Giseop Kim gisbi-kim

Using a lambda (or any function) in a loop can be considered a code smell in Python (and often in other languages like C++) for several reasons. Here's why it can be problematic:

1. Closure Binding Issue:

In Python, using a lambda function in a loop can lead to unexpected behavior due to late binding. This means the lambda function captures the variable, not the value. So, if the lambda uses loop variables, it will use the final value of the variable, not the value it had when the function was defined.

funcs = [lambda x: x + i for i in range(3)]
for func in funcs:

	"""
	stable diffusion dreaming
	creates hypnotic moving videos by smoothly walking randomly through the sample space

	example way to run this script:

	$ python stablediffusionwalk.py --prompt "blueberry spaghetti" --name blueberry

	to stitch together the images, e.g.:
	$ ffmpeg -r 10 -f image2 -s 512x512 -i blueberry/frame%06d.jpg -vcodec libx264 -crf 10 -pix_fmt yuv420p blueberry.mp4

	import numpy as np
	import matplotlib.pyplot as plt
	import open3d as o3d
	from pytictoc import TicToc # pip install pytictoc

	# start
	t = TicToc()
	t.tic()

	# option

	import sys
	import os
	import numpy as np
	import open3d as o3d
	from utils import *

	# params
	num_pnvlad_points = 4096

	# dataset setting

	import os
	import sys
	import time
	import copy
	import numpy as np
	import open3d as o3d

	#
	parent_dir = 'ScanNet/scans'
	seq_dir_names = os.listdir(parent_dir)

	%% Understanding how a constrastive loss works

	% constrastive loss refs:
	% - Kihyuk Sohn. Improved deep metric learning with multi- class n-pair loss objective. In Advances in Neural Informa- tion Processing Systems (NeurIPS), 2016.
	% - Aaron van den Oord, Yazhe Li, and Oriol Vinyals. Repre- sentation learning with contrastive predictive coding. arXiv preprint arXiv:1807.03748, 2018.
	% - Zaiwei Zhang et al. Self-Supervised Pretraining of 3D Features on any Point-Cloud, 2021

	%% param
	num_negs = 100;

	https://www.arxiv.org/list/cs.RO/pastweek?skip=0&show=2000

	https://www.arxiv.org/list/cs.CV/pastweek?skip=0&show=2000

	/*
	purpose: voxeldownsampling in pcl sometimes fails for a large-scale point cloud
	*/

	void octreeDownsampling(const pcl::PointCloud<PointType>::Ptr &_src,
	pcl::PointCloud<PointType>::Ptr &_to_save,
	const float _kDownsampleVoxelSize)
	{
	pcl::octree::OctreePointCloudVoxelCentroid<PointType> octree(_kDownsampleVoxelSize);
	octree.setInputCloud(_src);

	function [files] = listdir(dir_path)

	files = dir(dir_path);
	files(1:2) = []; % remove . and ..
	files = {files(:).name};

	end