Python imagenet_preprocess_input Examples

Example #1

File: 1_testing.py Project: erikagardini/ImageFeaturization

def _bagging_predict(style_name, img_name, x,model):
    x_flip = np.copy(x)
    x_flip = np.fliplr(x_flip)
    x = imagenet_preprocess_input(x)
    x_flip = imagenet_preprocess_input(x_flip)
    pred = model.predict(x[np.newaxis,...])
    print(model.input)

    #mod_2
    _save_intermediate_output(model, x, style_name, img_name, layer=-2, filename=RES_PATH + '/img_dataset_testing.csv')

    pred_flip = model.predict(x_flip[np.newaxis,...])
    avg = np.mean(np.array([pred,pred_flip]), axis=0 )
    return avg

Example #2

File: Rasta_evaluation.py Project: ngonthier/Icono_Art_Analysis

def _preprocess_input(x, preprocessing=None):
    if preprocessing == 'imagenet':
        return imagenet_preprocess_input(x)
    elif preprocessing == 'wp':
        return wp_preprocess_input(x)
    else:
        return x