Merge branch 'main' of https://huggingface.co/spaces/namnh2002/video-summarization_timesformer

app.py

@@ -1,52 +0,0 @@
-import gradio as gr
-import cv2
-import numpy as np
-from transformers import pipeline
-import os
-import torch
-import torch.nn.functional as F
-from torchvision import transforms
-from torchvision.transforms import Compose
-import spaces
-
-title = "# Video Summarization using Timesformer Demo"
-description = """ Author: Nguyen Hoai Nam."""
-css = """
-#img-display-container {
-    max-height: 100vh;
-    }
-#img-display-input {
-    max-height: 80vh;
-    }
-#img-display-output {
-    max-height: 80vh;
-    }
-"""
-
-with gr.Blocks(css=css) as demo:
-    gr.Markdown(title)
-    gr.Markdown(description)
-    gr.Markdown("### Video Summarization demo")
-
-    with gr.Row():
-        input_video = gr.Video(label="Input Video")
-        model_type = gr.Dropdown(["K-means", "Sum of Squared Difference 01", "Sum of Squared Difference 02"], type="value", label='Model Type')
-    submit = gr.Button("Submit")
-    processed_video = gr.Video(label="Summarized Video")
-
-    def on_submit(uploaded_video,model_type):
-        pass        
-        # Process the video and get the path of the output video
-        #output_video_path = make_video(uploaded_video,encoder=model_type)
-
-        #return output_video_path
-        
-    submit.click(on_submit, inputs=[input_video, model_type], outputs=processed_video)
-
-    example_files = os.listdir('assets/examples_video')
-    example_files.sort()
-    example_files = [os.path.join('assets/examples_video', filename) for filename in example_files]
-    examples = gr.Examples(examples=example_files, inputs=[input_video], outputs=processed_video, fn=on_submit, cache_examples=True)
-
-if __name__ == '__main__':
-    demo.queue().launch()