Spaces:
Sleeping
Sleeping
Update app.py
Browse files
app.py
CHANGED
@@ -6,7 +6,6 @@ DATASET_NAME = "Cnam-LMSSC/vibravox-test"
|
|
6 |
SUBSETS = ["speech_clean", "speech_noisy", "speechless_clean", "speechless_noisy"]
|
7 |
SPLITS = ["train", "validation", "test"]
|
8 |
TEXT_COLUMN = "raw_text"
|
9 |
-
# Add new column names to the configuration
|
10 |
PHONEMIZED_TEXT_COLUMN = "phonemized_text"
|
11 |
GENDER_COLUMN = "gender"
|
12 |
AUDIO_COLUMNS = [
|
@@ -28,23 +27,30 @@ def load_and_update_all(subset, split):
|
|
28 |
dataset = load_dataset(DATASET_NAME, name=subset, split=split)
|
29 |
has_text_fields = TEXT_COLUMN in dataset.features
|
30 |
|
31 |
-
# Get the first row to display immediately
|
32 |
sample = dataset[0]
|
33 |
-
sentence = sample
|
34 |
-
|
35 |
-
|
36 |
-
gender = sample[GENDER_COLUMN] if has_text_fields else None
|
37 |
|
38 |
raw_audio_data = [
|
39 |
(sample[col]['sampling_rate'], sample[col]['array']) for col in AUDIO_COLUMNS
|
40 |
]
|
41 |
|
42 |
-
#
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
43 |
return (
|
44 |
dataset,
|
45 |
-
|
46 |
gr.update(value=sentence, visible=has_text_fields),
|
47 |
-
# Add updates for the new text boxes
|
48 |
gr.update(value=phonemized_text, visible=has_text_fields),
|
49 |
gr.update(value=gender, visible=has_text_fields),
|
50 |
*raw_audio_data,
|
@@ -53,7 +59,6 @@ def load_and_update_all(subset, split):
|
|
53 |
except Exception as e:
|
54 |
error_message = f"Failed to load {subset}/{split}. Error: {e}"
|
55 |
empty_audio = (None, None)
|
56 |
-
# Return empty/hidden updates for all components on error
|
57 |
return (
|
58 |
None,
|
59 |
gr.update(visible=False),
|
@@ -67,16 +72,15 @@ def get_audio_row(dataset, index):
|
|
67 |
Fetches a new row from the currently loaded dataset when the slider moves.
|
68 |
"""
|
69 |
if dataset is None:
|
70 |
-
return [None] * (3 + len(AUDIO_COLUMNS))
|
71 |
|
72 |
index = int(index)
|
73 |
sample = dataset[index]
|
74 |
|
75 |
has_text_fields = TEXT_COLUMN in dataset.features
|
76 |
-
sentence = sample
|
77 |
-
|
78 |
-
|
79 |
-
gender = sample[GENDER_COLUMN] if has_text_fields else None
|
80 |
|
81 |
raw_audio_data = [
|
82 |
(sample[col]['sampling_rate'], sample[col]['array']) for col in AUDIO_COLUMNS
|
@@ -84,26 +88,19 @@ def get_audio_row(dataset, index):
|
|
84 |
|
85 |
return [sentence, phonemized_text, gender] + raw_audio_data
|
86 |
|
|
|
87 |
with gr.Blocks(css="footer {display: none !important}") as demo:
|
88 |
-
# Change the app title
|
89 |
gr.Markdown("# Vibravox Viewer")
|
90 |
-
|
91 |
loaded_dataset_state = gr.State(None)
|
92 |
-
|
93 |
with gr.Row():
|
94 |
subset_dropdown = gr.Dropdown(SUBSETS, value="speech_clean", label="Select Subset")
|
95 |
split_dropdown = gr.Dropdown(SPLITS, value="train", label="Select Split")
|
96 |
-
|
97 |
error_box = gr.Textbox(visible=False, interactive=False, container=False)
|
98 |
-
|
99 |
-
# Group the text outputs together
|
100 |
with gr.Row():
|
101 |
sentence_output = gr.Textbox(label="Raw Text", interactive=False)
|
102 |
phonemized_output = gr.Textbox(label="Phonemized Text", interactive=False)
|
103 |
gender_output = gr.Textbox(label="Gender", interactive=False)
|
104 |
-
|
105 |
slider = gr.Slider(label="Select Data Row")
|
106 |
-
|
107 |
with gr.Row():
|
108 |
audio1 = gr.Audio(label="Headset Microphone")
|
109 |
audio2 = gr.Audio(label="Laryngophone (Throat Mic)")
|
@@ -113,21 +110,12 @@ with gr.Blocks(css="footer {display: none !important}") as demo:
|
|
113 |
audio5 = gr.Audio(label="Forehead Accelerometer")
|
114 |
audio6 = gr.Audio(label="Temple Vibration Pickup")
|
115 |
|
116 |
-
# Update the component lists to include the new text boxes
|
117 |
all_outputs = [loaded_dataset_state, slider, sentence_output, phonemized_output, gender_output, audio1, audio2, audio3, audio4, audio5, audio6, error_box]
|
118 |
data_outputs = [sentence_output, phonemized_output, gender_output, audio1, audio2, audio3, audio4, audio5, audio6]
|
119 |
-
|
120 |
-
# --- WIRING THE EVENT HANDLERS ---
|
121 |
-
# The handlers themselves don't need to change, as we updated the functions and component lists
|
122 |
|
123 |
-
# 1. When the app first loads
|
124 |
demo.load(fn=load_and_update_all, inputs=[subset_dropdown, split_dropdown], outputs=all_outputs)
|
125 |
-
|
126 |
-
# 2. When a dropdown value changes
|
127 |
subset_dropdown.change(fn=load_and_update_all, inputs=[subset_dropdown, split_dropdown], outputs=all_outputs)
|
128 |
split_dropdown.change(fn=load_and_update_all, inputs=[subset_dropdown, split_dropdown], outputs=all_outputs)
|
129 |
-
|
130 |
-
# 3. When ONLY the slider changes
|
131 |
slider.change(fn=get_audio_row, inputs=[loaded_dataset_state, slider], outputs=data_outputs)
|
132 |
|
133 |
demo.launch()
|
|
|
6 |
SUBSETS = ["speech_clean", "speech_noisy", "speechless_clean", "speechless_noisy"]
|
7 |
SPLITS = ["train", "validation", "test"]
|
8 |
TEXT_COLUMN = "raw_text"
|
|
|
9 |
PHONEMIZED_TEXT_COLUMN = "phonemized_text"
|
10 |
GENDER_COLUMN = "gender"
|
11 |
AUDIO_COLUMNS = [
|
|
|
27 |
dataset = load_dataset(DATASET_NAME, name=subset, split=split)
|
28 |
has_text_fields = TEXT_COLUMN in dataset.features
|
29 |
|
|
|
30 |
sample = dataset[0]
|
31 |
+
sentence = sample.get(TEXT_COLUMN)
|
32 |
+
phonemized_text = sample.get(PHONEMIZED_TEXT_COLUMN)
|
33 |
+
gender = sample.get(GENDER_COLUMN)
|
|
|
34 |
|
35 |
raw_audio_data = [
|
36 |
(sample[col]['sampling_rate'], sample[col]['array']) for col in AUDIO_COLUMNS
|
37 |
]
|
38 |
|
39 |
+
# --- THE FIX IS HERE ---
|
40 |
+
# We add a condition to handle datasets with only one row.
|
41 |
+
dataset_len = len(dataset)
|
42 |
+
if dataset_len <= 1:
|
43 |
+
# If there's only one item, hide the slider as it's not needed.
|
44 |
+
slider_update = gr.update(visible=False)
|
45 |
+
else:
|
46 |
+
# Otherwise, show and configure the slider as normal.
|
47 |
+
slider_update = gr.update(maximum=dataset_len - 1, value=0, visible=True, interactive=True)
|
48 |
+
# --------------------
|
49 |
+
|
50 |
return (
|
51 |
dataset,
|
52 |
+
slider_update, # Use the new slider_update variable here
|
53 |
gr.update(value=sentence, visible=has_text_fields),
|
|
|
54 |
gr.update(value=phonemized_text, visible=has_text_fields),
|
55 |
gr.update(value=gender, visible=has_text_fields),
|
56 |
*raw_audio_data,
|
|
|
59 |
except Exception as e:
|
60 |
error_message = f"Failed to load {subset}/{split}. Error: {e}"
|
61 |
empty_audio = (None, None)
|
|
|
62 |
return (
|
63 |
None,
|
64 |
gr.update(visible=False),
|
|
|
72 |
Fetches a new row from the currently loaded dataset when the slider moves.
|
73 |
"""
|
74 |
if dataset is None:
|
75 |
+
return [None] * (3 + len(AUDIO_COLUMNS))
|
76 |
|
77 |
index = int(index)
|
78 |
sample = dataset[index]
|
79 |
|
80 |
has_text_fields = TEXT_COLUMN in dataset.features
|
81 |
+
sentence = sample.get(TEXT_COLUMN)
|
82 |
+
phonemized_text = sample.get(PHONEMIZED_TEXT_COLUMN)
|
83 |
+
gender = sample.get(GENDER_COLUMN)
|
|
|
84 |
|
85 |
raw_audio_data = [
|
86 |
(sample[col]['sampling_rate'], sample[col]['array']) for col in AUDIO_COLUMNS
|
|
|
88 |
|
89 |
return [sentence, phonemized_text, gender] + raw_audio_data
|
90 |
|
91 |
+
# --- Build the Gradio Interface (No changes needed here) ---
|
92 |
with gr.Blocks(css="footer {display: none !important}") as demo:
|
|
|
93 |
gr.Markdown("# Vibravox Viewer")
|
|
|
94 |
loaded_dataset_state = gr.State(None)
|
|
|
95 |
with gr.Row():
|
96 |
subset_dropdown = gr.Dropdown(SUBSETS, value="speech_clean", label="Select Subset")
|
97 |
split_dropdown = gr.Dropdown(SPLITS, value="train", label="Select Split")
|
|
|
98 |
error_box = gr.Textbox(visible=False, interactive=False, container=False)
|
|
|
|
|
99 |
with gr.Row():
|
100 |
sentence_output = gr.Textbox(label="Raw Text", interactive=False)
|
101 |
phonemized_output = gr.Textbox(label="Phonemized Text", interactive=False)
|
102 |
gender_output = gr.Textbox(label="Gender", interactive=False)
|
|
|
103 |
slider = gr.Slider(label="Select Data Row")
|
|
|
104 |
with gr.Row():
|
105 |
audio1 = gr.Audio(label="Headset Microphone")
|
106 |
audio2 = gr.Audio(label="Laryngophone (Throat Mic)")
|
|
|
110 |
audio5 = gr.Audio(label="Forehead Accelerometer")
|
111 |
audio6 = gr.Audio(label="Temple Vibration Pickup")
|
112 |
|
|
|
113 |
all_outputs = [loaded_dataset_state, slider, sentence_output, phonemized_output, gender_output, audio1, audio2, audio3, audio4, audio5, audio6, error_box]
|
114 |
data_outputs = [sentence_output, phonemized_output, gender_output, audio1, audio2, audio3, audio4, audio5, audio6]
|
|
|
|
|
|
|
115 |
|
|
|
116 |
demo.load(fn=load_and_update_all, inputs=[subset_dropdown, split_dropdown], outputs=all_outputs)
|
|
|
|
|
117 |
subset_dropdown.change(fn=load_and_update_all, inputs=[subset_dropdown, split_dropdown], outputs=all_outputs)
|
118 |
split_dropdown.change(fn=load_and_update_all, inputs=[subset_dropdown, split_dropdown], outputs=all_outputs)
|
|
|
|
|
119 |
slider.change(fn=get_audio_row, inputs=[loaded_dataset_state, slider], outputs=data_outputs)
|
120 |
|
121 |
demo.launch()
|