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()