Ramana Sundararaman

Normal consistency based closest point

1

Hello Mike @mikedh , I would like to align two meshes that are close in Euclidean space. For this, I'm using `trimesh.proximity.closest_point`. In my alignment problem, I would like to...

Hi, A lot of codebase seem to use `np.float` which was deprecated in numpy 1.20 and removed in 1.24. Therefore, importing menpo3d raises error. An update would be much appreciated....

`average_onto_vertices` only accepts 3-dim input

2

Hi, As far as I understand, this function: https://libigl.github.io/libigl-python-bindings/igl_docs/#average_onto_vertices would be performing a matrix (incidence with voronoi weight?) vector multiplication. I don't understand why it's restricted to 3-dim input? It's...

Hello, I think it would be really useful to have unique_edge_map and cotmatrix_entries ordered in the same manner. I agree that the explanation provided in the documentation is accurate, but...

Unable to use meshplot on VSCode and Python 3.9

2

Hello, As the title says, I'm unable to plot on a notebook using VSCode alongside Python 3.9. Specifically, I get the error(s) attached below.  When I click on the...

Should the placeholder `all_images` be of `float32` type?

3

Hi, I tried to run the code with imagenet dataset and I land into this following error ``` TypeError: Expected int32 passed to parameter 'y' of op 'Minimum', got 50.0...

Support for searching recursively

1

Suppose my codebase is of this structure, it'd be nice to recursively run the script for all the .py files. - src/ - driver.py - DB/ - DBHelper.py - Analyze/...

Hi, I just wanted to ensure that the mean subtraction in the Convolution Autoencoder's test images are correct. [Here](https://github.com/pkmital/tensorflow_tutorials/blob/master/python/09_convolutional_autoencoder.py#L157 ) the mean of the train image is being subtracted from...

`np.ndarray` vs `list` discrepancy

1

Hi, I'm facing a discrepancy between `np.ndarray` and python `list`. here's a reproducible code. ``` (Pdb) munkres_inst.compute(cost_matrix) *** ValueError: non-broadcastable output operand with shape (1,) doesn't match the broadcast shape...

Custom transform support

1

This PR aims to change the `FasterRCNN` class to accept custom Transformations from the user, foregoing the generic `GeneralizedRCNNTransform` as the compulsory transform. Addresses #2263 Edit : I couldn't test...