Update app.py

app.py

@@ -7,40 +7,39 @@ API_URL = "https://api-inference.huggingface.co/models/MIT/ast-finetuned-audiose
 HF_TOKEN = os.getenv("HF_TOKEN")
 headers = {"Authorization": f"Bearer {HF_TOKEN}"} 
 
-# Function to send audio file to the Hugging Face model for classification
-def query(filename):
-    with open(filename, "rb") as f:
-        data = f.read()
-    response = requests.post(API_URL, headers=headers, files={"file": f})
+# Function to send the audio file to the Hugging Face API and get the classification result
+def classify_audio(audio_file_path):
+    with open(audio_file_path, "rb") as audio_file:
+        response = requests.post(
+            "https://api-inference.huggingface.co/models/MIT/ast-finetuned-audioset-10-10-0.4593",
+            headers=headers,
+            files={"file": audio_file}
+        )
     return response.json()
 
-# Pre-uploaded audio files (assuming these files are stored in a directory named 'audio_files')
-audio_files = {
-    "Labrador Barking": "labrador-barking.mp3",
-    "Tolling Bell": "tolling-bell.mp3",
-    "Airplane Landing": "airplane-landing.mp3",
-    "Old Car Engine": "old-car-engine.mp3",
-    "Hard Shoes": "hard_shoes.mp3",
-    "Alien Spaceship": "alien-spaceship.mp3",
-}
+# Streamlit interface
+st.title("Audio Classifier")
 
-# Streamlit UI
-st.title("Audio Classification with Hugging Face Inference API")
+# Define the folder where your audio files are located
+audio_folder = "audio_files"
 
-# Audio file selection
-selected_audio_name = st.selectbox("Select an audio file", list(audio_files.keys()))
-audio_file_path = os.path.join("path_to_your_audio_files", audio_files[selected_audio_name])  # Update path as necessary
+# List the audio files in the folder
+audio_files = os.listdir(audio_folder)
+audio_file_options = [f for f in audio_files if f.endswith(('.mp3', '.wav'))]
 
-# Perform classification
-if st.button("Classify"):
-    results = query(audio_file_path)
+# Dropdown to select an audio file
+selected_file = st.selectbox("Select an audio file:", audio_file_options)
 
-    # Displaying results
-    st.write("Classification Results:")
-    if isinstance(results, list):  # Check if the response is as expected
-        for result in results:
-            label = result['label']
-            score = round(result['score'], 4)  # Adjust rounding as needed
-            st.write(f"Label: {label}, Score: {score}")
-    else:
-        st.write("An error occurred:", results)
+# Button to classify the selected audio file
+if st.button("Classify"):
+    # Get the full path of the selected audio file
+    audio_file_path = os.path.join(audio_folder, selected_file)
+    
+    # Show the audio player
+    st.audio(audio_file_path)
+    
+    # Get and display the classification results
+    results = classify_audio(audio_file_path)
+    st.write("Results:")
+    for result in results:
+        st.write(f"Label: {result['label']}, Confidence: {result['score']:.2f}")