data_juicer.ops.deduplicator.image_deduplicator module

data_juicer.ops.deduplicator.image_deduplicator.get_hash_method(method_name)

class data_juicer.ops.deduplicator.image_deduplicator.ImageDeduplicator(method: str = 'phash', consider_text: bool = False, *args, **kwargs)

Bases: Deduplicator

Deduplicates samples at the document level by exact matching of images.

This operator compares images across documents to identify and remove duplicates. - It uses a specified hash method (default is ‘phash’) to compute image hashes. - If consider_text is set, it also considers text content for deduplication, using a text deduplicator in conjunction with the image hashes. - The key metric, imagehash, is computed for each sample. If consider_text is enabled, an additional hash field is used. - Duplicates are identified by comparing these hash values. Samples with identical hashes are considered duplicates. - When show_num is greater than 0, the operator also returns a subset of duplicate pairs for tracing purposes. - The operator caches the imagehash and, if applicable, the hash fields.

__init__(method: str = 'phash', consider_text: bool = False, *args, **kwargs)

Initialization method.

Parameters:

• method – hash method for image

• consider_text – whether to consider text hash together with image hash when applying deduplication.

• args – extra args

• kwargs – extra args

compute_hash(sample, context=False)

Compute hash values for the sample.

Parameters:

sample – input sample

Returns:

sample with computed hash value.

process(dataset, show_num=0)

For doc-level, dataset –> dataset.

Parameters:

• dataset – input dataset

• show_num – number of traced samples used when tracer is open.

Returns:

deduplicated dataset and the sampled duplicate pairs.