app.py

from fastapi import FastAPI, File, UploadFile
from fastapi.responses import JSONResponse
from PIL import Image
import tensorflow as tf
import numpy as np
import io

app = FastAPI()

# Load model
model = tf.keras.models.load_model("klasifikasi_batik_model.keras")

# Label yang kamu pakai
labels = ['Kawung', 'Mega_Mendung', 'Parang', 'Truntum']

def preprocess_image(image: Image.Image):
    image = image.resize((224, 224))  # Ubah jika input size berbeda
    image = np.array(image) / 255.0
    image = np.expand_dims(image, axis=0)
    return image

@app.post("/predict")
async def predict(file: UploadFile = File(...)):
    contents = await file.read()
    image = Image.open(io.BytesIO(contents)).convert("RGB")
    
    processed_image = preprocess_image(image)
    predictions = model.predict(processed_image)
    predicted_probabilities = predictions[0]

    if np.max(predicted_probabilities) < 0.80:
        result = "Gambar bukan batik"
    else:
        result = labels[np.argmax(predicted_probabilities)]

    probabilities = {labels[i]: float(predicted_probabilities[i]) for i in range(len(labels))}

    return JSONResponse(content={
        "prediction": result,
        "probabilities": probabilities
    })