Spaces:
Running
Running
Epsilon617
commited on
Commit
•
e85f544
1
Parent(s):
ebd2b6f
update output format
Browse files- __pycache__/app.cpython-310.pyc +0 -0
- app.py +8 -8
__pycache__/app.cpython-310.pyc
CHANGED
Binary files a/__pycache__/app.cpython-310.pyc and b/__pycache__/app.cpython-310.pyc differ
|
|
app.py
CHANGED
@@ -48,13 +48,13 @@ audio_examples = [
|
|
48 |
# ["input/example-2.wav"],
|
49 |
]
|
50 |
|
51 |
-
df_init = pd.DataFrame(columns=['Task', 'Top 1', 'Top 2', 'Top 3'])
|
52 |
transcription_df = gr.DataFrame(value=df_init, label="Output Dataframe", row_count=(
|
53 |
0, "dynamic"), max_rows=30, wrap=True, overflow_row_behaviour='paginate')
|
54 |
# outputs = [gr.components.Textbox()]
|
55 |
outputs = transcription_df
|
56 |
|
57 |
-
df_init_live = pd.DataFrame(columns=['Task', 'Top 1', 'Top 2', 'Top 3'])
|
58 |
transcription_df_live = gr.DataFrame(value=df_init_live, label="Output Dataframe", row_count=(
|
59 |
0, "dynamic"), max_rows=30, wrap=True, overflow_row_behaviour='paginate')
|
60 |
outputs_live = transcription_df_live
|
@@ -143,7 +143,7 @@ def model_infernce(inputs):
|
|
143 |
all_layer_hidden_states = all_layer_hidden_states.mean(dim=2)
|
144 |
|
145 |
task_output_texts = ""
|
146 |
-
df = pd.DataFrame(columns=['Task', 'Top 1', 'Top 2', 'Top 3'])
|
147 |
df_objects = []
|
148 |
|
149 |
for task in TASKS:
|
@@ -159,9 +159,9 @@ def model_infernce(inputs):
|
|
159 |
# print(sorted_prob)
|
160 |
# print(sorted_prob.shape)
|
161 |
|
162 |
-
top_n_show =
|
163 |
-
task_output_texts = task_output_texts + f"TASK {task} output:\n" + "\n".join([str(ID2CLASS[task][str(sorted_idx[idx].item())])+f', probability: {sorted_prob[idx].item():.2%}' for idx in range(top_n_show)]) + '\n'
|
164 |
-
task_output_texts = task_output_texts + '----------------------\n'
|
165 |
|
166 |
row_elements = [task]
|
167 |
for idx in range(top_n_show):
|
@@ -174,10 +174,10 @@ def model_infernce(inputs):
|
|
174 |
output_prob = f' {sorted_prob[idx].item():.2%}'
|
175 |
row_elements.append(output_class_name+output_prob)
|
176 |
# fill empty elment
|
177 |
-
for _ in range(
|
178 |
row_elements.append(' ')
|
179 |
df_objects.append(row_elements)
|
180 |
-
df = pd.DataFrame(df_objects, columns=['Task', 'Top 1', 'Top 2', 'Top 3'])
|
181 |
return df
|
182 |
|
183 |
def convert_audio(inputs, microphone):
|
|
|
48 |
# ["input/example-2.wav"],
|
49 |
]
|
50 |
|
51 |
+
df_init = pd.DataFrame(columns=['Task', 'Top 1', 'Top 2', 'Top 3', 'Top 4', 'Top 5'])
|
52 |
transcription_df = gr.DataFrame(value=df_init, label="Output Dataframe", row_count=(
|
53 |
0, "dynamic"), max_rows=30, wrap=True, overflow_row_behaviour='paginate')
|
54 |
# outputs = [gr.components.Textbox()]
|
55 |
outputs = transcription_df
|
56 |
|
57 |
+
df_init_live = pd.DataFrame(columns=['Task', 'Top 1', 'Top 2', 'Top 3', 'Top 4', 'Top 5'])
|
58 |
transcription_df_live = gr.DataFrame(value=df_init_live, label="Output Dataframe", row_count=(
|
59 |
0, "dynamic"), max_rows=30, wrap=True, overflow_row_behaviour='paginate')
|
60 |
outputs_live = transcription_df_live
|
|
|
143 |
all_layer_hidden_states = all_layer_hidden_states.mean(dim=2)
|
144 |
|
145 |
task_output_texts = ""
|
146 |
+
df = pd.DataFrame(columns=['Task', 'Top 1', 'Top 2', 'Top 3', 'Top 4', 'Top 5'])
|
147 |
df_objects = []
|
148 |
|
149 |
for task in TASKS:
|
|
|
159 |
# print(sorted_prob)
|
160 |
# print(sorted_prob.shape)
|
161 |
|
162 |
+
top_n_show = 5 if num_class >= 5 else num_class
|
163 |
+
# task_output_texts = task_output_texts + f"TASK {task} output:\n" + "\n".join([str(ID2CLASS[task][str(sorted_idx[idx].item())])+f', probability: {sorted_prob[idx].item():.2%}' for idx in range(top_n_show)]) + '\n'
|
164 |
+
# task_output_texts = task_output_texts + '----------------------\n'
|
165 |
|
166 |
row_elements = [task]
|
167 |
for idx in range(top_n_show):
|
|
|
174 |
output_prob = f' {sorted_prob[idx].item():.2%}'
|
175 |
row_elements.append(output_class_name+output_prob)
|
176 |
# fill empty elment
|
177 |
+
for _ in range(5+1 - len(row_elements)):
|
178 |
row_elements.append(' ')
|
179 |
df_objects.append(row_elements)
|
180 |
+
df = pd.DataFrame(df_objects, columns=['Task', 'Top 1', 'Top 2', 'Top 3', 'Top 4', 'Top 5'])
|
181 |
return df
|
182 |
|
183 |
def convert_audio(inputs, microphone):
|