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| import gradio as gr | |
| import os | |
| import cv2 | |
| import numpy as np | |
| import imutils | |
| from keras.preprocessing.image import img_to_array | |
| from keras.models import load_model | |
| # Load the pre-trained models and define parameters | |
| detection_model_path = 'haarcascade_files/haarcascade_frontalface_default.xml' | |
| emotion_model_path = 'model4_0.83/model4_entire_model.h5' | |
| face_detection = cv2.CascadeClassifier(detection_model_path) | |
| emotion_classifier = load_model(emotion_model_path, compile=False) | |
| EMOTIONS = ['neutral', 'happiness', 'surprise', 'sadness', 'anger', 'disgust', 'fear', 'contempt', 'unknown'] | |
| # face_detector_mtcnn = MTCNN() | |
| classifier = load_model(emotion_model_path) | |
| def predict_emotion(image): | |
| faces = face_detection(image) | |
| for face in faces: | |
| x,y,w,h = face['box'] | |
| roi = image[y:y+h,x:x+w] | |
| # Converting the region of interest to grayscale, and resize | |
| roi_gray = cv2.cvtColor(roi, cv2.COLOR_BGR2GRAY) | |
| roi_gray = cv2.resize(roi_gray,(48,48),interpolation=cv2.INTER_AREA) | |
| img = roi_gray.astype('float')/255.0 | |
| img = img_to_array(img) | |
| img = np.expand_dims(img,axis=0) | |
| prediction = classifier.predict(img)[0] | |
| #top_indices = np.argsort(prediction)[-2:] | |
| #top_emotion = top_indices[1] | |
| #second_emotion = top_indices[0] | |
| #label = emotions[top_emotion] | |
| confidences = {emotions[i]: float(prediction[i]) for i in range(len(emotions))} | |
| return confidences | |
| demo = gr.Interface( | |
| fn = predict_emotion, | |
| inputs = gr.Image(type="numpy"), | |
| outputs = gr.Label(num_top_classes=9), | |
| #flagging_options=["blurry", "incorrect", "other"], | |
| examples = [ | |
| os.path.join(os.path.dirname(__file__), "images/Image_1.jpg"), | |
| os.path.join(os.path.dirname(__file__), "images/Image_2.jpg"), | |
| os.path.join(os.path.dirname(__file__), "images/Image_3.jpg"), | |
| os.path.join(os.path.dirname(__file__), "images/Image_4.jpg"), | |
| os.path.join(os.path.dirname(__file__), "images/Image_5.jpg"), | |
| os.path.join(os.path.dirname(__file__), "images/Image_6.jpg"), | |
| os.path.join(os.path.dirname(__file__), "images/Image_7.jpg"), | |
| os.path.join(os.path.dirname(__file__), "images/Image_8.jpg"), | |
| os.path.join(os.path.dirname(__file__), "images/Image_9.jpg"), | |
| os.path.join(os.path.dirname(__file__), "images/Image_10.jpg"), | |
| ], | |
| title = "Whatchu feeling?", | |
| theme = "shivi/calm_seafoam" | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch() |