mmagic.models.editors.inst_colorization.colorization_net
¶
Module Contents¶
Classes¶
Real-Time User-Guided Image Colorization with Learned Deep Priors. The |
- class mmagic.models.editors.inst_colorization.colorization_net.ColorizationNet(input_nc, output_nc, norm_type, use_tanh=True, classification=True)[source]¶
Bases:
mmengine.model.BaseModule
Real-Time User-Guided Image Colorization with Learned Deep Priors. The backbone used for.
https://arxiv.org/abs/1705.02999
Codes adapted from ‘https://github.com/ericsujw/InstColorization.git’ ‘InstColorization/blob/master/models/networks.py#L108’
- Parameters
input_nc (int) – input image channels
output_nc (int) – output image channels
norm_type (str) – instance normalization or batch normalization
use_tanh (bool) – Whether to use nn.Tanh() Default: True.
classification (bool) – backprop trunk using classification, otherwise use regression. Default: True
- forward(input_A, input_B, mask_B)[source]¶
Forward function.
- Parameters
input_A (tensor) – Channel of the image in lab color space
input_B (tensor) – Color patch
mask_B (tensor) – Color patch mask
- Returns
Classification output out_reg (tensor): Regression output feature_map (dict): The full-image feature
- Return type
out_class (tensor)