Create app.py

app.py

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+import gradio as gr
+from transformers import AutoFeatureExtractor, AutoModelForImageClassification
+from PIL import Image
+import torch
+import pandas as pd
+
+# Cargar modelo de reconocimiento de alimentos
+model_name = "nateraw/food101"  # modelo preentrenado Food-101
+model = AutoModelForImageClassification.from_pretrained(model_name)
+extractor = AutoFeatureExtractor.from_pretrained(model_name)
+
+# Cargar tabla de nutrición de ejemplo
+# Debes subir nutrition.csv después con columnas: food, calories, protein, fat, carbs
+nutrition_df = pd.read_csv("nutrition.csv")  
+
+def analizar_comida(imagen: Image):
+    # Preprocesar imagen
+    inputs = extractor(images=imagen, return_tensors="pt")
+    with torch.no_grad():
+        outputs = model(**inputs)
+    
+    predicted_class = model.config.id2label[outputs.logits.]()_