Giter Club home page Giter Club logo

Comments (10)

jacobunderlinebenseal avatar jacobunderlinebenseal commented on May 16, 2024 3

me too

from spatial-transformer-network.

bit1002lst avatar bit1002lst commented on May 16, 2024

me too, and all of the images in samples are empty

from spatial-transformer-network.

kevinzakka avatar kevinzakka commented on May 16, 2024

Hey guys, I'll take a look at the code when I get the time.

from spatial-transformer-network.

moormoon avatar moormoon commented on May 16, 2024

I have the same issue. Looks like it is related to the initialization of the conv and fc layers. I tried only using fc layers for regression and the training converged. Remember to initialize the weight to zeros and bias to identity.

Haven't figured out how to initialize conv layers yet. If anyone make progress on this please let us know.

from spatial-transformer-network.

BlueWinters avatar BlueWinters commented on May 16, 2024

i think that the bilinear interpolation process in funtion bilinear_sampler is wrong, and a good example of this process can be found in https://github.com/tensorflow/models/tree/master/research/transformer
` # get pixel value at corner coords
Ia = get_pixel_value(img, x0, y0)
Ib = get_pixel_value(img, x0, y1)
Ic = get_pixel_value(img, x1, y0)
Id = get_pixel_value(img, x1, y1)

# recast as float for delta calculation
x0 = tf.cast(x0, 'float32')
x1 = tf.cast(x1, 'float32')
y0 = tf.cast(y0, 'float32')
y1 = tf.cast(y1, 'float32')

# calculate deltas
wa = (x1-x) * (y1-y)
wb = (x1-x) * (y-y0)
wc = (x-x0) * (y1-y)
wd = (x-x0) * (y-y0)

# add dimension for addition
wa = tf.expand_dims(wa, axis=3)
wb = tf.expand_dims(wb, axis=3)
wc = tf.expand_dims(wc, axis=3)
wd = tf.expand_dims(wd, axis=3)

# compute output
out = tf.add_n([wa*Ia, wb*Ib, wc*Ic, wd*Id])`

from spatial-transformer-network.

lifan9880 avatar lifan9880 commented on May 16, 2024

me too

from spatial-transformer-network.

kakashi571 avatar kakashi571 commented on May 16, 2024

how to start the training?

from spatial-transformer-network.

wanziz avatar wanziz commented on May 16, 2024

如何开始培训?

Excuse me,do you know how to train now?

from spatial-transformer-network.

wanziz avatar wanziz commented on May 16, 2024

Excuse me, I would like to know how to start training the model?thank you!

from spatial-transformer-network.

turandai avatar turandai commented on May 16, 2024

I think the problem is the gradients of bilinear sampling can not be auto-generated by tensorflow properly. In the original paper, author defined special gradients during this process, and this package has not included it for now.

from spatial-transformer-network.

Related Issues (20)

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.