Emotion reco

emotion/Emotional_recoLITE.py

@@ -0,0 +1,47 @@
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import cv2
+import numpy as np
+
+from PIL import Image
+
+import tensorflow as tf
+
+def init():
+    global labels
+    global interpreter
+
+    labels = ['Angry', 'Disgusted', 'Fear', 'Happy', 'Neutral', 'Sad', 'Surprised']
+    interpreter = tf.lite.Interpreter(model_path="model.tflite")
+    interpreter.allocate_tensors()
+
+
+
+def detect(image):
+    input_details = interpreter.get_input_details()
+    output_details = interpreter.get_output_details()
+    height = 48
+    width = 48
+    data = image
+    gray = (np.float32(data), cv2.COLOR_RGB2GRAY)
+    data = np.array(gray)
+    data = data.resize((width, height))
+
+
+    interpreter.invoke()
+
+    output_data = interpreter.get_tensor(output_details[0]['index'])
+    results = np.squeeze(output_data)
+    top_percentage = results.argsort()[-1:][::-1]
+
+    for i in top_percentage:
+
+        print('{:08.6f}: {}'.format(float(results[i]), labels[i]))
+
+if __name__ == '__main__':
+
+    init()
+    img = Image.open('sad.jpg')
+    detect(img)

emotion/README.md

@@ -1 +1,2 @@
-#Facial Emotion Sensing
+# Facial Expression Recognition
+