update app

app.py

@@ -29,10 +29,7 @@ state_dict = torch.load(ckpts[0], map_location=torch.device(device))['state_dict
 net = Model_LA(args, len(token_to_ix), pretrained_emb).to(device)
 net.load_state_dict(state_dict)
 
-
-
 def inference(video_path, text):
-    
     # data preprocessing
     # text
     def clean(w):
@@ -54,9 +51,18 @@ def inference(video_path, text):
     A = pad_feature(mel, a_max_len)
     V = pad_feature(mel, v_max_len)
     # print shapes
-    print("Processed text shape: ", L.shape)
-    print("Processed audio shape: ", A.shape)
-    print("Processed video shape: ", V.shape)
+    print(f"Processed text shape from {len(s)} to {L.shape}")
+    print(f"Processed audio shape from {mel.shape} to {A.shape}")
+    print(f"Processed video shape from {mel.shape} to {V.shape}")
+
+    net.train(False)
+    x = np.expand_dims(L,axis=0)
+    y = np.expand_dims(A,axis=0)
+    z = np.expand_dims(V,axis=0)
+    x, y, z = torch.from_numpy(x).to(device), torch.from_numpy(y).to(device), torch.from_numpy(z).float().to(device)
+    pred = net(x, y, z).cpu().data.numpy()
+    label_to_ix = ['happy', 'sad', 'angry', 'fear', 'disgust', 'surprise']
+    result_dict = dict(zip(label_to_ix, pred[0]))
     return out
 
 
@@ -69,18 +75,14 @@ description="This is a demo implementation of EfficientNetV2 Deepfakes Image Det
             "
             
 examples = [              
-                ['Video1-fake-1-ff.mp4'],
-                ['Video6-real-1-ff.mp4'],
-                ['Video3-fake-3-ff.mp4'],
-                ['Video8-real-3-ff.mp4'],
-                ['real-1.mp4'],
-                ['fake-1.mp4'],
+                ['examples/03bSnISJMiM_1.mp4', "IT WAS REALLY GOOD "],
+                ['examples/03bSnISJMiM_5.mp4', "AND THEY SHOULDVE I GUESS "],
            ]
            
 gr.Interface(inference,
                      inputs = ["video", "text"],
-                     outputs=["text","text", gr.outputs.Video(label="Detected face sequence")],
+                     outputs=["label"],
                      title=title,
                      description=description,
                      examples=examples
-                     ).launch()
+                     ).launch(debug=True)

requirements.txt

@@ -1 +1,2 @@
-https://github.com/explosion/spacy-models/releases/download/en_vectors_web_lg-2.1.0/en_vectors_web_lg-2.1.0.tar.gz
+https://github.com/explosion/spacy-models/releases/download/en_vectors_web_lg-2.1.0/en_vectors_web_lg-2.1.0.tar.gz
+torch==1.9.1