tfmatch

tfmatch copied to clipboard

Bumps [tensorflow-gpu](https://github.com/tensorflow/tensorflow) from 1.15.2 to 2.12.0. Release notes Sourced from tensorflow-gpu's releases. TensorFlow 2.12.0 Release 2.12.0 TensorFlow Breaking Changes Build, Compilation and Packaging Removed redundant packages tensorflow-gpu and tf-nightly-gpu. These...

dependabot[bot]

How was the model validated before running on the test sets? I see that you can set `is_training=False` to run on a separate held out set, but this causes multiple...

travisdriver

Nice work first! Is it possible for ASLFeat to train on a custom dataset which only consists of image pairs (without camera.txt or other info)? I find ASLFeat loss calculation...

tangchen2

Hello, does your comparison algorithm use the same training data as ASLFEAT?

reacher-l

Pytorch porting failed

1

Dear @zjhthu @lzx551402, thanks for ur great works and code sharing! I'm struggling to reimplement your TF code into PT version, but failed to get same accuracy/loss. almost all code...

dedoogong

Loss does not decrease

1

Hi,I encountered a problem that the loss did not decrease. Specifically,the loss remains at 0.5 from the 100th iteration to 360,000 iterations and the effect has not improved after training.The...

EstherJinyan

batch_size and the unstable loss

1

@lzx551402 @zjhthu Hi, thanks a lot for your great work. I'v trained aslfeat with circle loss , and when I use tensorboard to see the loss , I found it...

SkySeaWalk

phototourism data not optional?

1

I downloaded the required `GL3D` part of the training set and ran the training for the first time to generate the matches. The dataset preparation fails when trying to access...

christian-rauch

Hi, In contextDesc paper, I saw  in equation(5), the s is softmax(2-D), but the code in line170 of loss.py, list below softmax_row = tf.nn.softmax(log_scale * dist_mat,...

Yvaine

` for i in range(batch_size): if corr_weight is not None: loss += tf.reduce_sum(tot_loss[i][inlier_mask[i]]) / \ (tf.reduce_sum(corr_weight[i][inlier_mask[i]]) + 1e-6) else: loss += tf.reduce_mean(tot_loss[i][inlier_mask[i]]) cnt_err_row = tf.count_nonzero( err_row[i][inlier_mask[i]], dtype=tf.float32) cnt_err_col = tf.count_nonzero(...

Yajiang