Update app.py

app.py

@@ -1,30 +1,20 @@
 import gradio as gr
 from fastai.vision.all import *
 import skimage
-
+from fastai.vision.all import PILImage
 
 learn = load_learner('model.pkl')
-#from huggingface_hub import from_pretrained_fastai
-#learn = from_pretrained_fastai("devdatanalytics/commonbean")
 
 labels = learn.dls.vocab
+
 def predict(img):
-    img = PILImage.create(img)
-    pred,pred_idx,probs = learn.predict(img)
-    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+ img = PILImage.create(img)
+ img = img.resize((512, 512))
+ pred,pred_idx,probs = learn.predict(img)
+ return {labels[i]: float(probs[i]) for i in range(len(labels))}
 
-#title = "Common beans diseases classfier"
-#description = "An app for Common beans diseases Classisfication"
-#article="<p style='text-align: center'>The app identifies and classifies common beans diseases: Anthracnose and Bean rust.</p>"
-# Create the Gradio interface
-interface = gr.Interface(
-    fn=predict,
-    inputs=gr.Image(),
-    outputs=gr.Label(num_top_classes=3)
-)
+#examples = ['image.jpg']
 
-# Enable the queue to handle POST requests
-interface.queue(api_open=True)
+#gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=3),examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch()
+gr.Interface(fn=predict,inputs=gr.Image(),outputs=gr.Label(num_top_classes=3)).launch().share=True
 
-# Launch the interface
-interface.launch()