Update app.py

app.py

@@ -1,4 +1,3 @@
-from huggingface_hub import hf_hub_download
 import gradio as gr
 import numpy as np
 import imageio
@@ -12,21 +11,6 @@ from utils import IMAGENET_MEAN, IMAGENET_STD, num_frames, patch_size, input_siz
 from labels import K400_label_map, SSv2_label_map, UCF_label_map
 
 
-# MODELS = {
-#     'K400': [
-#         './TFVideoMAE_S_K400_16x224_FT',
-#         './TFVideoMAE_S_K400_16x224_PT'
-#         ],
-#     'SSv2': [
-#         './TFVideoMAE_S_K400_16x224_FT',
-#         './TFVideoMAE_S_K400_16x224_PT'
-#         ],
-#     'UCF' : [
-#         './TFVideoMAE_S_K400_16x224_FT',
-#         './TFVideoMAE_S_K400_16x224_PT'
-#         ]
-# }
-
 LABEL_MAPS = {
     'K400': K400_label_map,
     'SSv2': SSv2_label_map,
@@ -57,7 +41,6 @@ def get_model(model_type):
     # pt_path = hf_hub_download(
     #     repo_id='innat/videomae', filename=model_type + '_PT', repo_type="model"
     # )
-
     ft_model = keras.models.load_model(model_type + '_FT')
     pt_model = keras.models.load_model(model_type + '_PT')
 
@@ -75,6 +58,10 @@ def get_model(model_type):
 
 
 def inference(video_file, model_type, mask_ratio):
+    print(video_file)
+    print(model_type)
+    print(mask_ratio)
+    print('---------------')
     # get sample data
     container = read_video(video_file)
     frames = frame_sampling(container, num_frames=num_frames)