def prepare(dataset, epochs, batch_size, base_path): get_masks = load_masks(dataset, base_path) stream = ds.epochs(dataset.image_ids, epochs) stream = ds.stream(lambda x: (dataset.load_image(x), get_masks(x)), stream) stream = ds.bufferize(stream, size=batch_size) batch = ds.stream_batch(stream, size=batch_size, fun=ds.pack_elements) return batch
def prepare(dataset, epochs, batch_size, input_shape, output_shape): stream = ds.epochs(dataset.image_ids, epochs) stream = ds.stream( lambda x: (dataset.load_image(x), dataset.load_output(x)), stream) stream = ds.stream(ds.apply_to_x(ds.resize(input_shape)), stream) stream = ds.stream(ds.apply_to_y(resize_all(output_shape)), stream) stream = ds.bufferize(stream, size=20) batch = ds.stream_batch(stream, size=batch_size, fun=ds.pack_elements) batch = ds.stream(ds.apply_to_y(ds.apply_to_xn( lambda x: ds.image2mask(x).reshape(x.shape + (1,)))), batch) return batch
def prepare(dataset, epochs, batch_size, input_shape): stream = ds.epochs(dataset.image_ids, epochs) stream = ds.stream( lambda x: (dataset.load_image(x), dataset.load_output(x)), stream) stream = ds.stream(ds.apply_to_xn(ds.resize(input_shape[:2])), stream) # stream = ds.stream(ds.apply_to_x(check), stream) stream = ds.bufferize(stream, size=20) batch = ds.stream_batch(stream, size=batch_size) batch = ds.stream( ds.apply_to_y(lambda x: ds.mask2image(x).reshape(x.shape + (1, ))), batch) return batch
def prepare(dataset, input_shape, output_shape): stream = ds.epochs(dataset.image_ids, epochs=1) stream = ds.stream( lambda x: (dataset._img_filenames[x], (x, dataset.load_output(x))), stream) # stream = ds.stream(ds.apply_to_x(ds.resize(input_shape)), stream) stream = ds.stream(ds.apply_to_y(resize_all(dataset, output_shape)), stream) stream = ds.bufferize(stream, size=10) batch = ds.stream_batch(stream, size=10, fun=ds.pack_elements) # batch = ds.stream(ds.apply_to_y(check), batch) batch = ds.stream( ds.apply_to_y(ds.apply_to_xn(lambda x: ds.image2mask(x))), batch) return batch