tensorflow/models · error · FileNotFoundError

Image not found at {image_path}

Error message

Image not found at {image_path}

What it means

Error "Image not found at {image_path}" thrown in tensorflow/models.

Source

Thrown at official/projects/waste_identification_ml/Deploy/detr_cloud_deployment/client/triton_server_inference.py:132

  def _get_input_batch_for_inference(self, image_path: str) -> np.ndarray:
    """Preprocesses an image for Triton inference.

    Loads an image, resizes it, converts it to RGB, normalizes pixel values,
    and transposes it to the channel-first format expected by the model.

    Args:
      image_path: The path to the input image file.

    Returns:
      A numpy array representing the preprocessed image, ready for inference.

    Raises:
      FileNotFoundError: If the image file does not exist.
    """
    original_image = cv2.imread(image_path)
    if original_image is None:
      raise FileNotFoundError(f'Image not found at {image_path}')

    rgb_image = cv2.cvtColor(original_image, cv2.COLOR_BGR2RGB)
    resized_image = cv2.resize(
        rgb_image, self.input_size, interpolation=cv2.INTER_AREA
    )

    # Normalize: (pixel / 255 - mean) / std
    float_image = resized_image.astype(np.float32) / 255.0
    normalized_image = (float_image - self.means) / self.stds

    # Transpose to CHW and add batch dimension
    transposed_image = np.transpose(normalized_image, (2, 0, 1))
    batched_image = np.expand_dims(transposed_image, axis=0).astype(np.float32)
    return batched_image

  def _reformat_triton_output_to_dict(
      self,
      outputs: List[np.ndarray],

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/projects/waste_identification_ml/Deploy/detr_cloud_deployment/client/triton_server_inference.py:132 when the library encounters an invalid state.

Common situations: See trigger scenarios.

AI-assisted analysis of tensorflow/models@e006f5f0d5 (2026-08-24). Data as JSON: /api/errors/82299b7c79db3b01. Report an issue: GitHub.