app.py

import gradio as gr

def greet(name):
    return "Hello " + name + "!!"

iface = gr.Interface(fn=greet, inputs="text", outputs="text")
iface.launch()

import fastbook
from fastbook import *
from fastai.vision.widgets import *
import skimage
from skimage import io as skio
import numpy
from PIL import Image, ImageEnhance
def name_to_hrs (r): return float(round(float(os.path.basename(r)[0:-4].split("_")[1][1:])*(minutes/60)+5,2))
def validation_split (r):  return os.path.basename(r)[0:-4].split("_")[3] == "R0003" or os.path.basename(r)[0:-4].split("_")[3] == "R0006"
def get_label_filename(name): return path/'labels'/f'{name.stem}_annotationLabels.tif'
zebrafish_age_predictor = load_learner(path/'FishAge.pkl')
zebrafish_classifier = load_learner(path/'FishSegmentation.pkl')