Create app.py

app.py

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+import gradio as gr
+from fastai.vision.all import load_learner
+from fastai import *
+import torch
+import os
+from PIL import Image
+
+
+model_path  = 'model3-86%.pkl'
+
+model = load_learner(model_path)
+
+def result(path):  
+  
+  pred,_,probability = model.predict(path)
+  pred = str(pred)
+  pred = pred.upper()
+
+  return {pred: float(probability.max())}
+
+path = 'test/'
+
+image_path = []
+
+for i in os.listdir(path):
+  image_path.append(path+i) 
+
+
+image = gr.inputs.Image(shape =(200,200),image_mode='L',invert_colors=False)
+label = gr.outputs.Label()
+
+iface = gr.Interface(fn=result, inputs=image, outputs=label, examples = image_path)
+iface.launch(inline=False)