Create app.py

app.py

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+import gradio as gr
+from fastai.vision.all import *
+import torch
+
+learn = load_learner('food_classif_model_v1.pkl')
+
+def predict_image(img):
+    pred,los,prob = learn.predict(img)
+    top_values, top_indx = torch.topk(prob, 3) # show 3 max values
+
+    if (top_values < 0.4).all():
+        return 'I do not know what is that'
+    else:    
+        return f'{food_indx[top_indx[0]]} = {top_values[0]}\n{food_indx[top_indx[1]]} = {top_values[1]}\n{food_indx[top_indx[2]]} = {top_values[2]}'
+
+
+# UI huggface
+
+intrfce = gr.Interface(fn=predict_image,
+             inputs=gr.Image(type="pil"),
+             outputs=gr.Label(num_top_classes=3)).launch()