app.py

from fastai.vision.all import *
from fastai.vision.all import load_learner
import gradio as gr

fruit_labels = ('Anthracnose', 'Apple Scab', 'Black Spot', 'Blight', 
                'Blossom End Rot', 'Botrytis', 'Brown Rot', 'Canker', 
                'Cedar Apple Rust', 'Clubroot', 'Crown Gall', 'Downy Mildew', 
                'Fire Blight', 'Fusarium', 'Gray Mold', 'Leaf Spots', 'Mosaic Virus', 
                'Nematodes', 'Powdery Mildew', 'Verticillium')

model=load_learner("crop_model_1.pkl")

def recognize_image(image):
  pred, idx, probs = model.predict(image)
  print(pred)
  return dict(zip(fruit_labels, map(float, probs)))


image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label(num_top_classes=5)  # Remove the unused parameter 'type'
examples = [
    'image_1.jpg',
    'image_2.jpeg',
    'image_3.jpeg',
    'image_4.jpeg'
]

iface = gr.Interface(fn=recognize_image, inputs=image, outputs=label, examples=examples)
iface.launch(inline=False)