Comments (11)
You can reduce the content size and style size in the training process. But I am not sure if it will affect the stylization effect.
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can you test it now? can we communicate?
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can you test it now? can we communicate?
I can't test successfully and i don't know why.
from stytr-2.
can you test it now? can we communicate?
I can't test successfully and i don't know why.
my wechat is c319186779.Can we communicate more?
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Hallo, can you test successfully now? How to slove the error tuple object has no attribute cpu
from stytr-2.
Hallo, can you test successfully now? How to slove the error tuple object has no attribute cpu
for content_path in content_paths:
for style_path in style_paths:
print(content_path)
content_tf1 = content_transform()
content = content_tf(Image.open(content_path).convert("RGB"))
h, w, c = np.shape(content)
style_tf1 = style_transform(h, w)
style = style_tf(Image.open(style_path).convert("RGB"))
style = style.to(device).unsqueeze(0)
content = content.to(device).unsqueeze(0)
with torch.no_grad():
output = network(content, style)
# output = output.cuda()
output = output
output_name = '{:s}/{:s}_stylized_{:s}{:s}'.format(
output_path, splitext(basename(content_path))[0],
splitext(basename(style_path))[0], save_ext
)
save_image(output[0], output_name)
You can copy this code to replace corresponding code on test.py
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Hallo, can you test successfully now? How to slove the error tuple object has no attribute cpu
for content_path in content_paths: for style_path in style_paths: print(content_path)
content_tf1 = content_transform() content = content_tf(Image.open(content_path).convert("RGB")) h, w, c = np.shape(content) style_tf1 = style_transform(h, w) style = style_tf(Image.open(style_path).convert("RGB")) style = style.to(device).unsqueeze(0) content = content.to(device).unsqueeze(0) with torch.no_grad(): output = network(content, style) # output = output.cuda() output = output output_name = '{:s}/{:s}_stylized_{:s}{:s}'.format( output_path, splitext(basename(content_path))[0], splitext(basename(style_path))[0], save_ext ) save_image(output[0], output_name)
You can copy this code to replace corresponding code on test.py
Did you successfully test it?I editted the code as yours but in vain, may you share your environment?
from stytr-2.
Hallo, can you test successfully now? How to slove the error tuple object has no attribute cpu
for content_path in content_paths: for style_path in style_paths: print(content_path)
content_tf1 = content_transform() content = content_tf(Image.open(content_path).convert("RGB")) h, w, c = np.shape(content) style_tf1 = style_transform(h, w) style = style_tf(Image.open(style_path).convert("RGB")) style = style.to(device).unsqueeze(0) content = content.to(device).unsqueeze(0) with torch.no_grad(): output = network(content, style) # output = output.cuda() output = output output_name = '{:s}/{:s}_stylized_{:s}{:s}'.format( output_path, splitext(basename(content_path))[0], splitext(basename(style_path))[0], save_ext ) save_image(output[0], output_name)
You can copy this code to replace corresponding code on test.py
Did you successfully test it?I editted the code as yours but in vain, may you share your environment?
Maybe you can try the following code:
style = style.to(device).unsqueeze(0)
content = content.to(device).unsqueeze(0)
#with torch.no_grad():
# output= network(content,style)
#output = output.cpu()
with torch.no_grad():
output = network(content, style)
output = output[0].cpu()
output_name = '{:s}/{:s}_stylized_{:s}{:s}'.format(
output_path, splitext(basename(content_path))[0],
splitext(basename(style_path))[0], save_ext
)
save_image(output, output_name)
from stytr-2.
Hallo, can you test successfully now? How to slove the error tuple object has no attribute cpu
for content_path in content_paths: for style_path in style_paths: print(content_path)
content_tf1 = content_transform() content = content_tf(Image.open(content_path).convert("RGB")) h, w, c = np.shape(content) style_tf1 = style_transform(h, w) style = style_tf(Image.open(style_path).convert("RGB")) style = style.to(device).unsqueeze(0) content = content.to(device).unsqueeze(0) with torch.no_grad(): output = network(content, style) # output = output.cuda() output = output output_name = '{:s}/{:s}_stylized_{:s}{:s}'.format( output_path, splitext(basename(content_path))[0], splitext(basename(style_path))[0], save_ext ) save_image(output[0], output_name)
You can copy this code to replace corresponding code on test.py
Did you successfully test it?I editted the code as yours but in vain, may you share your environment?
Maybe you can try the following code:
style = style.to(device).unsqueeze(0) content = content.to(device).unsqueeze(0) #with torch.no_grad(): # output= network(content,style) #output = output.cpu() with torch.no_grad(): output = network(content, style) output = output[0].cpu() output_name = '{:s}/{:s}_stylized_{:s}{:s}'.format( output_path, splitext(basename(content_path))[0], splitext(basename(style_path))[0], save_ext ) save_image(output, output_name)
Thank u so much!It works perfectly,and I found a mistake in the version of cuda,the code can only run on the cuda 10.x or lower.
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Have you solved your problem? I tried to run this code in RTX3080 with 10G memory and got "CUDA OUT OF MEMORY". I can only run this code when the batch size is 1. Once the batch size is greater than 1, even if iters is 1, it will report an error.
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Related Issues (20)
- dataset HOT 1
- PatchEmbed源码和论文图中好像操作方法好像不太一样 HOT 4
- 作者您好!对于位置编码有一些疑问
- About the patch partition. HOT 1
- inference parameters
- Arbitrary output size instead of square HOT 3
- Request for elaboration regarding the Dataset HOT 2
- content leak HOT 1
- Error in running "train.py"
- 没有结果生成 HOT 5
- AttributeError: 'tuple' object has no attribute 'cpu' HOT 1
- Hello, thank you for your great work.
- Hi,please help me HOT 4
- About the metric score of StyTr2:Image Style Transfer with Transformers
- 关于代码中构建的transformer的问题
- running train.py get wrong
- 0
- 非常感谢你的论文做出的贡献
- I replace the code with yours, but I got the output as this![result](https://user-images.githubusercontent.com/53261018/186422373-0678c37a-8d2d-45ac-97cd-b772c99f0368.jpg) HOT 2
- Loss weight different values different from the paper
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