mirror of
https://github.com/open-mmlab/mmdeploy.git
synced 2025-01-14 08:09:43 +08:00
f7c484a046
* Add support for inpainting models * Add configs * Add comment * Refactor * Add test code for inpainting task * Fix * Fix * Update * Fix * Fix * Update docs * Update * Fix visualization * Handle case without Resize
110 lines
3.9 KiB
Python
110 lines
3.9 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
|
|
exp_name = 'deepfillv1_256x256_8x2_places'
|
|
|
|
model = dict(
|
|
type='DeepFillv1Inpaintor',
|
|
encdec=dict(
|
|
type='DeepFillEncoderDecoder',
|
|
stage1=dict(
|
|
type='GLEncoderDecoder',
|
|
encoder=dict(type='DeepFillEncoder', padding_mode='reflect'),
|
|
decoder=dict(
|
|
type='DeepFillDecoder',
|
|
in_channels=128,
|
|
padding_mode='reflect'),
|
|
dilation_neck=dict(
|
|
type='GLDilationNeck',
|
|
in_channels=128,
|
|
act_cfg=dict(type='ELU'),
|
|
padding_mode='reflect')),
|
|
stage2=dict(
|
|
type='DeepFillRefiner',
|
|
encoder_attention=dict(
|
|
type='DeepFillEncoder',
|
|
encoder_type='stage2_attention',
|
|
padding_mode='reflect'),
|
|
encoder_conv=dict(
|
|
type='DeepFillEncoder',
|
|
encoder_type='stage2_conv',
|
|
padding_mode='reflect'),
|
|
dilation_neck=dict(
|
|
type='GLDilationNeck',
|
|
in_channels=128,
|
|
act_cfg=dict(type='ELU'),
|
|
padding_mode='reflect'),
|
|
contextual_attention=dict(
|
|
type='ContextualAttentionNeck',
|
|
in_channels=128,
|
|
padding_mode='reflect'),
|
|
decoder=dict(
|
|
type='DeepFillDecoder',
|
|
in_channels=256,
|
|
padding_mode='reflect'))),
|
|
disc=dict(
|
|
type='DeepFillv1Discriminators',
|
|
global_disc_cfg=dict(
|
|
type='MultiLayerDiscriminator',
|
|
in_channels=3,
|
|
max_channels=256,
|
|
fc_in_channels=65536,
|
|
fc_out_channels=1,
|
|
num_convs=4,
|
|
norm_cfg=None,
|
|
act_cfg=dict(type='ELU'),
|
|
out_act_cfg=dict(type='LeakyReLU', negative_slope=0.2)),
|
|
local_disc_cfg=dict(
|
|
type='MultiLayerDiscriminator',
|
|
in_channels=3,
|
|
max_channels=512,
|
|
fc_in_channels=32768,
|
|
fc_out_channels=1,
|
|
num_convs=4,
|
|
norm_cfg=None,
|
|
act_cfg=dict(type='ELU'),
|
|
out_act_cfg=dict(type='LeakyReLU', negative_slope=0.2))),
|
|
stage1_loss_type=('loss_l1_hole', 'loss_l1_valid'),
|
|
stage2_loss_type=('loss_l1_hole', 'loss_l1_valid', 'loss_gan'),
|
|
loss_gan=dict(type='GANLoss', gan_type='wgan', loss_weight=0.0001),
|
|
loss_l1_hole=dict(type='L1Loss', loss_weight=1.0),
|
|
loss_l1_valid=dict(type='L1Loss', loss_weight=1.0),
|
|
loss_gp=dict(type='GradientPenaltyLoss', loss_weight=10.0),
|
|
loss_disc_shift=dict(type='DiscShiftLoss', loss_weight=0.001),
|
|
pretrained=None)
|
|
|
|
test_cfg = dict(metrics=['l1', 'psnr', 'ssim'])
|
|
|
|
test_pipeline = [
|
|
dict(type='LoadImageFromFile', key='gt_img'),
|
|
dict(
|
|
type='LoadMask',
|
|
mask_mode='bbox',
|
|
mask_config=dict(
|
|
max_bbox_shape=(128, 128),
|
|
max_bbox_delta=40,
|
|
min_margin=20,
|
|
img_shape=(256, 256))),
|
|
dict(type='Crop', keys=['gt_img'], crop_size=(384, 384), random_crop=True),
|
|
dict(type='Resize', keys=['gt_img'], scale=(256, 256), keep_ratio=False),
|
|
dict(
|
|
type='Normalize',
|
|
keys=['gt_img'],
|
|
mean=[127.5, 127.5, 127.5],
|
|
std=[127.5, 127.5, 127.5],
|
|
to_rgb=False),
|
|
dict(type='GetMaskedImage'),
|
|
dict(
|
|
type='Collect',
|
|
keys=['gt_img', 'masked_img', 'mask', 'mask_bbox'],
|
|
meta_keys=['gt_img_path']),
|
|
dict(type='ImageToTensor', keys=['gt_img', 'masked_img', 'mask']),
|
|
dict(type='ToTensor', keys=['mask_bbox'])
|
|
]
|
|
data = dict(
|
|
test_dataloader=dict(samples_per_gpu=1),
|
|
test=dict(
|
|
type='ImgInpaintingDataset',
|
|
ann_file='tests/test_codebase/test_mmedit/data/ann_file.txt',
|
|
data_prefix='tests/test_codebase/test_mmedit/data',
|
|
pipeline=test_pipeline,
|
|
test_mode=True))
|