setup fastai vision learner

app.py

@@ -1,7 +1,26 @@
 import gradio as gr
+from fastai.vision.all import *
 
-def greet(name):
-    return "Hello " + name + "!!"
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+def get_data():
+    # Label function
+    def is_cat(x:string): return x[0].isupper()
+
+    # Read the dataset from fastai
+    path = untar_data(URLs.PETS)/'images'
+    return ImageDataLoaders.from_name_func(
+        path,get_image_files(path), valid_pct=0.2, seed=42,
+        label_func=is_cat, item_tfms=Resize(224))
+    
+if __name__ == '__main__':
+    # This is required for windows users
+    multiprocessing.set_start_method('spawn')
+    dls = get_data() 
+
+    # Train the model with vision_learner
+    learn = vision_learner(dls, resnet34, metrics=error_rate)
+    learn.fine_tune(1)
+
+    demo = gr.Interface(fn=learn.predict, inputs="image", outputs="text")
+    demo.launch()
+

requirements.txt

@@ -0,0 +1,2 @@
+fastai==2.7.7
+gradio==3.20.0