export_model.py

from nbdev.export import nb_export
nb_export(r"C:\Users\klath\Downloads\dogs-v-cats.ipynb", ".")

#| export
from fastai.vision.all import *
import gradio as gr

def is_cat(x): return x[0].isupper() 

#| export
learn = load_learner('C:\Users\klath\Downloads\K.L\SAMFORD DRPH - SUMMER 2025\HIIM 661\model.pkl')

#| export
categories = ('Dog', 'Cat')

def classify_images(img):
    #'Is it a car?', 'Is it a car? but as zero or one', 'probabillity of [dog, cat]'
    pred, idx, probs = learn.predict(img)
    #return dictionary
    #zip together the categories and the
                                        #turn probs to float
    return dict(zip(categories, map(float, probs)))

#| export
image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label()
examples = ['C:\Users\klath\Downloads\K.L\SAMFORD DRPH - SUMMER 2025\HIIM 661\dog.jpg', 'C:\Users\klath\Downloads\K.L\SAMFORD DRPH - SUMMER 2025\HIIM 661\cat.jpg', 'C:\Users\klath\Downloads\K.L\SAMFORD DRPH - SUMMER 2025\HIIM 661\catdog.jpg', 'C:\Users\klath\Downloads\K.L\SAMFORD DRPH - SUMMER 2025\HIIM 661\he-s-a-catdog-or-dogcat.jpeg']

intf = gr.Interface(fn=classify_images, inputs=image, outputs=label, examples=examples)
intf.launch(inline=False)



#| export
from fastai.vision.all import *
import gradio as gr

def is_cat(x): return x[0].isupper() 

#| export
learn = load_learner('C:\Users\klath\Downloads\K.L\SAMFORD DRPH - SUMMER 2025\HIIM 661\model.pkl')

#| export
categories = ('Dog', 'Cat')

def classify_images(img):
    #'Is it a car?', 'Is it a car? but as zero or one', 'probabillity of [dog, cat]'
    pred, idx, probs = learn.predict(img)
    #return dictionary
    #zip together the categories and the
                                        #turn probs to float
    return dict(zip(categories, map(float, probs)))

#| export
image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label()
examples = ['C:\Users\klath\Downloads\K.L\SAMFORD DRPH - SUMMER 2025\HIIM 661\dog.jpg', 'C:\Users\klath\Downloads\K.L\SAMFORD DRPH - SUMMER 2025\HIIM 661\cat.jpg', 'C:\Users\klath\Downloads\K.L\SAMFORD DRPH - SUMMER 2025\HIIM 661\catdog.jpg', 'C:\Users\klath\Downloads\K.L\SAMFORD DRPH - SUMMER 2025\HIIM 661\he-s-a-catdog-or-dogcat.jpeg']

intf = gr.Interface(fn=classify_images, inputs=image, outputs=label, examples=examples)
intf.launch(inline=False)