add app.py

app.py

@@ -0,0 +1,58 @@
+# Bismillahir Rahmaanir Raheem 
+# Almadadh Ya Gause Radi Allahu Ta'alah Anh - Ameen 
+
+
+from fastai.vision.all import *
+import gradio as gr
+
+
+def is_cat(x):
+	return x[0].isupper()
+	
+
+
+# load the trained fast ai model for predictions
+learn = load_learner('model.pkl')
+
+
+# define the function to call
+categories = ('Dog', 'Cat') 
+
+def predict(img):
+	pred, idx, probs = learn.predict(img)
+	return dict(zip(categories, map(float, probs)))
+	
+	
+title = "CAT PREDICTOR"
+
+description = "A cat predictor model trained on the Pets dataset with fastai. Created as a demo for Gradio and Hugging Face spaces."
+
+
+article = "<p style='text-align: center'><span style='font-size: 15pt;'>CAT_PREDICTOR. 2022. </span></p>"
+
+
+image = gr.inputs.Image(shape=(192, 192))
+label = gr.outputs.Label()
+examples = ['chapter1_cat_example.jpg']
+interpretation = 'default'
+enable_queue = True 
+
+
+
+
+iface = gr.Interface(
+		fn=predict, 
+		title=title, 
+		description=description, 
+		article=article,
+		inputs=image, 
+		outputs=label,
+		#theme="grass",
+		examples=examples,
+		interpretation=interpretation,
+		enable_queue=enable_queue
+)
+
+
+
+iface.launch(inline=False)