feat: add the generated model

app.py

@@ -1,11 +1,10 @@
 import gradio as gr
 from fastai.vision.all import *
 
+# Label function
+def is_cat(x:string): return x[0].isupper()
 
 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(
@@ -18,9 +17,22 @@ if __name__ == '__main__':
     dls = get_data() 
 
     # Train the model with vision_learner
-    learn = vision_learner(dls, resnet34, metrics=error_rate)
-    learn.fine_tune(1)
+    # learn = vision_learner(dls, resnet34, metrics=error_rate)
+    # learn.fine_tune(1)
 
-    demo = gr.Interface(fn=learn.predict, inputs="image", outputs="text")
-    demo.launch()
+    # #Export the model
+    # learn.path = Path('.')
+    # learn.export(
+    #     'cats_classifier.pkl'
+    # )
+
+    model = load_learner('cats_classifier.pkl')
 
+    def predict(image):
+        img = PILImage.create(image)
+        pred,pred_idx,probs = model.predict(img)
+        # print('tt',pred,pred_idx,probs)
+        return f"Probability it's a cat: {probs[1].item():.6f}" 
+
+    demo = gr.Interface(fn=model.predict, inputs="image", outputs='text')
+    demo.launch()

cats_classifier.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3ae938ddb9d7daf92b295528b5dd019303dea1cc2cc090e01bf230ac0e4b00c5
+size 87564116