def apply_inference_graph(model_path):
    """Run inference from a different graph, which receives encoded images buffers. """
    pred_config = PredictConfig(
        session_init=get_model_loader(model_path),
        model=InferenceOnlyModel(),
        input_names=['input_img_bytes'],
        output_names=['prediction_img_bytes'])

    pred = OfflinePredictor(pred_config)
    buf = open('lena.png', 'rb').read()
    prediction = pred([buf])[0]
    with open('applied_inference_graph.png', 'wb') as f:
        f.write(prediction[0])
def apply_inference_graph ( model_path ) : pred_config = PredictConfig ( session_init = get_model_loader ( model_path ) , model = InferenceOnlyModel ( ) , input_names = [ 'input_img_bytes' ] , output_names = [ 'prediction_img_bytes' ] ) pred = OfflinePredictor ( pred_config ) buf = open ( 'lena.png' , 'rb' ) . read ( ) prediction = pred ( [ buf ] ) [ 0 ] with open ( 'applied_inference_graph.png' , 'wb' ) as f : f . write ( prediction [ 0 ] )
Run inference from a different graph, which receives encoded images buffers.