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72 lines
2.5 KiB
Markdown
72 lines
2.5 KiB
Markdown
English | [简体中文](README_CN.md)
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# AnimeGAN Python Deployment Example
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Two steps before deployment
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- 1. Software and hardware should meet the requirements. Please refer to [FastDeploy Environment Requirements](../../../../../docs/en/build_and_install/download_prebuilt_libraries.md)
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- 2. Install FastDeploy Python whl package. Refer to [FastDeploy Python Installation](../../../../../docs/en/build_and_install/download_prebuilt_libraries.md)
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This directory provides examples that `infer.py` fast finishes the deployment of AnimeGAN on CPU/GPU and GPU accelerated by TensorRT. The script is as follows
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```bash
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# Download the example code for deployment
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git clone https://github.com/PaddlePaddle/FastDeploy.git
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cd FastDeploy/examples/vision/generation/anemigan/python
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# Download prepared test images
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wget https://bj.bcebos.com/paddlehub/fastdeploy/style_transfer_testimg.jpg
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# CPU inference
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python infer.py --model animegan_v1_hayao_60 --image style_transfer_testimg.jpg --device cpu
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# GPU inference
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python infer.py --model animegan_v1_hayao_60 --image style_transfer_testimg.jpg --device gpu
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```
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## AnimeGAN Python Interface
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```python
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fd.vision.generation.AnimeGAN(model_file, params_file, runtime_option=None, model_format=ModelFormat.PADDLE)
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```
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AnimeGAN model loading and initialization, among which model_file and params_file are the model file and parameter file for Paddle inference.
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**Parameter**
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> * **model_file**(str): Model file path
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> * **params_file**(str): Parameter file path
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> * **runtime_option**(RuntimeOption): Backend inference configuration. None by default, which is the default configuration
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> * **model_format**(ModelFormat): Model format. PADDLE format by default
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### predict function
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> ```python
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> AnimeGAN.predict(input_image)
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> ```
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> Model prediction interface. Input images and output style transfer results.
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> **Parameter**
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> > * **input_image**(np.ndarray): Input data in HWC or BGR format
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> **Return** np.ndarray, the image after style transfer in BGR format
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### batch_predict function
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> ```python
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> AnimeGAN.batch_predict function (input_images)
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> ```
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> Model prediction interface. Input a set of images and output style transfer results
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>
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> **Parameter**
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>
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> > * **input_images**(list(np.ndarray)): Input data in HWC or BGR format
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> **Return** list(np.ndarray), a set of images after style transfer in BGR format
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## Other Documents
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- [Style Transfer Model Description](..)
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- [C++ Deployment](../cpp)
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- [How to switch the model inference backend engine](../../../../../docs/en/faq/how_to_change_backend.md)
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