DRRGModuleLoss¶

class mmocr.models.textdet.DRRGModuleLoss(ohem_ratio=3.0, downsample_ratio=1.0, orientation_thr=2.0, resample_step=8.0, num_min_comps=9, num_max_comps=600, min_width=8.0, max_width=24.0, center_region_shrink_ratio=0.3, comp_shrink_ratio=1.0, comp_w_h_ratio=0.3, text_comp_nms_thr=0.25, min_rand_half_height=8.0, max_rand_half_height=24.0, jitter_level=0.2, loss_text={'eps': 1e-05, 'fallback_negative_num': 100, 'type': 'MaskedBalancedBCEWithLogitsLoss'}, loss_center={'type': 'MaskedBCEWithLogitsLoss'}, loss_top={'reduction': 'none', 'type': 'SmoothL1Loss'}, loss_btm={'reduction': 'none', 'type': 'SmoothL1Loss'}, loss_sin={'type': 'MaskedSmoothL1Loss'}, loss_cos={'type': 'MaskedSmoothL1Loss'}, loss_gcn={'type': 'CrossEntropyLoss'})[源代码]¶

The class for implementing DRRG loss. This is partially adapted from https://github.com/GXYM/DRRG licensed under the MIT license.

DRRG: Deep Relational Reasoning Graph Network for Arbitrary Shape Text Detection.

参数

ohem_ratio (float) – The negative/positive ratio in ohem. Defaults to 3.0.
downsample_ratio (float) – Downsample ratio. Defaults to 1.0. TODO: remove it.
orientation_thr (float) – The threshold for distinguishing between head edge and tail edge among the horizontal and vertical edges of a quadrangle. Defaults to 2.0.
resample_step (float) – The step size for resampling the text center line. Defaults to 8.0.
num_min_comps (int) – The minimum number of text components, which should be larger than k_hop1 mentioned in paper. Defaults to 9.
num_max_comps (int) – The maximum number of text components. Defaults to 600.
min_width (float) – The minimum width of text components. Defaults to 8.0.
max_width (float) – The maximum width of text components. Defaults to 24.0.
center_region_shrink_ratio (float) – The shrink ratio of text center regions. Defaults to 0.3.
comp_shrink_ratio (float) – The shrink ratio of text components. Defaults to 1.0.
comp_w_h_ratio (float) – The width to height ratio of text components. Defaults to 0.3.
min_rand_half_height (float) – The minimum half-height of random text components. Defaults to 8.0.
max_rand_half_height (float) – The maximum half-height of random text components. Defaults to 24.0.
jitter_level (float) – The jitter level of text component geometric features. Defaults to 0.2.
loss_text (dict) – The loss config used to calculate the text loss. Defaults to dict(type='MaskedBalancedBCEWithLogitsLoss', fallback_negative_num=100, eps=1e-5).
loss_center (dict) – The loss config used to calculate the center loss. Defaults to dict(type='MaskedBCEWithLogitsLoss').
loss_top (dict) – The loss config used to calculate the top loss, which is a part of the height loss. Defaults to dict(type='SmoothL1Loss', reduction='none').
loss_btm (dict) – The loss config used to calculate the bottom loss, which is a part of the height loss. Defaults to dict(type='SmoothL1Loss', reduction='none').
loss_sin (dict) – The loss config used to calculate the sin loss. Defaults to dict(type='MaskedSmoothL1Loss').
loss_cos (dict) – The loss config used to calculate the cos loss. Defaults to dict(type='MaskedSmoothL1Loss').
loss_gcn (dict) – The loss config used to calculate the GCN loss. Defaults to dict(type='CrossEntropyLoss').
text_comp_nms_thr (float) –

返回类型

None

forward(preds, data_samples)[源代码]¶

Compute Drrg loss.

参数

preds (tuple) – The prediction tuple(pred_maps, gcn_pred, gt_labels), each of shape \((N, 6, H, W)\), \((N, 2)\) and \((m ,n)\), where \(m * n = N\).
data_samples (list[TextDetDataSample]) – The data samples.

返回

A loss dict with loss_text, loss_center, loss_height, loss_sin, loss_cos, and loss_gcn.

返回类型

dict

get_targets(data_samples)[源代码]¶

Generate loss targets from data samples.

参数: data_samples (list(TextDetDataSample)) – Ground truth data samples.
返回: A tuple of 8 lists of tensors as DRRG targets. Read docstring of _get_target_single for more details.
返回类型: tuple