BNNPreprocess / app.py
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import os
os.system("pip -qq install h5py")
os.system("pip -qq install torch")
os.system("pip -qq install torchvision")
os.system("pip -qq install pandas")
os.system("pip -qq install scikit-image")
from dataset import FrameDataset
import numpy as np
import gradio as gr
def generate_frames(ffile,dfile):
dataset = FrameDataset(ffile=ffile,dfile=dfile)
patches = dataset.get_peaks_skimage()
normalized_patches = dataset.normalize_patches(patches)
np.save("normalized_patches.npy",normalized_patches)
return normalized_patches
interface=gr.Interface(fn=generate_frames, inputs=[gr.File(label="frame file",type="binary"),gr.File(label="dark file",type="binary")],
outputs=gr.outputs.File("peaks.npy"))
interface.launch()