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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+model_9.keras filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,67 @@
+import gradio as gr
+import os
+import cv2
+import PIL
+from PIL import Image
+from mtcnn import MTCNN
+import numpy as np
+from tensorflow.keras.models import load_model
+from keras.preprocessing.image import img_to_array
+
+emotions = ['neutral','happiness','surprise','sadness','anger','disgust','fear','contempt','unknown']
+classifier = load_model("model_9.keras")
+face_detector_mtcnn = MTCNN()
+
+
+def predict_emotion(image):
+
+    faces = face_detector_mtcnn.detect_faces(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?"
+)
+    
+
+
+if __name__ == "__main__":
+    demo.launch()

model_9.keras

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:805a2ce0814a8910a68a06bf54b0bb1579595307972b8f211c5dadf35c59cdad
+size 16531714