def get_preproc_image():
data_params = Data.default_params()
data_params.skip_invalid_gt = False
data_params.pre_proc.run_parallel = False
data_params.pre_proc.processors = data_params.pre_proc.processors[:-1]
for p in data_params.pre_proc.processors_of_type(FinalPreparationProcessorParams):
p.pad = 0
post_init(data_params)
pl = Data(data_params).create_pipeline(DataPipelineParams, None)
pl.mode = PipelineMode.PREDICTION
preproc = data_params.pre_proc.create(pl)
def pp(image):
its = InputSample(
image, None, SampleMeta("001", fold_id="01")
).to_input_target_sample()
s = preproc.apply_on_sample(its)
return s.inputs
return pp
def get_preproc_text(rtl=False):
data_params = Data.default_params()
data_params.skip_invalid_gt = False
data_params.pre_proc.run_parallel = False
if rtl:
for p in data_params.pre_proc.processors_of_type(BidiTextProcessorParams):
p.bidi_direction = BidiDirection.RTL
post_init(data_params)
pl = Data(data_params).create_pipeline(DataPipelineParams, None)
pl.mode = PipelineMode.TARGETS
preproc = data_params.pre_proc.create(pl)
def pp(text):
its = InputSample(
None, text, SampleMeta("001", fold_id="01")
).to_input_target_sample()
s = preproc.apply_on_sample(its)
return s.targets
return pp