Update pipeline.py

pipeline.py

@@ -0,0 +1,32 @@
+import cv2
+import numpy as np
+import tensorflow as tf
+
+# Load model
+model = tf.keras.models.load_model("efficientnet-b0/")
+
+class DetectionPipeline:
+    def __init__(self, batch_size=1):
+        self.batch_size = batch_size
+    
+    def __call__(self, filename):
+        print('Processing image...')
+        image = cv2.cvtColor(filename, cv2.COLOR_BGR2RGB)
+        image = cv2.resize(image, (224, 224))
+        return image
+
+# Initialize image detection pipeline
+detection_image_pipeline = DetectionPipeline()
+
+def deepfakes_image_predict(input_image):
+    face = detection_image_pipeline(input_image)
+    face2 = face / 255.0
+    pred = model.predict(np.expand_dims(face2, axis=0))[0]
+    real, fake = pred[0], pred[1]
+    
+    if real > 0.5:
+        text = f"The image is REAL. \n Deepfakes Confidence: {round(100 - (real * 100), 3)}%"
+    else:
+        text = f"The image is FAKE. \n Deepfakes Confidence: {round(fake * 100, 3)}%"
+    
+    return text