kimoktm / u-net Goto Github PK
View Code? Open in Web Editor NEWU-net segmentation network in Tensorflow
U-net segmentation network in Tensorflow
Hello I am trying to use unet on a custom data set of labels that have the standard 3 RGB channels. My question is how would I configure the mask for each image given that there are three different classifications I want?
Hi! I'm new at this. Can somebody help me how to import my data images in dataset_to_tfrecords?
I can only get training dataset of 1 channel from the internet,so where can I find the color dataset with RGB channels?
It will be very kind if someone can share the color dataset!
You've done great job!
But I face so many troubles with training the model, could you please provide link (Google Disk for example) to your model (it could be not fully trainedl).
I just want to look at the model structure, to figure out, if it fits my needs :)
Thank you for your work!
def deconv_upsample(inputs, factor, name, padding = 'SAME', activation_fn = None):
"""
Convolution Transpose upsampling layer with bilinear interpolation weights:
ISSUE: problems with odd scaling factors
----------
Args:
inputs: Tensor, [batch_size, height, width, channels]
factor: Integer, upsampling factor
name: String, scope name
padding: String, input padding
activation_fn: Tensor fn, activation function on output (can be None)
Returns:
outputs: Tensor, [batch_size, height * factor, width * factor, num_filters_in]
"""
with tf.variable_scope(name):
stride_shape = [1, factor, factor, 1]
input_shape = tf.shape(inputs)# [1,14,14,1024]
num_filters_in = inputs.get_shape()[-1].value
output_shape = tf.stack([input_shape[0], input_shape[1] * factor, input_shape[2] * factor, num_filters_in])# [ 1 28 28 1024]
weights = bilinear_upsample_weights(factor, num_filters_in)# [ 4 4 1024 1024]
outputs = tf.nn.conv2d_transpose(inputs, weights, output_shape, stride_shape, padding = padding)#shape=(?,?,?,?)!!!
if activation_fn is not None:
outputs = activation_fn(outputs)
return outputs
ValueError: Shape of a new variable (conv6_1/weights) must be fully defined, but instead was (3, 3, ?, 512).
how to resolve it
A declarative, efficient, and flexible JavaScript library for building user interfaces.
๐ Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. ๐๐๐
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google โค๏ธ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.