Create app.py

app.py

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+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}