app.py

import gradio as gr
from transformers import pipeline
from PIL import Image

# Swin modelini pipeline ile yükle
model_name = "kedimestan/swin-base-patch4-window7-224"
classifier = pipeline("image-classification", model=model_name)

# Tahmin fonksiyonu
def predict(image: Image.Image):
    # Görüntüyü sınıflandırma yaparak tahmin edin
    image = image.resize((224, 224))
    result = classifier(image)
    return result[0]["label"]

# Gradio arayüzü
inputs = gr.Image(type="pil", label="Görsel Yükle")
outputs = gr.Textbox(label="Tahmin Sonucu")

gr.Interface(
    fn=predict,
    inputs=inputs,
    outputs=outputs,
    title="Retinoblastoma Tespiti",
    theme="default"
).launch(debug=True)