"Done"

.ipynb_checkpoints/app-checkpoint.ipynb

@@ -0,0 +1,56 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "8f87b679",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "pip install fastai\n",
+ "pip install gradio"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "f2458b29",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#|default_exp app\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "79013522",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#|export\n"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.10.6"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

app.py

@@ -1,7 +1,28 @@
+# AUTOGENERATED! DO NOT EDIT! File to edit: ../app.ipynb.
+
+# %% auto 0
+__all__ = ['model', 'categories', 'image', 'label', 'examples', 'intf', 'classify_image']
+
+# %% ../app.ipynb 3
+from fastai.vision.all import *
+
 import gradio as gr
 
-def greet(name):
- return "Hello " + name + "!!"
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+# %% ../app.ipynb 6
+model=load_learner('model.pkl')
+
+# %% ../app.ipynb 8
+categories = ('black', 'grizzly','teddy')
+
+def classify_image(img):
+ pred, idx, probs = model.predict(img) 
+ return dict(zip(categories, map (float,probs)))
+
+# %% ../app.ipynb 10
+image= gr.inputs.Image(shape=(192, 192)) 
+label= gr.outputs.Label() 
+examples =['black.jpg', 'teddy.jpg']
+
+intf= gr.Interface(fn =classify_image, inputs= image, outputs= label, Examples= examples) 
+intf.launch(inline=False, share=True, debug=True)

app/app.py

@@ -0,0 +1,28 @@
+# AUTOGENERATED! DO NOT EDIT! File to edit: ../app.ipynb.
+
+# %% auto 0
+__all__ = ['model', 'categories', 'image', 'label', 'examples', 'intf', 'classify_image']
+
+# %% ../app.ipynb 3
+from fastai.vision.all import *
+
+import gradio as gr
+
+
+# %% ../app.ipynb 6
+model=load_learner('model.pkl')
+
+# %% ../app.ipynb 8
+categories = ('black', 'grizzly','teddy')
+
+def classify_image(img):
+ pred, idx, probs = model.predict(img) 
+ return dict(zip(categories, map (float,probs)))
+
+# %% ../app.ipynb 10
+image= gr.inputs.Image(shape=(192, 192)) 
+label= gr.outputs.Label() 
+examples =['black.jpg', 'teddy.jpg']
+
+intf= gr.Interface(fn =classify_image, inputs= image, outputs= label, Examples= examples) 
+intf.launch(inline=False, share=True, debug=True)

bpp/app.py

@@ -0,0 +1,28 @@
+# AUTOGENERATED! DO NOT EDIT! File to edit: ../app.ipynb.
+
+# %% auto 0
+__all__ = ['model', 'categories', 'image', 'label', 'examples', 'intf', 'classify_image']
+
+# %% ../app.ipynb 3
+from fastai.vision.all import *
+
+import gradio as gr
+
+
+# %% ../app.ipynb 6
+model=load_learner('model.pkl')
+
+# %% ../app.ipynb 8
+categories = ('black', 'grizzly','teddy')
+
+def classify_image(img):
+ pred, idx, probs = model.predict(img) 
+ return dict(zip(categories, map (float,probs)))
+
+# %% ../app.ipynb 10
+image= gr.inputs.Image(shape=(192, 192)) 
+label= gr.outputs.Label() 
+examples =['/content/black.jpg', '/content/grizzly.jpg', '/content/teddy.jpg']
+
+intf= gr.Interface(fn =classify_image, inputs= image, outputs= label, Examples= examples) 
+intf.launch(inline=False, share=True, debug=True)

model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e86d9f2c10ec40a15cadd4ca5f59fca23ee66a134bbaed6d14781e0b67429641
+size 46973327