app.py

import gradio as gr
import requests
from io import BytesIO

url = 'http://188.166.196.227:8000/predict'

def inference(input_image):
    # Convert the PIL image to bytes
    img_bytes = BytesIO()
    input_image.save(img_bytes, format='JPEG')
    
    # Send the POST request with the image data as 'image' key
    files = {'image': ('input.jpg', img_bytes.getvalue(), 'image/jpeg')}
    response = requests.post(url, files=files)

    # Check if the request was successful (status code 200)
    if response.status_code == 200:
        return response.json()
    else:
        print("POST request failed with status code:", response.status_code)

title = "SeeFood102"
description = "Gradio frontend for SeeFood102, the expansion edition of SeeFood101. Note: due to cost, I shutdown the K8S cluster backend."

examples = [
    ['Screenshot 2023-05-05 085533.png']
]

iface = gr.Interface(fn=inference,
                     inputs=gr.Image(type="pil"),
                     outputs=gr.Label(num_top_classes=5),
                     title=title,
                     description=description,
                     examples=examples,
                     analytics_enabled=False)
iface.launch()