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import gradio as gr
import pandas as pd
import os
import gradio as gr
# List of all audio files to annotate
file_list = pd.read_excel(os.path.join('combined_annotations.xlsx'))
# Initialize an empty DataFrame to store annotations
annotations = pd.DataFrame(columns=['sample_id', 'sentence', 'emotion', 'comments'])
current_index = {"index": 0} # Dictionary to allow modifying inside functions
def load_example(index):
"""Load the example (audio + text) by index."""
row = file_list.iloc[index]
audio_path = os.path.join('files_to_annotate_padded_smaller_emotion_set', row["SAMPLE ID"].split('-')[0], row["SAMPLE ID"] + '.wav')
print(f"Audio path: {audio_path}, Exists: {os.path.exists(audio_path)}")
sentence = row["SENTENCE"]
# If the user already made an annotation for this example, gradio will return said annotation
previous_annotation = (
annotations.iloc[index].to_dict() if index < len(annotations) else {"sample_id": row["SAMPLE ID"], "emotion": '',
"comments": ''}
)
return (sentence, audio_path, previous_annotation['emotion'], previous_annotation["comments"])
def save_annotation(emotions, comments):
"""Save the annotation for the current example."""
idx = current_index["index"]
row = file_list.iloc[idx]
sample_id = row["SAMPLE ID"]
sentence = row["SENTENCE"]
# Update or append annotation
if sample_id in annotations["sample_id"].values:
annotations.loc[annotations["sample_id"] == sample_id, ["emotion", "comments"]] = \
[emotions, comments]
else:
annotations.loc[len(annotations)] = [sample_id, sentence, emotions, comments]
annotations.to_csv("annotations.csv", index=False) # Save to a CSV file
#return f"Saved annotations for example {idx + 1}"
def next_example(emotions, comments):
if emotions == '':
raise gr.Error("Please fill out the emotion section")
else:
"""Move to the next example."""
save_annotation(emotions, comments)
if current_index["index"] < len(file_list) - 1:
current_index["index"] += 1
return load_example(current_index["index"])
#return "End of examples", None, 0, 0, 0, 0, ''
def previous_example(emotion, comments):
"""Move to the previous example."""
save_annotation(emotion, comments)
if current_index["index"] > 0:
current_index["index"] -= 1
return load_example(current_index["index"])
return load_example(current_index["index"])
# Gradio Interface
audio_path = 'test.mp3'
with (gr.Blocks() as demo):
# Row with audio player
with gr.Row():
audio_player = gr.Audio(value=audio_path, label="Audio", type="filepath", interactive=False)
# Hidden row with corresponding sentence
with gr.Row():
with gr.Accordion(label="Click to see the sentence", open=False):
sentence_text = gr.Textbox(label="Sentence", interactive=False)
# Row for emotion annotation and confidence
with gr.Row():
emotions = gr.Radio(["Joy", "Sad", "Angry", "Neutral"], label="Predominant Emotion")
confidence = gr.Slider(label="Confidence (%)", minimum=0, maximum=100, step=10)
# Instructions for emotion annotation
with gr.Sidebar():
gr.Textbox()
# Next and Previous Buttons
with gr.Row():
next_button = gr.Button("Next Example")
previous_button = gr.Button("Previous Example")
comments = gr.Textbox(label="Comments", interactive=True)
# Initial load
sentence_text.value, audio_player.value, emotions.value, comments.value = load_example(
current_index["index"]
)
next_button.click(
next_example,
inputs=[emotions, comments],
outputs=[sentence_text, audio_player, emotions, comments],
)
previous_button.click(
previous_example,
inputs=[emotions, comments],
outputs=[sentence_text, audio_player, emotions, comments],
)
demo.launch()
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