app.py

# prompt: gradio image 分类
import fastai
from fastai.vision import *
from fastai.vision.learner import load_learner
from PIL import Image 
import gradio as gr

# Load the model
model = load_learner("model.pkl")

# Define an image classification function
def classify_image(image):
    # Preprocess the image
    image = Image.open(image).resize((192, 192))

    # Make a prediction
    prediction = model.predict(image)[0]

    # Return the prediction
    return {prediction: 1.0}

# Create the Gradio interface
image_input = gr.Image()
label_output = gr.Label(num_top_classes=3)
interface = gr.Interface(fn=classify_image, inputs=image_input, outputs=label_output)

# Launch the interface
interface.launch()