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app.py

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+# Facial expression classifier
+import os
+from fastai.vision.all import *
+import gradio as gr
+
+# Emotion
+learn_emotion = load_learner('emotions_vgg19.pkl')
+learn_emotion_labels = learn_emotion.dls.vocab
+
+# Sentiment
+learn_sentiment = load_learner('sentiment_vgg19.pkl')
+learn_sentiment_labels = learn_sentiment.dls.vocab
+
+# Predict
+def predict(img):
+    img = PILImage.create(img)
+    
+    pred_emotion, pred_emotion_idx, probs_emotion = learn_emotion.predict(img)
+    
+    pred_sentiment, pred_sentiment_idx, probs_sentiment = learn_sentiment.predict(img)
+    
+    #emotions = {f'emotion_{learn_emotion_labels[i]}': float(probs_emotion[i]) for i in range(len(learn_emotion_labels))}
+    #sentiments = {f'sentiment_{learn_sentiment_labels[i]}': float(probs_sentiment[i]) for i in range(len(learn_sentiment_labels))}
+    
+    emotions = {learn_emotion_labels[i]: float(probs_emotion[i]) for i in range(len(learn_emotion_labels))}
+    sentiments = {learn_sentiment_labels[i]: float(probs_sentiment[i]) for i in range(len(learn_sentiment_labels))}
+        
+    return [emotions, sentiments] #{**emotions, **sentiments}
+
+# Gradio
+title = "Facial Emotion and Sentiment Detector"
+
+enable_queue=True
+
+examples = ['happy1.jpg', 'happy2.jpg', 'angry1.png', 'angry2.jpg', 'neutral1.jpg', 'neutral2.jpg']
+
+gr.Interface(fn = predict, 
+             inputs = gr.Image(shape=(48, 48), image_mode='L'), 
+             outputs = [gr.Label(label='Emotion'), gr.Label(label='Sentiment')], #gr.Label(),
+             title = title,
+             examples = examples,
+             description = description,
+             article=article,
+             allow_flagging='never').launch(enable_queue=enable_queue)

emotions_vgg19.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:335570ccf5133bc1fc0d4cc9bb7835b72fd457a64c0cdefbbc863f1c24cc4454
+size 82965753

requirements.txt

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+fastai

sentiment_vgg19.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:e6fc0f18d5a082cd835b6b8cbd32041170be0ac20b7ca555df1209e2e4d181c3
+size 82957497