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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 | |
| # Predict | |
| def predict(img): | |
| img = PILImage.create(img) | |
| pred_emotion, pred_emotion_idx, probs_emotion = learn_emotion.predict(img) | |
| predicted_emotion = learn_emotion_labels[pred_emotion_idx] | |
| return predicted_emotion | |
| # Gradio | |
| title = "Facial Emotion Detector" | |
| description = gr.Markdown( | |
| """Ever wondered what a person might be feeling looking at their picture? | |
| Well, now you can! Try this fun app. Just upload a facial image in JPG or | |
| PNG format. You can now see what they might have felt when the picture | |
| was taken. | |
| **Tip**: Be sure to only include face to get best results. Check some sample images | |
| below for inspiration!""").value | |
| article = gr.Markdown( | |
| """**DISCLAIMER:** This model does not reveal the actual emotional state of a person. Use and | |
| interpret results at your own risk!. | |
| **PREMISE:** The idea is to determine an overall emotion of a person | |
| based on the pictures. We are restricting pictures to only include close-up facial | |
| images. | |
| **DATA:** FER2013 dataset consists of 48x48 pixel grayscale images of faces.Images | |
| are assigned one of the 7 emotions: Angry, Disgust, Fear, Happy, Sad, Surprise, and Neutral. | |
| """).value | |
| enable_queue=True | |
| examples = ['happy1.jpg', 'happy2.jpg', 'angry1.png', 'angry2.jpg', 'neutral1.jpg', 'neutral2.jpg'] | |
| gr.Interface(fn = predict, | |
| inputs = gr.Image( image_mode='L'), | |
| outputs = [gr.Label(label='Emotion')], #gr.Label(), | |
| title = title, | |
| examples = examples, | |
| description = description, | |
| article=article, | |
| allow_flagging='never').launch() | |