app.py

from transformers import AutoImageProcessor, AutoModelForImageClassification
from PIL import Image
import gradio as gr
import torch

# Model yükle
processor = AutoImageProcessor.from_pretrained("umutbozdag/plant-identity")
model = AutoModelForImageClassification.from_pretrained("umutbozdag/plant-identity")

# Tahmin fonksiyonu
def predict(image):
    image = image.convert("RGB")
    inputs = processor(images=image, return_tensors="pt")
    with torch.no_grad():
        outputs = model(**inputs)
    logits = outputs.logits
    predicted_class_idx = logits.argmax(-1).item()
    predicted_label = model.config.id2label[predicted_class_idx]
    return predicted_label

# Arayüz
iface = gr.Interface(
    fn=predict,
    inputs=gr.Image(type="pil", label="Bitki Fotoğrafı Yükle"),
    outputs=gr.Textbox(label="Tahmin Edilen Bitki"),
    title="🌿 Bitki Tanıma Sistemi",
    description="Bir bitki fotoğrafı yükleyin",
    article="✨ Lumi çalışıyor..."
)

iface.launch()