model(**inputs) instead model(img.unsqueeze...)

app.py

@@ -17,8 +17,8 @@ def query_image(img):
     """Función para generar predicciones a la escala origina"""
     inputs = preprocessor(images=img, return_tensors="pt")
     with torch.no_grad():
-        preds = model(inputs.unsqueeze(0).to(device))["logits"]
-        #preds = model(image.unsqueeze(0).to(device))["logits"]
+        #preds = model(inputs.unsqueeze(0).to(device))["logits"]
+        preds = model(**inputs)["logits"]
     preds_upscale = upscale_logits_modified(preds, image.shape[2])
     predict_label = torch.argmax(preds_upscale, dim=1).to(device)
     return predict_label[0,:,:].detach().cpu().numpy()