Comments (11)
@leopku I also encountered the same problem, do you use
readImg.ResizeArea(image.Size{Height:224, Width:224})
?Yes.
Thank you, it helped me a lot.
Thanks also to the author
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You need to add the batch dimension to the input tensor, in order to correctly feed the model with a (1, 573,860,3) shaped tensor
You can use tg.Batchify more or less in this way (code not tested I'm not able to run it right now, I'm sorry)
img := tg.Batchify(scope, []tf.Output{image.Read(scope, "/tmp/test.jpeg", 3)})
from tfgo.
@galeone Big Thanks.
This time error was panic: Can not squeeze dim[1], expected a dimension of 1, got 44
core code
img := tg.Batchify(scope, []tf.Output{image.Read(scope, "/tmp/a72.jpg", 3).Value()})
input := tg.Exec(scope, []tf.Output{img}, nil, &tf.SessionOptions{})
results := model.Exec(
[]tf.Output{model.Op("StatefulPartitionedCall", 0)},
map[tf.Output]*tf.Tensor{model.Op("serving_default_input", 0): input[0]},
)
log.Debug().Interface("results", results[0].Value()).Msg("")
from tfgo.
I don't know from where the 44 came from - is it an input dimension?
Can you show me the shape of img
after the batchify call?
from tfgo.
The shape was [1, ?, ?, 3]
.
Maybe 44 came from input dimension.
I wrote the input dimension into a file. Now I'm analyzing it.
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Finally fixed by comparing codes between which using tensorflow official go package.
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Out of curiosity - can you show me how you fixed it?
from tfgo.
Out of curiosity - can you show me how you fixed it?
I forgot to resize the image 😭 . Resizing the image before batchify can fix it.
This tfgo
library is so cool. I really like it.
Finally, thank you for your reply and this amazing library.
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Thank you for the kind words!! 😃
from tfgo.
@leopku I also encountered the same problem, do you use readImg.ResizeArea(image.Size{Height:224, Width:224})
?
from tfgo.
@leopku I also encountered the same problem, do you use
readImg.ResizeArea(image.Size{Height:224, Width:224})
?
Yes.
from tfgo.
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