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百度AI攻略:Paddlehub实现图像生成

运维开发网 https://www.qedev.com 2020-01-21 15:08 出处:网络 作者:才能我浪费
PaddleHub可以便捷地获取PaddlePaddle生态下的预训练模型,完成模型的管理和一键预测。配合使用Fine-tune API,可以基于大规模预训练模型快速完成迁移学习,让预训练模型能更好地服务于用户特定场景的应用。模型概述CycleGAN是生成对抗网络(Generative Adversarial Networks )的一种,与传统的GAN只能单向生成图片不同,CycleGAN可以同时

PaddleHub可以便捷地获取PaddlePaddle生态下的预训练模型,完成模型的管理和一键预测。配合使用Fine-tune API,可以基于大规模预训练模型快速完成迁移学习,让预训练模型能更好地服务于用户特定场景的应用。

模型概述

CycleGAN是生成对抗网络(Generative Adversarial Networks )的一种,与传统的GAN只能单向生成图片不同,CycleGAN可以同时完成两个domain的图片进行相互转换。该PaddleHub Module使用Cityscapes数据集训练完成,支持图片从实景图转换为语义分割结果,也支持从语义分割结果转换为实景图。

代码及效果示例:

import paddlehub as hub

import matplotlib.pyplot as plt

import matplotlib.image as mpimg

cyclegan = hub.Module(name="cyclegan_cityscapes")

test_img_path = "./body2.jpg"

# 预测结果展示

img = mpimg.imread(test_img_path)

plt.imshow(img)

plt.axis('off')

plt.show()

# set input dict

input_dict = {"image": [test_img_path]}

# execute predict and print the result

results = cyclegan.generate(data=input_dict)

for result in results:

    print(result)

test_img_path = "./cyclegan_output/body2.jpg"

img = mpimg.imread(test_img_path)

plt.imshow(img)

plt.axis('off')

plt.show()

[2020-01-06 08:47:55,320] [    INFO] - Installing cyclegan_cityscapes module

2020-01-06 08:47:55,320-INFO: Installing cyclegan_cityscapes module

[2020-01-06 08:47:55,353] [    INFO] - Module cyclegan_cityscapes already installed in /home/aistudio/.paddlehub/modules/cyclegan_cityscapes

2020-01-06 08:47:55,353-INFO: Module cyclegan_cityscapes already installed in /home/aistudio/.paddlehub/modules/cyclegan_cityscapes

百度AI攻略:Paddlehub实现图像生成

[2020-01-06 08:47:55,728] [    INFO] - 234 pretrained paramaters loaded by PaddleHub

2020-01-06 08:47:55,728-INFO: 234 pretrained paramaters loaded by PaddleHub

File ./body2.jpg is processed successfully and the result is saved to the cyclegan_output/body2.jpg

百度AI攻略:Paddlehub实现图像生成

In[8]

cyclegan = hub.Module(name="cyclegan_cityscapes")

test_img_path = "./cbd1.jpg"

# 预测结果展示

img = mpimg.imread(test_img_path)

plt.imshow(img)

plt.axis('off')

plt.show()

# set input dict

input_dict = {"image": [test_img_path]}

# execute predict and print the result

results = cyclegan.generate(data=input_dict)

for result in results:

    print(result)

test_img_path = "./cyclegan_output/cbd1.jpg"

img = mpimg.imread(test_img_path)

plt.imshow(img)

plt.axis('off')

plt.show()

[2020-01-06 08:49:16,726] [    INFO] - Installing cyclegan_cityscapes module

2020-01-06 08:49:16,726-INFO: Installing cyclegan_cityscapes module

[2020-01-06 08:49:16,746] [    INFO] - Module cyclegan_cityscapes already installed in /home/aistudio/.paddlehub/modules/cyclegan_cityscapes

2020-01-06 08:49:16,746-INFO: Module cyclegan_cityscapes already installed in /home/aistudio/.paddlehub/modules/cyclegan_cityscapes

百度AI攻略:Paddlehub实现图像生成

[2020-01-06 08:49:17,164] [    INFO] - 234 pretrained paramaters loaded by PaddleHub

2020-01-06 08:49:17,164-INFO: 234 pretrained paramaters loaded by PaddleHub

File ./cbd1.jpg is processed successfully and the result is saved to the cyclegan_output/cbd1.jpg

百度AI攻略:Paddlehub实现图像生成

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