update reqs

app.py

@@ -59,19 +59,16 @@ def inference(video_path, text):
     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()
+    pred = net(x, y, z).cpu().data.numpy()[0]
+    # normalize between 0 and 1
+    pred = (pred + pred.min()) / (pred.max() - pred.min())
     label_to_ix = ['happy', 'sad', 'angry', 'fear', 'disgust', 'surprise']
-    result_dict = dict(zip(label_to_ix, pred[0]))
+    result_dict = {label_to_ix[i]: float(pred[i]) for i in range(len(label_to_ix))}
     return result_dict
 
 
 title="Emotion Recognition"
-description="This is a demo implementation of EfficientNetV2 Deepfakes Image Detector by using frame-by-frame detection. \
-            To use it, simply upload your video, or click one of the examples to load them.\
-            This demo and model represent the work of \"Achieving Face Swapped Deepfakes Detection Using EfficientNetV2\" by Lee Sheng Yeh. \
-            The examples were extracted from Celeb-DF(V2)(Li et al, 2020) and FaceForensics++(Rossler et al., 2019). Full reference details is available in \"references.txt.\" \
-            The examples are used under fair use to demo the working of the model only. If any copyright is infringed, please contact the researcher via this email: tp054565@mail.apu.edu.my, the researcher will immediately take down the examples used.\
-            "
+description=""
             
 examples = [              
                 ['examples/03bSnISJMiM_1.mp4', "IT WAS REALLY GOOD "],

requirements.txt

@@ -1,3 +1,9 @@
-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
-librosa
+gradio==2.8.5
+librosa==0.9.1
+soundfile==0.10.3.post1
+matplotlib==3.5.1
+numpy==1.21.2
+scipy==1.5.3
+tensorflow==2.8.0
+torch==1.10.1
+https://github.com/explosion/spacy-models/releases/download/en_vectors_web_lg-2.1.0/en_vectors_web_lg-2.1.0.tar.gz