JunkvHealth Food model

.ipynb_checkpoints/app-checkpoint.ipynb

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+{
+ "cells": [],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

export.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:9b6aec690ccbcd8bf8a77769ab144a3e221745f5fff10904fcce1a2c9b8d6fdd
+size 46963151

foods/app.py

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+# AUTOGENERATED! DO NOT EDIT! File to edit: ../app.ipynb.
+
+# %% auto 0
+__all__ = ['learn', 'categories', 'image', 'label', 'examples', 'intf', 'classify_image']
+
+# %% ../app.ipynb 1
+from fastai.vision.all import *
+import gradio as gr
+
+# %% ../app.ipynb 3
+learn = load_learner('export.pkl')
+
+# %% ../app.ipynb 5
+categories = ('Healthy', 'Junk')
+
+def classify_image(img):
+    pred, idx, probs = learn.predict(img)
+    return dict(zip(categories, map(float, probs)))
+
+# %% ../app.ipynb 7
+image = gr.inputs.Image(shape=(192,192))
+label = gr.outputs.Label()
+examples = ['hf2.jpg', 'hf3.jpg', 'hf4.jpg', 'jf2.jpg', 'jf3.jpg', 'jf4.jpg','jf5.jpg']
+
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
+intf.launch(inline=False)