diff --git a/README.md b/README.md index 9a6944145be4c82e02e3500209e6c01e10de46a7..32574ee5e019078cf33bca0c8a4c6983a58bc638 100644 --- a/README.md +++ b/README.md @@ -32,31 +32,10 @@ PaddleGAN 是一个基于飞桨的生成对抗网络开发工具包. ## 安装 -### 1. 安装 paddlepaddle - -PaddleGAN 所需的版本: -* PaddlePaddle >= 2.0.0-rc -* Python >= 3.5+ - -``` -pip install -U paddlepaddle-gpu -``` - -### 2. 安装ppgan -``` -python -m pip install 'git+https://github.com/PaddlePaddle/PaddleGAN.git' -``` - -或者通过将项目克隆到本地 -``` -git clone https://github.com/PaddlePaddle/PaddleGAN -cd PaddleGAN - -pip install -v -e . # or "python setup.py develop" -``` +请参考[安装文档](./docs/install.md)来进行PaddlePaddle和ppgan的安装 ## 数据准备 -请参考 [数据准备](./docs/data_prepare.md) 来准备对应的数据. +请参考[数据准备](./docs/data_prepare.md) 来准备对应的数据. ## 快速开始 diff --git a/README_en.md b/README_en.md index bc06bf1538048d187d8bd274f66040209bf90763..888d0cbedef4c84cb479ec988f03bc83d95fc948 100644 --- a/README_en.md +++ b/README_en.md @@ -1,4 +1,4 @@ -English | [简体中文](./README_cn.md) +English | [简体中文](./README.md) # PaddleGAN @@ -35,35 +35,13 @@ changes. ## Install -### 1. install paddlepaddle - -PaddleGAN work with: -* PaddlePaddle >= 2.0.0-rc -* Python >= 3.5+ - -``` -pip install -U paddlepaddle-gpu -``` - -### 2. install ppgan - -``` -python -m pip install 'git+https://github.com/PaddlePaddle/PaddleGAN.git' -``` - -Or install it from a local clone -``` -git clone https://github.com/PaddlePaddle/PaddleGAN -cd PaddleGAN - -pip install -v -e . # or "python setup.py develop" -``` +Please refer to [install](./docs/install_en.md). ## Data Prepare -Please refer to [data prepare](./docs/data_prepare.md) for dataset preparation. +Please refer to [data prepare](./docs/data_prepare_en.md) for dataset preparation. ## Get Start -Please refer [get started](./docs/get_started.md) for the basic usage of PaddleGAN. +Please refer [get started](./docs/get_started_en.md) for the basic usage of PaddleGAN. ## Model tutorial * [Pixel2Pixel and CycleGAN](./docs/tutorials/pix2pix_cyclegan.md) diff --git a/data/download_cyclegan_data.py b/data/download_cyclegan_data.py new file mode 100644 index 0000000000000000000000000000000000000000..307632872df131629fc55f0a5e4393bb1c91c89b --- /dev/null +++ b/data/download_cyclegan_data.py @@ -0,0 +1,30 @@ +import os +import argparse + +from ppgan.utils.download import get_path_from_url + +CYCLEGAN_URL_ROOT = 'https://people.eecs.berkeley.edu/~taesung_park/CycleGAN/datasets/' + +parser = argparse.ArgumentParser(description='download datasets') +parser.add_argument('--name', + type=str, + required=True, + help='dataset name, \ + support dataset name: apple2orange, summer2winter_yosemite, \ + horse2zebra, monet2photo, cezanne2photo, ukiyoe2photo, \ + vangogh2photo, maps, cityscapes, facades, iphone2dslr_flower, \ + ae_photos, cityscapes') + +if __name__ == "__main__": + args = parser.parse_args() + + data_url = CYCLEGAN_URL_ROOT + args.name + '.zip' + + if args.name == 'cityscapes': + data_url = 'https://paddlegan.bj.bcebos.com/datasets/cityscapes.zip' + + path = get_path_from_url(data_url) + + dst = os.path.join('data', args.name) + print('symlink {} to {}'.format(path, dst)) + os.symlink(path, dst) diff --git a/data/download_pix2pix_data.py b/data/download_pix2pix_data.py new file mode 100644 index 0000000000000000000000000000000000000000..ed250c7486c5429777164404a99e55d8c6ef5985 --- /dev/null +++ b/data/download_pix2pix_data.py @@ -0,0 +1,25 @@ +import os +import argparse + +from ppgan.utils.download import get_path_from_url + +PIX2PIX_URL_ROOT = 'http://efrosgans.eecs.berkeley.edu/pix2pix/datasets/' + +parser = argparse.ArgumentParser(description='download datasets') +parser.add_argument('--name', + type=str, + required=True, + help='dataset name, \ + support dataset name: cityscapes, night2day, edges2handbags, \ + edges2shoes, facades, maps') + +if __name__ == "__main__": + args = parser.parse_args() + + data_url = PIX2PIX_URL_ROOT + args.name + '.tar.gz' + + path = get_path_from_url(data_url) + + dst = os.path.join('data', args.name) + print('symlink {} to {}'.format(path, dst)) + os.symlink(path, dst) diff --git a/docs/data_prepare.md b/docs/data_prepare.md index 546f09f433f99dc530e8822f486b25e4c44be590..4f5e21bed33b4c5afdf2b2000aa10c3da2f40169 100644 --- a/docs/data_prepare.md +++ b/docs/data_prepare.md @@ -1,6 +1,6 @@ ## 数据准备 -推荐把数据集软链接到 `$PaddleGAN/data`. 软链接后的目录结构如下图所示： +现有的配置默认数据集的路径是在`$PaddleGAN/data`下，目录结构如下图所示。如果你已经下载好数据集了，建议将数据集软链接到 `$PaddleGAN/data`。 ``` PaddleGAN @@ -28,8 +28,65 @@ PaddleGAN ``` -### cyclegan 相关的数据集下载 +如果将数据集放在其他位置，比如 ```your/data/path```， +你可以修改配置文件中的 ```dataroot``` 参数: + +``` +dataset: + train: + name: PairedDataset + dataroot: your/data/path + num_workers: 4 +``` + +### CycleGAN模型相关的数据集下载 + +#### 已有的数据集下载 + +##### 从网页下载 cyclgan模型相关的数据集可以在[这里](https://people.eecs.berkeley.edu/~taesung_park/CycleGAN/datasets/)下载 -### pix2pix 相关的数据集下载 +##### 使用脚本下载 +我们在 ```PaddleGAN/data``` 文件夹下提供了一个脚本 ```download_cyclegan_data.py``` 方便下载CycleGAN相关的 +数据集。执行如下命令可以下载相关的数据集，目前支持的数据集名称有：apple2orange, summer2winter_yosemite,horse2zebra, monet2photo, cezanne2photo, ukiyoe2photo, vangogh2photo, maps, cityscapes, facades, iphone2dslr_flower, ae_photos, cityscapes。 + +执行如下命令，可以下载对应的数据集到 ```~/.cache/ppgan``` 并软连接到 ```PaddleGAN/data/``` 下。 +``` +python data/download_cyclegan_data.py --name horse2zebra +``` +#### 使用自己的数据集 +如果你使用自己的数据集，需要构造成如下目录的格式。注意 ```xxxA```，```xxxB```文件数量，文件内容无需一一对应。 +``` +custom_datasets +├── testA +├── testB +├── trainA +└── trainB +``` + +### Pix2Pix相关的数据集下载 + +#### 已有的数据集下载 + +##### 从网页下载 pixel2pixel模型相关的数据集可以在[这里](hhttps://people.eecs.berkeley.edu/~tinghuiz/projects/pix2pix/datasets/)下载 + +##### 使用脚本下载 +我们在 ```PaddleGAN/data``` 文件夹下提供了一个脚本 ```download_pix2pix_data.py``` 方便下载pix2pix模型相关的数据集。执行如下命令可以下载相关的数据集，目前支持的数据集名称有：apple2orange, summer2winter_yosemite,horse2zebra, monet2photo, cezanne2photo, ukiyoe2photo, vangogh2photo, maps, cityscapes, facades, iphone2dslr_flower, ae_photos, cityscapes。 + +执行如下命令，可以下载对应的数据集到 ```~/.cache/ppgan``` 并软连接到 ```PaddleGAN/data/``` 下。 +``` +python data/download_pix2pix_data.py --name cityscapes +``` + +#### 使用自己的数据集 +如果你使用自己的数据集，需要构造成如下目录的格式。同时图片应该制作成下图的样式，即左边为一种风格，另一边为相应转换的风格。 + +``` +facades +├── test +├── train +└── val +``` + +![](./imgs/1.jpg) diff --git a/docs/data_prepare_en.md b/docs/data_prepare_en.md index 6c25aa214c4e4d79178546866e952bc1f7ccc97f..c4652846e6b1f16ed6df39740e6d01b29763ccc8 100644 --- a/docs/data_prepare_en.md +++ b/docs/data_prepare_en.md @@ -1,6 +1,6 @@ ## data prepare -It is recommended to symlink the dataset root to `$PaddleGAN/data`. +The config will suppose your data put in `$PaddleGAN/data`. You can symlink your datasets to `$PaddleGAN/data`. ``` PaddleGAN @@ -28,8 +28,65 @@ PaddleGAN ``` -### cyclegan datasets -more dataset for cyclegan you can download from [here](https://people.eecs.berkeley.edu/~taesung_park/CycleGAN/datasets/) +if you put your datasets on other place，for example ```your/data/path```, +you can also change ```dataroot``` in config file: -### pix2pix datasets -more dataset for pix2pix you can download from [here](hhttps://people.eecs.berkeley.edu/~tinghuiz/projects/pix2pix/datasets/) +``` +dataset: + train: + name: PairedDataset + dataroot: your/data/path + num_workers: 4 +``` + +### Datasets of CycleGAN + +#### download existed datasets + +##### download form website +datasets for CycleGAN you can download from [here](https://people.eecs.berkeley.edu/~taesung_park/CycleGAN/datasets/) + +##### download by script +You can use ```download_cyclegan_data.py``` in ```PaddleGAN/data``` to download datasets you wanted. Supported datasets are: apple2orange, summer2winter_yosemite,horse2zebra, monet2photo, cezanne2photo, ukiyoe2photo, vangogh2photo, maps, cityscapes, facades, iphone2dslr_flower, ae_photos, cityscapes。 + +run following command. Dataset will be downloaded to ```~/.cache/ppgan``` and symlink to ```PaddleGAN/data/``` . +``` +python data/download_cyclegan_data.py --name horse2zebra +``` + +#### custom dataset +Data should be arranged in following way if you use custom dataset. +``` +custom_datasets +├── testA +├── testB +├── trainA +└── trainB +``` + +### Datasets of Pix2Pix + +#### download existed datasets + +##### download from website +dataset for pix2pix you can download from [here](hhttps://people.eecs.berkeley.edu/~tinghuiz/projects/pix2pix/datasets/) + +##### download by script +You can use ```download_pix2pix_data.py``` in ```PaddleGAN/data``` to download datasets you wanted. Supported datasets are: apple2orange, summer2winter_yosemite,horse2zebra, monet2photo, cezanne2photo, ukiyoe2photo, vangogh2photo, maps, cityscapes, facades, iphone2dslr_flower, ae_photos, cityscapes. + +run following command. Dataset will be downloaded to ```~/.cache/ppgan``` and symlink to ```PaddleGAN/data/``` . +``` +python data/download_pix2pix_data.py --name cityscapes +``` + +#### custom datasets +Data should be arranged in following way if you use custom dataset. And image content shoubld be same with example image. + +``` +facades +├── test +├── train +└── val +``` + +![](./imgs/1.jpg) diff --git a/docs/get_started.md b/docs/get_started.md index a584d9c033298509b2ffc120dc852f138eb65e8b..66926828c2d44b109a68d386cfd448dbd148b9c6 100644 --- a/docs/get_started.md +++ b/docs/get_started.md @@ -1,22 +1,71 @@ ## 快速开始使用PaddleGAN +注意： +* 开始使用PaddleGAN前请确保已经阅读过[安装文档](./install.md)，并根据[数据准备文档](./data_prepare.md)准备好数据集。 +* 以下教程以CycleGAN模型在Cityscapes数据集上的训练预测作为示例。 + + ### 训练 + +#### 单卡训练 ``` python -u tools/main.py --config-file configs/cyclegan_cityscapes.yaml ``` +#### 参数 -continue train from last checkpoint +- `--config-file (str)`: 配置文件的路径。 + + 输出的日志，权重，可视化结果会默认保存在```./output_dir```中，可以通过配置文件中的```output_dir```参数修改： + ``` + output_dir: output_dir + ``` + + 保存的文件夹会根据模型名字和时间戳自动生成一个新目录，目录示例如下： +``` +output_dir +└── CycleGANModel-2020-10-29-09-21 + ├── epoch_1_checkpoint.pkl + ├── log.txt + └── visual_train + ├── epoch001_fake_A.png + ├── epoch001_fake_B.png + ├── epoch001_idt_A.png + ├── epoch001_idt_B.png + ├── epoch001_real_A.png + ├── epoch001_real_B.png + ├── epoch001_rec_A.png + ├── epoch001_rec_B.png + ├── epoch002_fake_A.png + ├── epoch002_fake_B.png + ├── epoch002_idt_A.png + ├── epoch002_idt_B.png + ├── epoch002_real_A.png + ├── epoch002_real_B.png + ├── epoch002_rec_A.png + └── epoch002_rec_B.png +``` + +#### 恢复训练 + +训练过程中默认会保存上一个epoch的checkpoint，方便恢复训练 ``` python -u tools/main.py --config-file configs/cyclegan_cityscapes.yaml --resume your_checkpoint_path ``` +#### 参数 -multiple gpus train: +- `--resume (str)`: 用来恢复训练的checkpoint路径。 + +#### 多卡训练: ``` -CUDA_VISIBLE_DEVICES=0,1 python -m paddle.distributed.launch tools/main.py --config-file configs/pix2pix_cityscapes.yaml +CUDA_VISIBLE_DEVICES=0,1 python -m paddle.distributed.launch tools/main.py --config-file configs/cyclegan_cityscapes.yaml ``` ### 预测 ``` python tools/main.py --config-file configs/cyclegan_cityscapes.yaml --evaluate-only --load your_weight_path ``` + +#### 参数 +- `--evaluate-only`: 是否仅进行预测。 +- `--load (str)`: 训练好的权重路径。 diff --git a/docs/get_started_en.md b/docs/get_started_en.md index 024e8dec2bfac2afc51d472fa8617c0db82986fe..474a8fd295ddcde50e9f7a191348e89d24b47d47 100644 --- a/docs/get_started_en.md +++ b/docs/get_started_en.md @@ -1,22 +1,71 @@ ## Getting started with PaddleGAN +Note: +* Before starting to use PaddleGAN, please make sure you have read the [install document](./install_en.md), and prepare the dataset according to the [data preparation document](./data_prepare_en.md) +* The following tutorial uses the train and evaluate of the CycleGAN model on the Cityscapes dataset as an example + ### Train + +#### Train with single gpu ``` python -u tools/main.py --config-file configs/cyclegan_cityscapes.yaml ``` +#### Args + +- `--config-file (str)`: path of config file。 + +The output log, weight, and visualization result will be saved in ```./output_dir``` by default, which can be modified by the ```output_dir``` parameter in the config file: + ``` + output_dir: output_dir + ``` + + -continue train from last checkpoint +The saved folder will automatically generate a new directory based on the model name and timestamp. The directory example is as follows: +``` +output_dir +└── CycleGANModel-2020-10-29-09-21 + ├── epoch_1_checkpoint.pkl + ├── log.txt + └── visual_train + ├── epoch001_fake_A.png + ├── epoch001_fake_B.png + ├── epoch001_idt_A.png + ├── epoch001_idt_B.png + ├── epoch001_real_A.png + ├── epoch001_real_B.png + ├── epoch001_rec_A.png + ├── epoch001_rec_B.png + ├── epoch002_fake_A.png + ├── epoch002_fake_B.png + ├── epoch002_idt_A.png + ├── epoch002_idt_B.png + ├── epoch002_real_A.png + ├── epoch002_real_B.png + ├── epoch002_rec_A.png + └── epoch002_rec_B.png +``` +#### Recovery of training + +The checkpoint of the previous epoch will be saved by default during the training process to facilitate the recovery of training ``` python -u tools/main.py --config-file configs/cyclegan_cityscapes.yaml --resume your_checkpoint_path ``` +#### Args -multiple gpus train: +- `--resume (str)`: path of checkpoint。 + +#### Train with multiple gpus: ``` -CUDA_VISIBLE_DEVICES=0,1 python -m paddle.distributed.launch tools/main.py --config-file configs/pix2pix_cityscapes.yaml +CUDA_VISIBLE_DEVICES=0,1 python -m paddle.distributed.launch tools/main.py --config-file configs/cyclegan_cityscapes.yaml ``` -### Evaluate +### evaluate ``` python tools/main.py --config-file configs/cyclegan_cityscapes.yaml --evaluate-only --load your_weight_path ``` + +#### Args +- `--evaluate-only`: whether to evaluate only。 +- `--load (str)`: path of weight。 diff --git a/docs/install.md b/docs/install.md new file mode 100644 index 0000000000000000000000000000000000000000..36a56723deda3b94b4b62b50904691d6121491dc --- /dev/null +++ b/docs/install.md @@ -0,0 +1,36 @@ +## 安装PaddleGAN + +### 要求 + +* PaddlePaddle >= 2.0.0-rc +* Python >= 3.5+ +* CUDA >= 9.0 + +### 1. 安装PaddlePaddle +``` +pip install -U paddlepaddle-gpu==2.0.0rc0 +``` + +上面命令会默认安装cuda10.2的包，如果想安装其他cuda版本的包，可以参考下面的表格。 +
CUDA python3.8python3.7python3.6
10.1
install 
python -m pip install https://paddle-wheel.bj.bcebos.com/2.0.0-rc0-gpu-cuda10.1-cudnn7-mkl_gcc8.2%2Fpaddlepaddle_gpu-2.0.0rc0.post101-cp38-cp38-linux_x86_64.whl
+
install 
python -m pip install https://paddle-wheel.bj.bcebos.com/2.0.0-rc0-gpu-cuda10.1-cudnn7-mkl_gcc8.2%2Fpaddlepaddle_gpu-2.0.0rc0.post101-cp37-cp37m-linux_x86_64.whl
+
install 
python -m pip install https://paddle-wheel.bj.bcebos.com/2.0.0-rc0-gpu-cuda10.1-cudnn7-mkl_gcc8.2%2Fpaddlepaddle_gpu-2.0.0rc0.post101-cp36-cp36m-linux_x86_64.whl
+
10.0
install 
python -m pip install https://paddle-wheel.bj.bcebos.com/2.0.0-rc0-gpu-cuda10-cudnn7-mkl%2Fpaddlepaddle_gpu-2.0.0rc0.post100-cp38-cp38-linux_x86_64.whl
+
install 
python -m pip install https://paddle-wheel.bj.bcebos.com/2.0.0-rc0-gpu-cuda10-cudnn7-mkl%2Fpaddlepaddle_gpu-2.0.0rc0.post100-cp37-cp37m-linux_x86_64.whl
+
install 
python -m pip install https://paddle-wheel.bj.bcebos.com/2.0.0-rc0-gpu-cuda10-cudnn7-mkl%2Fpaddlepaddle_gpu-2.0.0rc0.post100-cp36-cp36m-linux_x86_64.whl
+
9.0
install 
python -m pip install https://paddle-wheel.bj.bcebos.com/2.0.0-rc0-gpu-cuda9-cudnn7-mkl%2Fpaddlepaddle_gpu-2.0.0rc0.post90-cp38-cp38-linux_x86_64.whl
+
install 
python -m pip install https://paddle-wheel.bj.bcebos.com/2.0.0-rc0-gpu-cuda9-cudnn7-mkl%2Fpaddlepaddle_gpu-2.0.0rc0.post90-cp37-cp37m-linux_x86_64.whl
+
install 
python -m pip install https://paddle-wheel.bj.bcebos.com/2.0.0-rc0-gpu-cuda9-cudnn7-mkl%2Fpaddlepaddle_gpu-2.0.0rc0.post90-cp36-cp36m-linux_x86_64.whl
+
+ + +### 2. 安装ppgan + +``` +git clone https://github.com/PaddlePaddle/PaddleGAN +cd PaddleGAN + +pip install -v -e . # or "python setup.py develop" +``` + +按照上述方法安装成功后，本地的修改也会自动同步到ppgan中 diff --git a/docs/install_en.md b/docs/install_en.md new file mode 100644 index 0000000000000000000000000000000000000000..07d3818004b8232b5f59e020d2475e55c1289184 --- /dev/null +++ b/docs/install_en.md @@ -0,0 +1,35 @@ +## Install PaddleGAN + +### requirements + +* PaddlePaddle >= 2.0.0-rc +* Python >= 3.5+ +* CUDA >= 9.0 + +### 1. Install PaddlePaddle +``` +pip install -U paddlepaddle-gpu==2.0.0rc0 +``` + +Note: command above will install paddle with cuda10.2，if your installed cuda is different, you can choose an proper version to install from table below. + +
CUDA python3.8python3.7python3.6
10.1
install 
python -m pip install https://paddle-wheel.bj.bcebos.com/2.0.0-rc0-gpu-cuda10.1-cudnn7-mkl_gcc8.2%2Fpaddlepaddle_gpu-2.0.0rc0.post101-cp38-cp38-linux_x86_64.whl
+
install 
python -m pip install https://paddle-wheel.bj.bcebos.com/2.0.0-rc0-gpu-cuda10.1-cudnn7-mkl_gcc8.2%2Fpaddlepaddle_gpu-2.0.0rc0.post101-cp37-cp37m-linux_x86_64.whl
+
install 
python -m pip install https://paddle-wheel.bj.bcebos.com/2.0.0-rc0-gpu-cuda10.1-cudnn7-mkl_gcc8.2%2Fpaddlepaddle_gpu-2.0.0rc0.post101-cp36-cp36m-linux_x86_64.whl
+
10.0
install 
python -m pip install https://paddle-wheel.bj.bcebos.com/2.0.0-rc0-gpu-cuda10-cudnn7-mkl%2Fpaddlepaddle_gpu-2.0.0rc0.post100-cp38-cp38-linux_x86_64.whl
+
install 
python -m pip install https://paddle-wheel.bj.bcebos.com/2.0.0-rc0-gpu-cuda10-cudnn7-mkl%2Fpaddlepaddle_gpu-2.0.0rc0.post100-cp37-cp37m-linux_x86_64.whl
+
install 
python -m pip install https://paddle-wheel.bj.bcebos.com/2.0.0-rc0-gpu-cuda10-cudnn7-mkl%2Fpaddlepaddle_gpu-2.0.0rc0.post100-cp36-cp36m-linux_x86_64.whl
+
9.0
install 
python -m pip install https://paddle-wheel.bj.bcebos.com/2.0.0-rc0-gpu-cuda9-cudnn7-mkl%2Fpaddlepaddle_gpu-2.0.0rc0.post90-cp38-cp38-linux_x86_64.whl
+
install 
python -m pip install https://paddle-wheel.bj.bcebos.com/2.0.0-rc0-gpu-cuda9-cudnn7-mkl%2Fpaddlepaddle_gpu-2.0.0rc0.post90-cp37-cp37m-linux_x86_64.whl
+
install 
python -m pip install https://paddle-wheel.bj.bcebos.com/2.0.0-rc0-gpu-cuda9-cudnn7-mkl%2Fpaddlepaddle_gpu-2.0.0rc0.post90-cp36-cp36m-linux_x86_64.whl
+
+ + +### 2. Install ppgan + +``` +git clone https://github.com/PaddlePaddle/PaddleGAN +cd PaddleGAN + +pip install -v -e . # or "python setup.py develop" +``` diff --git a/docs/tutorials/video_restore.md b/docs/tutorials/video_restore.md index ec999e594fb2f35d87133bc5ee77a42774f7dcbe..523e5cfaf9313f1374bf8c25bc5ec3bb09d070db 100644 --- a/docs/tutorials/video_restore.md +++ b/docs/tutorials/video_restore.md @@ -39,7 +39,7 @@ DAIN 模型通过探索深度的信息来显式检测遮挡。并且开发了一 ``` ppgan.apps.DAINPredictor( - output_path='output', + output='output', weight_path=None, time_step=None, use_gpu=True, @@ -47,7 +47,7 @@ ppgan.apps.DAINPredictor( ``` #### 参数 -- `output_path (str，可选的)`: 输出的文件夹路径，默认值：`output`. +- `output (str，可选的)`: 输出的文件夹路径，默认值：`output`. - `weight_path (None，可选的)`: 载入的权重路径，如果没有设置，则从云端下载默认的权重到本地。默认值：`None`。 - `time_step (int)`: 补帧的时间系数，如果设置为0.5，则原先为每秒30帧的视频，补帧后变为每秒60帧。 - `remove_duplicates (bool，可选的)`: 是否删除重复帧，默认值：`False`. @@ -61,7 +61,7 @@ ppgan.apps.DeOldifyPredictor(output='output', weight_path=None, render_factor=32 ``` #### 参数 -- `output_path (str，可选的)`: 输出的文件夹路径，默认值：`output`. +- `output (str，可选的)`: 输出的文件夹路径，默认值：`output`. - `weight_path (None，可选的)`: 载入的权重路径，如果没有设置，则从云端下载默认的权重到本地。默认值：`None`。 - `render_factor (int)`: 会将该参数乘以16后作为输入帧的resize的值，如果该值设置为32， 则输入帧会resize到(32 * 16, 32 * 16)的尺寸再输入到网络中。 @@ -80,7 +80,7 @@ ppgan.apps.DeepRemasterPredictor( ``` #### 参数 -- `output_path (str，可选的)`: 输出的文件夹路径，默认值：`output`. +- `output (str，可选的)`: 输出的文件夹路径，默认值：`output`. - `weight_path (None，可选的)`: 载入的权重路径，如果没有设置，则从云端下载默认的权重到本地。默认值：`None`。 - `colorization (bool)`: 是否对输入视频上色，如果选项设置为 `True` ，则参考帧的文件夹路径也必须要设置。默认值：`False`。 - `reference_dir (bool)`: 参考帧的文件夹路径。默认值：`None`。 @@ -96,7 +96,7 @@ ppgan.apps.RealSRPredictor(output='output', weight_path=None) ``` #### 参数 -- `output_path (str，可选的)`: 输出的文件夹路径，默认值：`output`. +- `output (str，可选的)`: 输出的文件夹路径，默认值：`output`. - `weight_path (None，可选的)`: 载入的权重路径，如果没有设置，则从云端下载默认的权重到本地。默认值：`None`。 - ### 超分辨率模型EDVRPredictor @@ -111,5 +111,5 @@ ppgan.apps.EDVRPredictor(output='output', weight_path=None) ``` #### 参数 -- `output_path (str，可选的)`: 输出的文件夹路径，默认值：`output`. +- `output (str，可选的)`: 输出的文件夹路径，默认值：`output`. - `weight_path (None，可选的)`: 载入的权重路径，如果没有设置，则从云端下载默认的权重到本地。默认值：`None`。 diff --git a/ppgan/apps/dain_predictor.py b/ppgan/apps/dain_predictor.py index e148b15a27b8be6fa9c9eba20d9150f981b4f90e..2e4b83d0e9a44c6c71f631077da9910c7a050a07 100644 --- a/ppgan/apps/dain_predictor.py +++ b/ppgan/apps/dain_predictor.py @@ -22,7 +22,7 @@ from imageio import imread, imsave import paddle import paddle.fluid as fluid -from paddle.utils.download import get_path_from_url +from ppgan.utils.download import get_path_from_url from ppgan.utils.video import video2frames, frames2video from .base_predictor import BasePredictor @@ -39,8 +39,7 @@ class DAINPredictor(BasePredictor): remove_duplicates=False): self.output_path = os.path.join(output, 'DAIN') if weight_path is None: - cur_path = os.path.abspath(os.path.dirname(__file__)) - weight_path = get_path_from_url(DAIN_WEIGHT_URL, cur_path) + weight_path = get_path_from_url(DAIN_WEIGHT_URL) self.weight_path = weight_path self.time_step = time_step diff --git a/ppgan/apps/deepremaster_predictor.py b/ppgan/apps/deepremaster_predictor.py index 2a8f555b93212fc9a23c9fb37806e5e168dbd8a7..5a578030480733c3ba88b2bc4ba2b0a3349cd3a4 100644 --- a/ppgan/apps/deepremaster_predictor.py +++ b/ppgan/apps/deepremaster_predictor.py @@ -22,7 +22,7 @@ from skimage import color import paddle from ppgan.models.generators.remaster import NetworkR, NetworkC -from paddle.utils.download import get_path_from_url +from ppgan.utils.download import get_path_from_url from .base_predictor import BasePredictor DEEPREMASTER_WEIGHT_URL = 'https://paddlegan.bj.bcebos.com/applications/deep_remaster.pdparams' @@ -77,9 +77,7 @@ class DeepRemasterPredictor(BasePredictor): self.mindim = mindim if weight_path is None: - cur_path = os.path.abspath(os.path.dirname(__file__)) - weight_path = get_path_from_url(DEEPREMASTER_WEIGHT_URL, cur_path) - print(weight_path) + weight_path = get_path_from_url(DEEPREMASTER_WEIGHT_URL) self.weight_path = weight_path diff --git a/ppgan/apps/deoldify_predictor.py b/ppgan/apps/deoldify_predictor.py index b3ca4613bc38f216f321c79c1f768a82668edd4f..c1bab4068630cc6d61a927ef431911c4f447c3d2 100644 --- a/ppgan/apps/deoldify_predictor.py +++ b/ppgan/apps/deoldify_predictor.py @@ -20,7 +20,7 @@ from PIL import Image from tqdm import tqdm import paddle -from paddle.utils.download import get_path_from_url +from ppgan.utils.download import get_path_from_url from ppgan.utils.video import frames2video, video2frames from ppgan.models.generators.deoldify import build_model @@ -36,8 +36,7 @@ class DeOldifyPredictor(BasePredictor): self.render_factor = render_factor self.model = build_model() if weight_path is None: - cur_path = os.path.abspath(os.path.dirname(__file__)) - weight_path = get_path_from_url(DEOLDIFY_WEIGHT_URL, cur_path) + weight_path = get_path_from_url(DEOLDIFY_WEIGHT_URL) state_dict = paddle.load(weight_path) self.model.load_dict(state_dict) diff --git a/ppgan/apps/edvr_predictor.py b/ppgan/apps/edvr_predictor.py index 0e9fe71db450e9a37bc3293bd0a9f196071f9213..695ca41829712dc6160a160e92542cc92de7e6a7 100644 --- a/ppgan/apps/edvr_predictor.py +++ b/ppgan/apps/edvr_predictor.py @@ -19,7 +19,7 @@ import glob import numpy as np from tqdm import tqdm -from paddle.utils.download import get_path_from_url +from ppgan.utils.download import get_path_from_url from ppgan.utils.video import frames2video, video2frames from .base_predictor import BasePredictor @@ -138,8 +138,7 @@ class EDVRPredictor(BasePredictor): self.output = os.path.join(output, 'EDVR') if weight_path is None: - cur_path = os.path.abspath(os.path.dirname(__file__)) - weight_path = get_path_from_url(EDVR_WEIGHT_URL, cur_path) + weight_path = get_path_from_url(EDVR_WEIGHT_URL) self.weight_path = weight_path diff --git a/ppgan/apps/first_order_predictor.py b/ppgan/apps/first_order_predictor.py index b83d456ee1e85fe1b51a30bbe89bb5d9ba43492a..c0f6dded049076c4946496259d1bafa4028e2bdb 100644 --- a/ppgan/apps/first_order_predictor.py +++ b/ppgan/apps/first_order_predictor.py @@ -25,7 +25,7 @@ from skimage.transform import resize from scipy.spatial import ConvexHull import paddle -from paddle.utils.download import get_path_from_url +from ppgan.utils.download import get_path_from_url from ppgan.utils.animate import normalize_kp from ppgan.modules.keypoint_detector import KPDetector from ppgan.models.generators.occlusion_aware import OcclusionAwareGenerator @@ -78,8 +78,7 @@ class FirstOrderPredictor(BasePredictor): } if weight_path is None: vox_cpk_weight_url = 'https://paddlegan.bj.bcebos.com/applications/first_order_model/vox-cpk.pdparams' - cur_path = os.path.abspath(os.path.dirname(__file__)) - weight_path = get_path_from_url(vox_cpk_weight_url, cur_path) + weight_path = get_path_from_url(vox_cpk_weight_url) self.weight_path = weight_path self.output = output diff --git a/ppgan/apps/realsr_predictor.py b/ppgan/apps/realsr_predictor.py index e7bd32b44fb4c5764100abdcdf43985d6ef55813..58f3b61537cff92c994fe3bfb13affef0e911915 100644 --- a/ppgan/apps/realsr_predictor.py +++ b/ppgan/apps/realsr_predictor.py @@ -22,7 +22,7 @@ from tqdm import tqdm import paddle from ppgan.models.generators import RRDBNet from ppgan.utils.video import frames2video, video2frames -from paddle.utils.download import get_path_from_url +from ppgan.utils.download import get_path_from_url from .base_predictor import BasePredictor REALSR_WEIGHT_URL = 'https://paddlegan.bj.bcebos.com/applications/DF2K_JPEG.pdparams' @@ -34,8 +34,7 @@ class RealSRPredictor(BasePredictor): self.output = os.path.join(output, 'RealSR') self.model = RRDBNet(3, 3, 64, 23) if weight_path is None: - cur_path = os.path.abspath(os.path.dirname(__file__)) - weight_path = get_path_from_url(REALSR_WEIGHT_URL, cur_path) + weight_path = get_path_from_url(REALSR_WEIGHT_URL) state_dict = paddle.load(weight_path) self.model.load_dict(state_dict) diff --git a/ppgan/utils/download.py b/ppgan/utils/download.py new file mode 100644 index 0000000000000000000000000000000000000000..49e1d061a4c76b409bc2afe4e11e9c0d5da2db10 --- /dev/null +++ b/ppgan/utils/download.py @@ -0,0 +1,254 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from __future__ import absolute_import +from __future__ import division +from __future__ import print_function + +import os +import sys +import os.path as osp +import shutil +import requests +import hashlib +import tarfile +import zipfile +import time +from tqdm import tqdm +import logging + +from .logger import get_logger + +logger = get_logger('ppgan') + +PPGAN_HOME = os.path.expanduser("~/.cache/ppgan/") + +DOWNLOAD_RETRY_LIMIT = 3 + + +def is_url(path): + """ + Whether path is URL. + Args: + path (string): URL string or not. + """ + return path.startswith('http://') or path.startswith('https://') + + +def _map_path(url, root_dir): + # parse path after download under root_dir + fname = osp.split(url)[-1] + fpath = fname + return osp.join(root_dir, fpath) + + +def get_path_from_url(url, md5sum=None, check_exist=True): + """ Download from given url to root_dir. + if file or directory specified by url is exists under + root_dir, return the path directly, otherwise download + from url and decompress it, return the path. + + Args: + url (str): download url + md5sum (str): md5 sum of download package + + Returns: + str: a local path to save downloaded models & weights & datasets. + """ + + from paddle.fluid.dygraph.parallel import ParallelEnv + + assert is_url(url), "downloading from {} not a url".format(url) + root_dir = PPGAN_HOME + # parse path after download to decompress under root_dir + fullpath = _map_path(url, root_dir) + + if osp.exists(fullpath) and check_exist and _md5check(fullpath, md5sum): + logger.info("Found {}".format(fullpath)) + else: + if ParallelEnv().local_rank == 0: + fullpath = _download(url, root_dir, md5sum) + else: + while not os.path.exists(fullpath): + time.sleep(1) + + if ParallelEnv().local_rank == 0: + if tarfile.is_tarfile(fullpath) or zipfile.is_zipfile(fullpath): + fullpath = _decompress(fullpath) + + return fullpath + + +def _download(url, path, md5sum=None): + """ + Download from url, save to path. + + url (str): download url + path (str): download to given path + """ + if not osp.exists(path): + os.makedirs(path) + + fname = osp.split(url)[-1] + fullname = osp.join(path, fname) + retry_cnt = 0 + + while not (osp.exists(fullname) and _md5check(fullname, md5sum)): + if retry_cnt < DOWNLOAD_RETRY_LIMIT: + retry_cnt += 1 + else: + raise RuntimeError("Download from {} failed. " + "Retry limit reached".format(url)) + + logger.info("Downloading {} from {}".format(fname, url)) + + req = requests.get(url, stream=True) + if req.status_code != 200: + raise RuntimeError("Downloading from {} failed with code " + "{}!".format(url, req.status_code)) + + # For protecting download interupted, download to + # tmp_fullname firstly, move tmp_fullname to fullname + # after download finished + tmp_fullname = fullname + "_tmp" + total_size = req.headers.get('content-length') + with open(tmp_fullname, 'wb') as f: + if total_size: + with tqdm(total=(int(total_size) + 1023) // 1024) as pbar: + for chunk in req.iter_content(chunk_size=1024): + f.write(chunk) + pbar.update(1) + else: + for chunk in req.iter_content(chunk_size=1024): + if chunk: + f.write(chunk) + shutil.move(tmp_fullname, fullname) + return fullname + + +def _md5check(fullname, md5sum=None): + if md5sum is None: + return True + + logger.info("File {} md5 checking...".format(fullname)) + md5 = hashlib.md5() + with open(fullname, 'rb') as f: + for chunk in iter(lambda: f.read(4096), b""): + md5.update(chunk) + calc_md5sum = md5.hexdigest() + + if calc_md5sum != md5sum: + logger.info("File {} md5 check failed, {}(calc) != " + "{}(base)".format(fullname, calc_md5sum, md5sum)) + return False + return True + + +def _decompress(fname): + """ + Decompress for zip and tar file + """ + logger.info("Decompressing {}...".format(fname)) + + # For protecting decompressing interupted, + # decompress to fpath_tmp directory firstly, if decompress + # successed, move decompress files to fpath and delete + # fpath_tmp and remove download compress file. + + if tarfile.is_tarfile(fname): + uncompressed_path = _uncompress_file_tar(fname) + elif zipfile.is_zipfile(fname): + uncompressed_path = _uncompress_file_zip(fname) + else: + raise TypeError("Unsupport compress file type {}".format(fname)) + + return uncompressed_path + + +def _uncompress_file_zip(filepath): + files = zipfile.ZipFile(filepath, 'r') + file_list = files.namelist() + + file_dir = os.path.dirname(filepath) + + if _is_a_single_file(file_list): + rootpath = file_list[0] + uncompressed_path = os.path.join(file_dir, rootpath) + + for item in file_list: + files.extract(item, file_dir) + + elif _is_a_single_dir(file_list): + rootpath = os.path.splitext(file_list[0])[0].strip(os.sep).split( + os.sep)[-1] + uncompressed_path = os.path.join(file_dir, rootpath) + + for item in file_list: + files.extract(item, file_dir) + + else: + rootpath = os.path.splitext(filepath)[0].split(os.sep)[-1] + uncompressed_path = os.path.join(file_dir, rootpath) + if not os.path.exists(uncompressed_path): + os.makedirs(uncompressed_path) + for item in file_list: + files.extract(item, os.path.join(file_dir, rootpath)) + + files.close() + + return uncompressed_path + + +def _uncompress_file_tar(filepath, mode="r:*"): + files = tarfile.open(filepath, mode) + file_list = files.getnames() + + file_dir = os.path.dirname(filepath) + + if _is_a_single_file(file_list): + rootpath = file_list[0] + uncompressed_path = os.path.join(file_dir, rootpath) + for item in file_list: + files.extract(item, file_dir) + elif _is_a_single_dir(file_list): + rootpath = os.path.splitext(file_list[0])[0].split(os.sep)[-1] + uncompressed_path = os.path.join(file_dir, rootpath) + for item in file_list: + files.extract(item, file_dir) + else: + rootpath = os.path.splitext(filepath)[0].split(os.sep)[-1] + uncompressed_path = os.path.join(file_dir, rootpath) + if not os.path.exists(uncompressed_path): + os.makedirs(uncompressed_path) + + for item in file_list: + files.extract(item, os.path.join(file_dir, rootpath)) + + files.close() + + return uncompressed_path + + +def _is_a_single_file(file_list): + if len(file_list) == 1 and file_list[0].find(os.sep) < -1: + return True + return False + + +def _is_a_single_dir(file_list): + file_name = file_list[0].split(os.sep)[0] + for i in range(1, len(file_list)): + if file_name != file_list[i].split(os.sep)[0]: + return False + return True diff --git a/ppgan/utils/logger.py b/ppgan/utils/logger.py index fed2acbac7f64137cd31a1b46a6f97a1b1f12599..b7585231286c90c3bac5ffa1018c233d7594f032 100644 --- a/ppgan/utils/logger.py +++ b/ppgan/utils/logger.py @@ -18,6 +18,8 @@ import sys from paddle.distributed import ParallelEnv +logger_initialized = {} + def setup_logger(output=None, name="ppgan"): """ @@ -67,3 +69,11 @@ def setup_logger(output=None, name="ppgan"): logger.addHandler(fh) return logger + + +def get_logger(name, output=None): + logger = logging.getLogger(name) + if name in logger_initialized: + return logger + + return setup_logger(name=name, output=name) diff --git a/script/pix2pix_download.sh b/script/pix2pix_download.sh deleted file mode 100644 index d3cc8ce9244ce9644aa25e2841b3d42bf5395f4e..0000000000000000000000000000000000000000 --- a/script/pix2pix_download.sh +++ /dev/null @@ -1,9 +0,0 @@ -FILE=$1 -URL=https://people.eecs.berkeley.edu/~tinghuiz/projects/pix2pix/datasets/$FILE.tar.gz -TAR_FILE=./$FILE.tar.gz -TARGET_DIR=./$FILE/ -wget -N $URL -O $TAR_FILE --no-check-certificate -mkdir $TARGET_DIR -tar -zxvf $TAR_FILE -C ../data/ -rm $TAR_FILE -rm -rf $TARGET_DIR