Delete app.py

app.py

@@ -1,155 +0,0 @@
-import gradio as gr
-from logic import Speaker_speech_analysis
-from scipy.io import wavfile
-
-
-
-def create_html_from_scores(word_scores):
-    html_output = ''
-    for word, score in word_scores:
-        if score == 1:
-            html_output += f'<span style="color: #dc3545;">{word}</span> '
-        elif score == 2:
-            html_output += f'<span style="color: #ffc107;">{word}</span> '
-        else:
-            html_output += f'<span style="color: #28a745;">{word}</span> '
-    return html_output
-  
-def generate_progress_bar(score, label):
-    score = round(score, 2)
-    score_text = f"{score:.2f}" if score < 90 else "90"
-    if score < 25:
-        bar_color = "#dc3545" 
-    elif score < 50:
-        bar_color = "#dc6545" 
-    elif score < 75:
-        bar_color = "#ffc107"
-    else:
-        bar_color = "#28a745"
-    bar_length = f"{(score / 90) * 100}%"
-    return f"""
-    <div class="progress-label">{label}:</div>
-    <div class="progress-container">
-        <div class="progress-bar" style="width: {bar_length}; background-color: {bar_color};">
-            <div class="progress-score">{score_text}</div>
-        </div>
-    </div>
-    <div class="progress-max">Max: 90</div>
-    """
-# CSS to be used in the Gradio Interface
-
-
-
-
-def analyze_audio(text, audio):
-# Write the processed audio to a temporary WAV file
-    temp_filename = 'temp_audio.wav'
-    wavfile.write(temp_filename, audio[0], audio[1])
-
-
-    result = Speaker_speech_analysis(temp_filename, text)
-    accuracy_score = result['pronunciation_accuracy']
-    fluency_score  = result['fluency_score']
-    word_scores    = result['word_scores']
-    
-    html_content = create_html_from_scores(word_scores)
-    pronunciation_progress_bar = generate_progress_bar(accuracy_score, "Pronunciation Accuracy")
-    fluency_progress_bar = generate_progress_bar(fluency_score, "Fluency Score")
-    
-    
-    html_with_css = f"""
-    <style>
-    .legend {{
-      font-size: 22px;
-      display: flex;
-      align-items: center;
-      gap: 12px;
-    }}
-    
-    .legend-dot {{
-        height: 15px;
-        width: 15px;
-        border-radius: 50%;
-        display: inline-block;
-      }}
-      
-    .good {{ color: #28a745; 
-    }}
-    .average {{ color: #ffc107; 
-    }}
-    .bad {{ color: #dc3545;
-    }}
-        
-    .text {{
-        font-size: 20px;
-        margin-bottom: 20px;
-      }}
-
-    .progress-container {{
-        width: 100%;
-        background-color: #ddd;
-        border-radius: 13px;
-        overflow: hidden;
-      }}
-
-    .progress-bar {{
-        height: 30px;
-        line-height: 30px;
-        text-align: center;
-        font-size: 16px;
-        border-radius: 15px;
-        transition: width 1s ease;
-      }}
-
-    .progress-label {{
-        font-weight: bold;
-        font-size: 22px;
-        margin-bottom: 20px;
-        margin-top: 5px;
-        text-align: center;
-      }}
-
-    .progress-score {{
-        display: inline-block;
-        color: black;
-      }}
-
-    .progress-max {{
-        text-align: right;
-        margin: 10px;
-        font-size: 16px;
-      }}
-        
-    </style>
-    
-    
-    <div class="legend">
-      <span class="legend-dot" style="background-color: #28a745;"></span><span>Good</span>
-      <span class="legend-dot" style="background-color: #ffc107;"></span><span>Understandable</span>
-      <span class="legend-dot" style="background-color: #dc3545;"></span><span>Bad</span>
-    </div>
-    
-    <p class="text">
-      {html_content}
-    </p>
-
-    {pronunciation_progress_bar}
-    {fluency_progress_bar}
-    """
-    return html_with_css
-
-# Define the Gradio interface
-iface = gr.Interface(fn=analyze_audio,
-                     inputs=[gr.Textbox(label='Training Text', placeholder='Write the text for pronunciation task', interactive=True, visible=True, show_copy_button=True,), 
-                             gr.Audio(label="Recoreded Audio", sources=['microphone', 'upload'])
-                             ],
-                     outputs=[gr.HTML(label="Analysis of pronunciation"),
-                              ],
-                    #  css=additional_css,
-                     # title="Audio Analysis Tool",
-                     description="Write any text and recored an audio to predict pronunciation erors"
-                     )
-
-# Run the Gradio app
-if __name__ == "__main__":
-    iface.launch()