Spaces:
Build error
Build error
| import gradio as gr | |
| from slowfast import slow_fast_train | |
| from video_object_extraction import video_object_extraction | |
| from audio_feature_extraction_final import audio_feature_extraction | |
| from CustomFile import CustomFile | |
| import numpy as np | |
| import pandas as pd | |
| import pickle | |
| import torch | |
| try: | |
| import detectron2 | |
| except: | |
| import os | |
| os.system('pip install git+https://github.com/facebookresearch/detectron2.git') | |
| def predict(video_path, frames): | |
| # gpu = torch.cuda.is_available() | |
| # video_1, df1 = slow_fast_train(video_path, gpu) | |
| # video_2, df2 = video_object_extraction(video_path,frames) | |
| # audio_path = audio_feature_extraction(video_path, gpu) | |
| # return ([video_1, video_2,audio_path], df1, df2) | |
| audio_features = np.random.rand(2,2) | |
| audio_path = 'audio_embeddings' | |
| with open(audio_path, 'wb') as f: | |
| pickle.dump(audio_features, f) | |
| df = pd.DataFrame() | |
| return ([video_path, video_path, audio_path], df, df) | |
| iface = gr.Interface(predict, inputs= [gr.Video(), gr.Slider(1, 100, value=15)], outputs=[CustomFile(), gr.Dataframe(max_rows = 10),gr.Dataframe(max_rows = 10)]) | |
| iface.launch(show_error=True) |