath, username_to_verify):
     if username_to_verify not in ENROLLED_USERS:
         return f"User '{username_to_verify}' is not enrolled. Please enroll first.", None
 
-    # Load the audio from the temporary file path provided by Gradio
     waveform, sr = torchaudio.load(audio_filepath)
 
-    # Save a permanent copy of the verification attempt
+
     timestamp = int(time.time())
     filename = f"user_data/verifications/{username_to_verify}_attempt_{timestamp}.wav"
     torchaudio.save(filename, waveform, sr)
@@ -77,7 +72,7 @@ def verify_speaker(audio_filepath, username_to_verify):
     
     return f"Similarity Score: {score:.4f}", decision
 
-# --- 3. Gradio Interface ---
+
 
 with gr.Blocks() as demo:
     gr.Markdown("# Voice Authentication System")
@@ -85,13 +80,11 @@ with gr.Blocks() as demo:
     with gr.Tabs():
         with gr.TabItem("Enrollment"):
             enroll_username = gr.Textbox(label="Enter a unique Username")
-            # <<< --- FIX: Changed type="numpy" to type="filepath" --- >>>
             enroll_audio = gr.Audio(sources=["microphone"], type="filepath", label="Record your enrollment phrase (3-5 seconds)")
             enroll_button = gr.Button("Enroll Voiceprint")
             enroll_output = gr.Textbox(label="Enrollment Status")
         with gr.TabItem("Verification"):
             verify_username = gr.Textbox(label="Enter your Username to verify")
-            # <<< --- FIX: Changed type="numpy" to type="filepath" --- >>>
             verify_audio = gr.Audio(sources=["microphone"], type="filepath", label="Record your verification phrase (must be different!)")
             verify_button = gr.Button("Verify My Voice")
             verify_score = gr.Textbox(label="Result Score")
@@ -100,6 +93,5 @@ with gr.Blocks() as demo:
     enroll_button.click(fn=enroll_speaker, inputs=[enroll_audio, enroll_username], outputs=[enroll_output, verify_username])
     verify_button.click(fn=verify_speaker, inputs=[verify_audio, verify_username], outputs=[verify_score, verify_decision])
 
-# --- 4. Launch the App ---
 if __name__ == "__main__":
     demo.queue().launch(share=True)