app.py

from fastapi import FastAPI, UploadFile, File
from transformers import AutoModelForImageClassification, AutoProcessor
from PIL import Image
import torch

app = FastAPI()

# Carga el modelo y el preprocesador desde Hugging Face
model_name = "jazzmacedo/fruits-and-vegetables-detector-36"
model = AutoModelForImageClassification.from_pretrained(model_name)
processor = AutoProcessor.from_pretrained(model_name)

@app.post("/predict")
async def predict(file: UploadFile = File(...)):
    # Procesa la imagen recibida
    image = Image.open(file.file).convert("RGB")
    inputs = processor(images=image, return_tensors="pt")

    # Realiza la predicción
    with torch.no_grad():
        outputs = model(**inputs)
    
    # Obtiene la predicción con mayor probabilidad
    logits = outputs.logits
    predicted_class_idx = logits.argmax(-1).item()
    predicted_class_name = model.config.id2label[predicted_class_idx]

    return {"prediction": predicted_class_name}