JTStephens commited on
Commit
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Browse files
.ipynb_checkpoints/Untitled-checkpoint.ipynb ADDED
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+ {
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+ "cells": [],
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+ "metadata": {},
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+ "nbformat": 4,
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+ "nbformat_minor": 5
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+ }
Untitled.ipynb ADDED
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+ {
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+ "cells": [
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+ {
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+ "cell_type": "code",
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+ "execution_count": null,
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+ "id": "83eb7185",
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+ "metadata": {},
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+ "outputs": [],
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+ "source": []
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+ }
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+ ],
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+ "metadata": {
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+ "kernelspec": {
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+ "display_name": "Python 3 (ipykernel)",
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+ "language": "python",
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+ "name": "python3"
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+ },
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+ "language_info": {
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+ "codemirror_mode": {
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+ "name": "ipython",
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+ "version": 3
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+ },
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+ "file_extension": ".py",
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+ "mimetype": "text/x-python",
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+ "name": "python",
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+ "nbconvert_exporter": "python",
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+ "pygments_lexer": "ipython3",
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+ "version": "3.11.3"
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+ }
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+ },
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+ "nbformat": 4,
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+ "nbformat_minor": 5
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+ }
app.py CHANGED
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  import gradio as gr
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- def greet(name):
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- return "Hello " + name + "1"
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- iface = gr.Interface(fn=greet, inputs="text", outputs="text")
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- iface.launch()
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ from fastai.vision.all import *
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  import gradio as gr
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+ def is_cat(x): return
 
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+ learn = load_learner('model.pkl')
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+
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+ categories = ('Dog', 'Cat')
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+
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+
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+ def classify_image(img):
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+ pred, pred_idx, probs = learn.predict(img)
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+ return dict(zip(categories, map(float, probs)))
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+
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+
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+ image = gr.inputs.Image(shape=(192, 192))
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+ label = gr.outputs.Label()
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+ examples = ["dog.jpg", "cat.jpg", "dunno.jpg"]
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+
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+
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+ iface = gr.Interface(fn=classify_image, inputs=image,
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+ outputs=label, examples=examples)
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+ iface.launch(inline=False)
model.pkl ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:106a4d704e07b7ef014ca8a9c12599b48bfceb54fd41c4c2a0712c52003c897c
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+ size 47063121