new

app.py

@@ -16,7 +16,7 @@ from concurrent.futures import ThreadPoolExecutor, TimeoutError as FutureTimeout
 # Load dataset from HuggingFace
 dataset = load_dataset("intersteller2887/Turing-test-dataset-en", split="train")
 dataset = dataset.cast_column("audio", Audio(decode=False)) # Prevent calling 'torchcodec' from newer version of 'datasets'
-
+sample1_audio = dataset[0]["audio"]
 # Huggingface space working directory: "/home/user/app"
 target_audio_dir = "/home/user/app/audio"
 os.makedirs(target_audio_dir, exist_ok=True)
@@ -38,8 +38,8 @@ for item in dataset:
 all_data_audio_paths = local_audio_paths
 
 # Take first file of the datasets as sample
-sample1_audio_path = local_audio_paths[0]
-print(sample1_audio_path)
+# sample1_audio_path = local_audio_paths[0]
+# print(sample1_audio_path)
 
 # ==============================================================================
 # Data Definition
@@ -883,7 +883,8 @@ with gr.Blocks(theme=gr.themes.Soft(), css=".gradio-container {max-width: 960px
         sample_dimension_selector = gr.Radio(DIMENSION_TITLES, label="Select Learning Dimension", value=DIMENSION_TITLES[0])
         with gr.Row():
             with gr.Column(scale=1):
-                sample_audio = gr.Audio(label="Sample Audio", value=DIMENSIONS_DATA[0]["audio"])
+                # sample_audio = gr.Audio(label="Sample Audio", value=DIMENSIONS_DATA[0]["audio"])
+                sample_audio = gr.Audio(label="Sample Audio", value=sample1_audio)
             with gr.Column(scale=2):
                 with gr.Column(visible=True) as interactive_view:
                     gr.Markdown("#### Please rate the following features (0-5 points. 0 - Feature not present; 1 - Machine; 3 - Neutral; 5 - Human)")