Spaces:
Sleeping
Sleeping
| import gradio as gr | |
| import pandas as pd | |
| import os | |
| import gradio as gr | |
| from pyannote.core import Annotation, Segment | |
| from pyannote.audio import Pipeline | |
| # 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): | |
| """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.mp4' | |
| with (gr.Blocks() as demo): | |
| with gr.Row(): | |
| audio_player = gr.Audio(value=audio_path, label="Audio", type="filepath", interactive=False) | |
| with gr.Row(): | |
| with gr.Accordion(label="Click to see the sentence", open=False): | |
| sentence_text = gr.Textbox(label="Sentence", interactive=False) | |
| with gr.Row(): | |
| slider = gr.Slider( | |
| minimum=-100, | |
| maximum=100, | |
| step=1, | |
| label="Sentiment Slider", | |
| info="Slide to the left for negative sentiment, to the right for positive sentiment", | |
| show_label=True, | |
| elem_classes=["sentiment-slider"] | |
| ) | |
| 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() | |
| gr.Button() | |
| with gr.Row(): | |
| save_button = gr.Button("Save Annotation") | |
| 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"] | |
| ) | |
| save_button.click( | |
| save_annotation, | |
| inputs=[emotions, comments] | |
| ) | |
| 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() | |