initial commit

.ipynb_checkpoints/Untitled-checkpoint.ipynb

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

app.py

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+import gradio as gr
+from fastai.vision.all import *
+import skimage
+
+learn = load_learner('model.pkl')
+
+labels = learn.dls.vocab
+def predict(img):
+    img = PILImage.create(img)
+    pred,pred_idx,probs = learn.predict(img)
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+title = "Bear/Teddy bear Classifier"
+interpretation='default'
+enable_queue=True
+
+gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),
+outputs=gr.outputs.Label(num_top_classes=3),
+title=title,interpretation=interpretation,
+enable_queue=enable_queue).launch()

model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:402d742adfd1c851f2bb73c90ccce82124992163b849c0b5d6c3c19bd0a49cc3
+size 46965281

requirements.txt

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+fastai
+scikit-image