Update app.py

app.py

@@ -1,18 +1,16 @@
 import tensorflow.keras as K
 from tensorflow.keras import layers
-        
 import keras
-
 import os
 import tensorflow as tf
 import gradio as gr
 from extract_landmarks import get_data_for_test,extract_landmark,merge_video_prediction
+from detect_from_videos import test_full_image_network
 
 block_size = 60
 DROPOUT_RATE = 0.5
 RNN_UNIT = 64
 os.environ["KMP_DUPLICATE_LIB_OK"]="TRUE"
-os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
 os.environ["CUDA_VISIBLE_DEVICES"] = "0"
 
 gpus = tf.config.list_physical_devices(device_type='GPU')
@@ -21,6 +19,8 @@ for gpu in gpus:
 device = "CPU" if len(gpus) == 0 else "GPU"
 print("using {}".format(device))
 
+model_path = '3_ff_raw.pkl'
+
 def predict(video):
     path = extract_landmark(video)
     test_samples, test_samples_diff, _, _, test_sv, test_vc = get_data_for_test(path, 1, block_size)
@@ -79,10 +79,12 @@ def predict(video):
         else:
             label = "Real"
     print("the pd is {}".format(pd))
-    return label
+    
+    output_video = test_full_image_network(video,model_path)
+    return label,output_video
 
 inputs = gr.inputs.Video()
-outputs = gr.outputs.Textbox()
+outputs = [gr.outputs.Textbox(),gr.Video()]
 iface = gr.Interface(fn=predict, inputs=inputs, outputs=outputs,
                      examples=[["sample__real.mp4"],["sample__fake.mp4"],["sample__real2.mp4"],["sample__fake2.mp4"]],
                      theme = "grass",