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Yshuo-Li authored Nov 19, 2021
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8 changes: 6 additions & 2 deletions configs/synthesizers/pix2pix/README.md
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Expand Up @@ -33,8 +33,12 @@ We use `FID` and `IS` metrics to evaluate the generation performance of pix2pix.
| official average | 111.678 | 2.624 | - |
| ours average | **106.139** | **2.664** | - |

Note: we strictly follow the [paper](http://openaccess.thecvf.com/content_cvpr_2017/papers/Isola_Image-To-Image_Translation_With_CVPR_2017_paper.pdf) setting in Section 3.3: "*At inference time, we run the generator net in exactly
Note: we strictly follow the [paper](http://openaccess.thecvf.com/content_cvpr_2017/papers/Isola_Image-To-Image_Translation_With_CVPR_2017_paper.pdf) setting in Section 3.3:

"*At inference time, we run the generator net in exactly
the same manner as during the training phase. This differs
from the usual protocol in that we apply dropout at test time,
and we apply batch normalization using the statistics of
the test batch, rather than aggregated statistics of the training batch.*" (i.e., use model.train() mode), thus may lead to slightly different inference results every time.
the test batch, rather than aggregated statistics of the training batch.*"

i.e., `use model.train()` mode, thus may lead to slightly different inference results every time.
41 changes: 19 additions & 22 deletions configs/synthesizers/pix2pix/README_zh-CN.md
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<!-- [ALGORITHM] -->
<details>
<summary align="right">Pix2Pix (CVPR'2017)</summary>
<summary align="right"><a href="https://arxiv.org/abs/1611.07004">Pix2Pix (CVPR'2017)</a></summary>

```bibtex
@inproceedings{isola2017image,
Expand All @@ -18,30 +18,27 @@

<br/>

We use `FID` and `IS` metrics to evaluate the generation performance of pix2pix.
我们使用 `FID` 和 `IS` 指标来评估 pix2pix 的生成表现。

`FID` evaluation:
| 算法 | FID | IS | 下载 |
| :----: | :-: | :-: | :------: |
| 官方 facades | **119.135** | 1.650 | - |
| [复现 facades](/configs/synthesizers/pix2pix/pix2pix_vanilla_unet_bn_1x1_80k_facades.py) | 127.792 | **1.745** | [模型](https://download.openmmlab.com/mmediting/synthesizers/pix2pix/pix2pix_facades/pix2pix_vanilla_unet_bn_1x1_80k_facades_20200524-6206de67.pth) \| [日志](https://download.openmmlab.com/mmediting/synthesizers/pix2pix/pix2pix_facades/pix2pix_vanilla_unet_bn_1x1_80k_facades_20200524_185039.log.json) |
| 官方 maps-a2b | 149.731 | 2.529 | - |
| [复现 maps-a2b](/configs/synthesizers/pix2pix/pix2pix_vanilla_unet_bn_a2b_1x1_219200_maps.py) | **118.552** | **2.689** | [模型](https://download.openmmlab.com/mmediting/synthesizers/pix2pix/pix2pix_maps_a2b/pix2pix_vanilla_unet_bn_a2b_1x1_219200_maps_20200524-b29c4538.pth) \| [日志](https://download.openmmlab.com/mmediting/synthesizers/pix2pix/pix2pix_maps_a2b/pix2pix_vanilla_unet_bn_a2b_1x1_219200_maps_20200524_191918.log.json) |
| 官方 maps-b2a | 102.072 | **3.552** | - |
| [复现 maps-b2a](/configs/synthesizers/pix2pix/pix2pix_vanilla_unet_bn_b2a_1x1_219200_maps.py) | **92.798** | 3.473 | [模型](https://download.openmmlab.com/mmediting/synthesizers/pix2pix/pix2pix_maps_b2a/pix2pix_vanilla_unet_bn_b2a_1x1_219200_maps_20200524-17882ec8.pth) \| [日志](https://download.openmmlab.com/mmediting/synthesizers/pix2pix/pix2pix_maps_b2a/pix2pix_vanilla_unet_bn_b2a_1x1_219200_maps_20200524_192641.log.json) |
| 官方 edges2shoes | **75.774** | **2.766** | - |
| [复现 edges2shoes](/configs/synthesizers/pix2pix/pix2pix_vanilla_unet_bn_wo_jitter_flip_1x4_186840_edges2shoes.py) | 85.413 | 2.747 | [模型](https://download.openmmlab.com/mmediting/synthesizers/pix2pix/pix2pix_edges2shoes_wo_jitter_flip/pix2pix_vanilla_unet_bn_wo_jitter_flip_1x4_186840_edges2shoes_20200524-b35fa9c0.pth) \| [日志](https://download.openmmlab.com/mmediting/synthesizers/pix2pix/pix2pix_edges2shoes_wo_jitter_flip/pix2pix_vanilla_unet_bn_wo_jitter_flip_1x4_186840_edges2shoes_20200524_193117.log.json) |
| 官方平均值 | 111.678 | 2.624 | - |
| 复现平均值 | **106.139** | **2.664** | - |

| Dataset | [facades](/configs/synthesizers/pix2pix/pix2pix_vanilla_unet_bn_1x1_80k_facades.py) | [maps-a2b](/configs/synthesizers/pix2pix/pix2pix_vanilla_unet_bn_a2b_1x1_219200_maps.py) | [maps-b2a](/configs/synthesizers/pix2pix/pix2pix_vanilla_unet_bn_b2a_1x1_219200_maps.py) | [edges2shoes](/configs/synthesizers/pix2pix/pix2pix_vanilla_unet_bn_wo_jitter_flip_1x4_186840_edges2shoes.py) | average |
| :------: | :--------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------: | :----------------------------------------------------------------------------------------------------------: | :---------: |
| official | **119.135** | 149.731 | 102.072 | **75.774** | 111.678 |
| ours | 127.792 | **118.552** | **92.798** | 85.413 | **106.139** |
注：我们严格遵守[论文](http://openaccess.thecvf.com/content_cvpr_2017/papers/Isola_Image-To-Image_Translation_With_CVPR_2017_paper.pdf)第3.3节中的设置：

`IS` evaluation:

| Dataset | facades | maps-a2b | maps-b2a | edges2shoes | average |
| :------: | :-------: | :-------: | :-------: | :---------: | :-------: |
| official | 1.650 | 2.529 | **3.552** | **2.766** | 2.624 |
| ours | **1.745** | **2.689** | 3.473 | 2.747 | **2.664** |

Model and log downloads:

| Dataset | facades | maps-a2b | maps-b2a | edges2shoes |
| :------: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
| download | [model](https://download.openmmlab.com/mmediting/synthesizers/pix2pix/pix2pix_facades/pix2pix_vanilla_unet_bn_1x1_80k_facades_20200524-6206de67.pth) \| [log](https://download.openmmlab.com/mmediting/synthesizers/pix2pix/pix2pix_facades/pix2pix_vanilla_unet_bn_1x1_80k_facades_20200524_185039.log.json) | [model](https://download.openmmlab.com/mmediting/synthesizers/pix2pix/pix2pix_maps_a2b/pix2pix_vanilla_unet_bn_a2b_1x1_219200_maps_20200524-b29c4538.pth) \| [log](https://download.openmmlab.com/mmediting/synthesizers/pix2pix/pix2pix_maps_a2b/pix2pix_vanilla_unet_bn_a2b_1x1_219200_maps_20200524_191918.log.json) | [model](https://download.openmmlab.com/mmediting/synthesizers/pix2pix/pix2pix_maps_b2a/pix2pix_vanilla_unet_bn_b2a_1x1_219200_maps_20200524-17882ec8.pth) \| [log](https://download.openmmlab.com/mmediting/synthesizers/pix2pix/pix2pix_maps_b2a/pix2pix_vanilla_unet_bn_b2a_1x1_219200_maps_20200524_192641.log.json) | [model](https://download.openmmlab.com/mmediting/synthesizers/pix2pix/pix2pix_edges2shoes_wo_jitter_flip/pix2pix_vanilla_unet_bn_wo_jitter_flip_1x4_186840_edges2shoes_20200524-b35fa9c0.pth) \| [log](https://download.openmmlab.com/mmediting/synthesizers/pix2pix/pix2pix_edges2shoes_wo_jitter_flip/pix2pix_vanilla_unet_bn_wo_jitter_flip_1x4_186840_edges2shoes_20200524_193117.log.json) |

Note: we strictly follow the [paper](http://openaccess.thecvf.com/content_cvpr_2017/papers/Isola_Image-To-Image_Translation_With_CVPR_2017_paper.pdf) setting in Section 3.3: "*At inference time, we run the generator net in exactly
"*At inference time, we run the generator net in exactly
the same manner as during the training phase. This differs
from the usual protocol in that we apply dropout at test time,
and we apply batch normalization using the statistics of
the test batch, rather than aggregated statistics of the training batch.*" (i.e., use model.train() mode), thus may lead to slightly different inference results every time.
the test batch, rather than aggregated statistics of the training batch.*"

即使用 `model.train()` 模式，因此可能会导致每次推理结果略有不同。

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