|
import os |
|
from fastai.vision.all import * |
|
import gradio as gr |
|
|
|
|
|
learn_emotion = load_learner('emotions_jey.pkl') |
|
learn_emotion_labels = learn_emotion.dls.vocab |
|
|
|
learn_sentiment = load_learner('sentiment_jey.pkl') |
|
learn_sentiment_labels = learn_sentiment.dls.vocab |
|
|
|
|
|
label_mapping = { |
|
'angry': 'enojado', |
|
'disgust': 'asco', |
|
'fear': 'miedo', |
|
'happy': 'feliz', |
|
'sad': 'triste', |
|
'surprise': 'sorpresa', |
|
'neutral': 'neutral', |
|
'negative': 'negativo', |
|
'positive': 'positivo' |
|
} |
|
|
|
|
|
def predict(img_path): |
|
img = PILImage.create(img_path) |
|
|
|
pred_emotion, pred_emotion_idx, probs_emotion = learn_emotion.predict(img) |
|
pred_sentiment, pred_sentiment_idx, probs_sentiment = learn_sentiment.predict(img) |
|
|
|
emotions = {label_mapping[label]: float(prob) for label, prob in zip(learn_emotion_labels, probs_emotion)} |
|
sentiments = {label_mapping[label]: float(prob) for label, prob in zip(learn_sentiment_labels, probs_sentiment)} |
|
|
|
return emotions, sentiments |
|
|
|
|
|
title = "Detector de emociones y sentimientos faciales" |
|
description = ( |
|
"Esta interfaz utiliza redes neuronales para detectar emociones y sentimientos a partir de im谩genes faciales." |
|
) |
|
article = "Esta herramienta proporciona una forma r谩pida de analizar emociones y sentimientos en im谩genes." |
|
|
|
examples = [ |
|
'PrivateTest_10131363.jpg', |
|
'angry1.png', |
|
'angry2.jpg', |
|
'happy1.jpg', |
|
'happy2.jpg', |
|
'neutral1.jpg', |
|
'neutral2.jpg' |
|
] |
|
|
|
iface = gr.Interface( |
|
fn=predict, |
|
inputs=gr.Image(shape=(48, 48), image_mode='L'), |
|
outputs=[gr.Label(label='Emoci贸n'), gr.Label(label='Sentimiento')], |
|
title=title, |
|
examples=examples, |
|
description=description, |
|
article=article, |
|
allow_flagging='never' |
|
) |
|
|
|
iface.launch(enable_queue=True) |
|
|
|
|
|
|
