app.py

from gradio_client import Client, file
import gradio as gr
import os
HEADERS = {
    "Authorization": f"Bearer {os.environ['HF_TOKEN']}"
}

client = Client("mariem2024/plantID")

def predict(image_path):
    try:
        result = client.predict(
            file(image_path),  # Doğru: gradio `filepath` tipini dosya nesnesine dönüştürüyor
            api_name="/predict"
        )
        return result
    except Exception as e:
        return f"Hata oluştu: {str(e)}"

demo = gr.Interface(
    fn=predict,
    inputs=gr.Image(type="filepath"),
    outputs="text",
    title="Bitki Tanıma",
    description="Bu arayüz Hugging Face Space üzerinden bitki türünü tahmin eder."
)

demo.launch()