drsaikirant88
commited on
Commit
•
19bbbb0
1
Parent(s):
9a9684f
initial commit
Browse files- angry1.png +0 -0
- angry2.jpg +0 -0
- app.py +41 -0
- happy1.jpg +0 -0
- happy2.jpg +0 -0
- neutral1.jpg +0 -0
- neutral2.jpg +0 -0
- requirements.txt +1 -0
angry1.png
ADDED
angry2.jpg
ADDED
app.py
ADDED
@@ -0,0 +1,41 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# Facial expression classifier
|
2 |
+
import os
|
3 |
+
from fastai.vision.all import *
|
4 |
+
import gradio as gr
|
5 |
+
|
6 |
+
# Emotion
|
7 |
+
learn_emotion = load_learner('emotions_vgg19.pkl')
|
8 |
+
learn_emotion_labels = learn_emotion.dls.vocab
|
9 |
+
|
10 |
+
# Sentiment
|
11 |
+
learn_sentiment = load_learner('sentiment_vgg19.pkl')
|
12 |
+
learn_sentiment_labels = learn_sentiment.dls.vocab
|
13 |
+
|
14 |
+
# Predict
|
15 |
+
def predict(img):
|
16 |
+
img = PILImage.create(img)
|
17 |
+
|
18 |
+
pred_emotion, pred_emotion_idx, probs_emotion = learn_emotion.predict(img)
|
19 |
+
|
20 |
+
pred_sentiment, pred_sentiment_idx, probs_sentiment = learn_sentiment.predict(img)
|
21 |
+
|
22 |
+
emotions = {f'emotion_{learn_emotion_labels[i]}': float(probs_emotion[i]) for i in range(len(learn_emotion_labels))}
|
23 |
+
sentiments = {f'sentiment_{learn_sentiment_labels[i]}': float(probs_sentiment[i]) for i in range(len(learn_sentiment_labels))}
|
24 |
+
|
25 |
+
return {**emotions, **sentiments}
|
26 |
+
|
27 |
+
# Gradio
|
28 |
+
title = "Facial Expression Sentiment Classifier"
|
29 |
+
description = "A model to detect emotion and sentiment from facial expressions trained on FER2013 dataset using FastAi. Created as a demo for AI Course."
|
30 |
+
article = 'Sample images are taken from VG & AftenPoften webpages. Copyrights belong to respective brands. All rights reserved.'
|
31 |
+
interpretation='default'
|
32 |
+
enable_queue=True
|
33 |
+
|
34 |
+
examples = ['happy1.jpg', 'happy2.jpg', 'angry1.jpg', 'angry2.jpg', 'neutral1.jpg', 'neutral2.jpg']
|
35 |
+
|
36 |
+
gr.Interface(fn = predict,
|
37 |
+
inputs = gr.Image(shape=(48, 48), image_mode='L'),
|
38 |
+
outputs = gr.Label(),
|
39 |
+
title = title,
|
40 |
+
description = description,
|
41 |
+
article=article).launch(share=True, enable_queue=enable_queue)
|
happy1.jpg
ADDED
happy2.jpg
ADDED
neutral1.jpg
ADDED
neutral2.jpg
ADDED
requirements.txt
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
fastai
|