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How to use _build_param_dict method in rester

Best Python code snippet using rester_python

transform_wrappers.py

Source:transform_wrappers.py

1from PIL import Image2def _build_param_dict(conf, required_params, optional_params=[],3                      key_renames={}, kwargs={}):4  # Filter out params which are passed in kwargs5  required_params = [p for p in required_params if p not in kwargs]6  param_dict = conf.to_param_dict(required_params,7                                  optional_params.copy(),8                                  key_renames)9  param_dict.update(kwargs)10  return param_dict11def get_sr_transform(conf, mode, **kwargs):12  def _get_interp(method):13    if method == 'bilinear':14      return Image.BILINEAR15    elif method == 'bicubic':16      return Image.BICUBIC17    else:18      raise ValueError('Unknown interpolation method {}'.format(method))19  assert mode in ('train', 'test')20  required_params = [21      'train_crop_size', 'upscale_factor'22  ]23  # Maps keys in configuration to parameter names in transform functions24  key_renames = {25      'train_crop_size': 'crop_size',26      'test_crop_size': 'crop_size',27      'scale_to_orig': 'upscale'28  }29  if mode == 'train':30    from data.sr_transforms import sr_train_transform31    optional_params = {32        'scale_to_orig': False,33        'interpolation': 'bilinear'34    }35    param_dict = _build_param_dict(conf,36                                   required_params,37                                   optional_params,38                                   key_renames,39                                   kwargs)40    param_dict['interpolation'] = _get_interp(param_dict['interpolation'])41    transform = sr_train_transform(**param_dict)42  else:43    from data.sr_transforms import sr_test_transform44    optional_params = {45        'scale_to_orig': False,46        'interpolation': 'bilinear',47        'full_image': False48    }49    param_dict = _build_param_dict(conf,50                                   required_params,51                                   optional_params,52                                   key_renames,53                                   kwargs)54    param_dict['interpolation'] = _get_interp(param_dict['interpolation'])55    transform = sr_test_transform(**param_dict)56  return transform57def get_sr_output_transform(conf, mode, **kwargs):58  assert mode in ('train', 'test', 'output')59  if mode == 'train':60    from data.sr_transforms import sr_output_train_transform61    transform = sr_output_train_transform(convert_luma=True)62  else:63    from data.sr_transforms import sr_output_test_transform64    if mode == 'test':65      param_dict = _build_param_dict(conf,66                                     ['upscale_factor'],67                                     kwargs={'crop_border_pixels': True,68                                             'convert_luma': True})69    else:70      param_dict = _build_param_dict(conf,71                                     ['upscale_factor'])72    transform = sr_output_test_transform(**param_dict)73  return transform74def get_output_transform(conf, application, mode, **kwargs):75  applications = {76      'super_resolution': get_sr_output_transform,77  }78  assert application in applications...

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