Spaces:
Runtime error
Runtime error
Updated app.py for latest Gradio version 4.0
#2
by
abhicodes
- opened
app.py
CHANGED
|
@@ -84,18 +84,13 @@ description = """
|
|
| 84 |
<br>
|
| 85 |
🎯 The sentiment analysis results are provided as a dictionary with different emotions and their corresponding scores.<br>
|
| 86 |
<br>
|
| 87 |
-
|
| 88 |
😃 The sentiment analysis results are displayed with emojis representing the corresponding sentiment.<br>
|
| 89 |
<br>
|
| 90 |
-
|
| 91 |
✅ The higher the score for a specific emotion, the stronger the presence of that emotion in the transcribed text.<br>
|
| 92 |
<br>
|
| 93 |
-
|
| 94 |
❓ Use the microphone for real-time speech recognition.<br>
|
| 95 |
<br>
|
| 96 |
-
|
| 97 |
⚡️ The model will transcribe the audio and perform sentiment analysis on the transcribed text.<br>
|
| 98 |
-
|
| 99 |
"""
|
| 100 |
|
| 101 |
custom_css = """
|
|
@@ -122,18 +117,16 @@ with block:
|
|
| 122 |
gr.HTML(description)
|
| 123 |
|
| 124 |
with gr.Group():
|
| 125 |
-
with gr.
|
| 126 |
audio = gr.Audio(
|
| 127 |
label="Input Audio",
|
| 128 |
show_label=False,
|
| 129 |
-
source="microphone",
|
| 130 |
type="filepath"
|
| 131 |
)
|
| 132 |
|
| 133 |
sentiment_option = gr.Radio(
|
| 134 |
choices=["Sentiment Only", "Sentiment + Score"],
|
| 135 |
label="Select an option",
|
| 136 |
-
default="Sentiment Only"
|
| 137 |
)
|
| 138 |
|
| 139 |
btn = gr.Button("Transcribe")
|
|
@@ -142,7 +135,7 @@ with block:
|
|
| 142 |
|
| 143 |
text = gr.Textbox(label="Transcription")
|
| 144 |
|
| 145 |
-
sentiment_output = gr.Textbox(label="Sentiment Analysis Results"
|
| 146 |
|
| 147 |
btn.click(inference, inputs=[audio, sentiment_option], outputs=[lang_str, text, sentiment_output])
|
| 148 |
|
|
@@ -153,4 +146,4 @@ with block:
|
|
| 153 |
</div>
|
| 154 |
''')
|
| 155 |
|
| 156 |
-
block.launch()
|
|
|
|
| 84 |
<br>
|
| 85 |
🎯 The sentiment analysis results are provided as a dictionary with different emotions and their corresponding scores.<br>
|
| 86 |
<br>
|
|
|
|
| 87 |
😃 The sentiment analysis results are displayed with emojis representing the corresponding sentiment.<br>
|
| 88 |
<br>
|
|
|
|
| 89 |
✅ The higher the score for a specific emotion, the stronger the presence of that emotion in the transcribed text.<br>
|
| 90 |
<br>
|
|
|
|
| 91 |
❓ Use the microphone for real-time speech recognition.<br>
|
| 92 |
<br>
|
|
|
|
| 93 |
⚡️ The model will transcribe the audio and perform sentiment analysis on the transcribed text.<br>
|
|
|
|
| 94 |
"""
|
| 95 |
|
| 96 |
custom_css = """
|
|
|
|
| 117 |
gr.HTML(description)
|
| 118 |
|
| 119 |
with gr.Group():
|
| 120 |
+
with gr.Column():
|
| 121 |
audio = gr.Audio(
|
| 122 |
label="Input Audio",
|
| 123 |
show_label=False,
|
|
|
|
| 124 |
type="filepath"
|
| 125 |
)
|
| 126 |
|
| 127 |
sentiment_option = gr.Radio(
|
| 128 |
choices=["Sentiment Only", "Sentiment + Score"],
|
| 129 |
label="Select an option",
|
|
|
|
| 130 |
)
|
| 131 |
|
| 132 |
btn = gr.Button("Transcribe")
|
|
|
|
| 135 |
|
| 136 |
text = gr.Textbox(label="Transcription")
|
| 137 |
|
| 138 |
+
sentiment_output = gr.Textbox(label="Sentiment Analysis Results")
|
| 139 |
|
| 140 |
btn.click(inference, inputs=[audio, sentiment_option], outputs=[lang_str, text, sentiment_output])
|
| 141 |
|
|
|
|
| 146 |
</div>
|
| 147 |
''')
|
| 148 |
|
| 149 |
+
block.launch()
|