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| import torch | |
| import os | |
| import gradio as gr | |
| from video_transformers import VideoModel | |
| from utils import ( | |
| convert_frames_to_gif, | |
| download_youtube_video, | |
| sample_frames_from_video_file, | |
| ) | |
| video_model = VideoModel.from_transformers("facebook/timesformer-base-finetuned-k400") | |
| examples = [ | |
| ["https://www.youtube.com/watch?v=huAJ9dC5lmI"], | |
| ["https://www.youtube.com/watch?v=wvcWt6u5HTg"], | |
| ["https://www.youtube.com/watch?v=-3kZSi5qjRM"], | |
| ["https://www.youtube.com/watch?v=-6usjfP8hys"], | |
| ["https://www.youtube.com/watch?v=BDHub0gBGtc"], | |
| ["https://www.youtube.com/watch?v=B9ea7YyCP6E"], | |
| ["https://www.youtube.com/watch?v=BBkpaeJBKmk"], | |
| ["https://www.youtube.com/watch?v=BBqU8Apee_g"], | |
| ["https://www.youtube.com/watch?v=B8OdMwVwyXc"], | |
| ["https://www.youtube.com/watch?v=I7cwq6_4QtM"], | |
| ["https://www.youtube.com/watch?v=Z0mJDXpNhYA"], | |
| ["https://www.youtube.com/watch?v=QkQQjFGnZlg"], | |
| ["https://www.youtube.com/watch?v=IQaoRUQif14"], | |
| ] | |
| def predict(youtube_url): | |
| video_path = download_youtube_video(youtube_url) | |
| frames = sample_frames_from_video_file(video_path, num_frames=16) | |
| gif_path = convert_frames_to_gif(frames) | |
| result = video_model.predict(video_or_folder_path=video_path) | |
| os.remove(video_path) | |
| return result["predictions"], gif_path | |
| app = gr.Blocks() | |
| with app: | |
| gr.Markdown("# **<p align='center'>Video Classification with Timesformer</p>**") | |
| gr.Markdown( | |
| """ | |
| <p style='text-align: center'> | |
| Timesformer is a video model that uses a Transformer architecture to process video frames. | |
| <br>It is released by Facebook AI Research in ICML 2021. | |
| <br>This version is trained on Kinetics-400 dataset and can classify videos into 400 classes. | |
| </p> | |
| """ | |
| ) | |
| gr.Markdown( | |
| """ | |
| <p style='text-align: center'> | |
| Follow me for more! | |
| <br> <a href='https://twitter.com/fcakyon' target='_blank'>twitter</a> | <a href='https://github.com/fcakyon' target='_blank'>github</a> | <a href='https://www.linkedin.com/in/fcakyon/' target='_blank'>linkedin</a> | <a href='https://fcakyon.medium.com/' target='_blank'>medium</a> | |
| </p> | |
| """ | |
| ) | |
| with gr.Row(): | |
| with gr.Column(): | |
| gr.Markdown("Provide a Youtube video URL.") | |
| youtube_url = gr.Textbox(label="Youtube URL:", show_label=True) | |
| predict_btn = gr.Button(value="Predict") | |
| with gr.Column(): | |
| video_gif = gr.Image( | |
| label="Input Clip", | |
| show_label=True, | |
| ) | |
| with gr.Column(): | |
| predictions = gr.Label( | |
| label="Predictions:", show_label=True, num_top_classes=5 | |
| ) | |
| gr.Markdown("**Examples:**") | |
| gr.Examples( | |
| examples, | |
| youtube_url, | |
| [predictions, video_gif], | |
| fn=predict, | |
| cache_examples=True, | |
| ) | |
| predict_btn.click(predict, inputs=youtube_url, outputs=[predictions, video_gif]) | |
| gr.Markdown( | |
| """ | |
| \n Demo created by: <a href=\"https://github.com/fcakyon\">fcakyon</a> | |
| <br> Based on this <a href=\"https://huggingface.co/docs/transformers/main/model_doc/timesformer">HuggingFace model</a> | |
| """ | |
| ) | |
| app.launch() | |