Jingbiao's Blog

「Hinc lucem et pocula sacra」

4F12 Revisions

Computer visions

Question 1 Image structures Implementing Gaussian/Low-Pass Filters Fourier transform of the Gaussian is a low pass filter, with the frequency cut-off at $1/\sigma$ Why smoothing is necessary: ...

C++ thread dynamic link issue

For multithreading concurrent program in C++, for example: 1 2 3 4 5 6 7 8 9 10 #include <iostream> #include <thread> void thread_init() { std::cout<<"This statement is executed ...

Cross entropy and KL divergence (relative entropy)

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Gaussian Process with GPML toolbox

Statistical machine learning

\( \require{amstext} \require{amsmath} \require{amssymb} \require{amsfonts} \) Function initialization 1 2 3 meanfunc = @meanZero; % zero mean function covfunc = @covSEiso; % Squared E...

Edge Detections implementation details

Computer visions

1D Edge Detection and the optimizations Simple method: Computing gradient However, with high frequency noises, the gradient could be even more noisier Therefore, Gaussian Smoothing is applie...

ROC Curves and Precision-Recall Curves

Summary ROC Curves summarize the trade-off between the true positive rate and false positve rate for a predictive model using different probability thresholds. Precision-Recall cu...

Threshold Moving - Finding optimal threshold for classification

Introduction Balanced class A class label is being predicted within a classification task. Most of the time, a threshold of 0.5 is used. Larger than 0.5 for one class (1), smaller than 0.5 for ano...

Argparser python usage

import 1 import argparse Initialise argparser 1 parser = argparse.ArgumentParser() Add arguments for the parser 1 2 parser.add_argument('--value', '-v', type=str, default='def', ...

Issue with transformer and Pytorch conflicts

In one project, the transformers package has to be version:transformers==3.5.1, and Pytorch has be >= 1.8.0 - Installing the legacy version may have some conflicts, but anaconda sh...

Issue with python JSONDecodeError

Issues Json loader issue When inputting json file into python with json.loads(_), 1 [json.loads(jline) for jline in open(path, "r").read().split('\n')] line 36 of hm_data.py a like...