new

.ipynb_checkpoints/Untitled-checkpoint.ipynb

@@ -0,0 +1,6 @@
+{
+ "cells": [],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

.ipynb_checkpoints/Untitled1-checkpoint.ipynb

@@ -0,0 +1,6 @@
+{
+ "cells": [],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

.ipynb_checkpoints/Untitled2-checkpoint.ipynb

@@ -0,0 +1,6 @@
+{
+ "cells": [],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

app.py

@@ -1,7 +1,27 @@
+__all__=['is_cat','learn','classify_image','categories','image','label','examples','intf']
+
+
+from fastai.vision.all import*
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+def is_cat(x): return x[0].isupper()
+
+learn=load_learner('model.pkl')
+
+categories=('dog','cat')
+
+def classify_image(img):
+    pred,idx,probs=learn.predict(img)
+    return dict(zip(categories, map(float,probs)))
+
+image=gr.inputs.Image(shape=(192,192))
+label = gr.outputs.Label()
+examples=['dog.jpg','cat.jpg','dunno.jpg']
+
+intf=gr.Interface(fn=classify_image,inputs=image,outputs=label,examples=examples)
+intf.launch(inline=False)
+# def greet(name):
+#     return "Hello " + name + "!!"
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+# iface = gr.Interface(fn=greet, inputs="text", outputs="text")
+# iface.launch()

model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1c09d8f778f89c9eb588eefd9a5ba094eb163cd3ea708a4ea567a83e924f149f
+size 47059947