app.py

import numpy as np

import gradio as gr


import os

import tempfile

import shutil

# from gradio_inter.predict_from_file import predict_from_file
from gradio_inter.create_bash_file import create_bash_file

def create_temp_file(path: str) -> str:
    temp_dir = tempfile.gettempdir()
    temp_folder = os.path.join(temp_dir, "denoising")
    os.makedirs(temp_folder, exist_ok=True)
    # Clean up directory
    # for i in os.listdir(temp_folder):
    #     print("Removing", i)
    #     os.remove(os.path.join(temp_folder, i))

    temp_path = os.path.join(temp_folder, path.split("/")[-1])
    shutil.copy2(path, temp_path)
    return temp_path

# from gradio_inter.predict import predict_from_data
# from gradio_inter.predi

def transpose(matrix):
    return matrix.T


def predict(file_path: str):
    temp_file_path = create_temp_file(file_path)
    # predict_from_file
    temp_bash_file = create_bash_file(temp_file_path)
    
    os.system(f"bash {temp_bash_file}")
    
    res_file_path = "/tmp/denoising/save/predicted_infos_seed_0_tag_20231104_017_jts_spatial_t_100__st_0.npy"
    
    return res_file_path
    

demo = gr.Interface(
    predict,
    # gr.Dataframe(type="numpy", datatype="number", row_count=5, col_count=3),
    gr.File(type="filepath"),
    gr.File(type="filepath"),
    cache_examples=False
)

if __name__ == "__main__":
    demo.launch()