Create app.py

app.py

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+import gradio as gr
+from transformers import AutoImageProcessor, AutoModel
+import torch
+
+# Cargar el modelo DINOv2 una sola vez
+processor = AutoImageProcessor.from_pretrained("facebook/dinov2-base")
+model = AutoModel.from_pretrained("facebook/dinov2-base")
+
+def get_embedding(image):
+    inputs = processor(images=image, return_tensors="pt")
+    with torch.no_grad():
+        embeddings = model(**inputs).last_hidden_state[:, 0]  # CLS token
+    return embeddings.squeeze().tolist()
+
+# Gradio UI solo para aceptar imágenes y devolver JSON
+iface = gr.Interface(
+    fn=get_embedding,
+    inputs=gr.Image(type="pil"),
+    outputs="json",
+    description="Microservicio para extraer embeddings de imágenes usando DINOv2."
+)
+
+iface.launch()