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21 search results found

Automatically visualize your pandas dataframe via a single print! 📊 💡

Fastpages ⭐ 3,435

An easy to use blogging platform, with enhanced support for Jupyter Notebooks.

Fastdup ⭐ 1,313

fastdup is a powerful free tool designed to rapidly extract valuable insights from your image & video datasets. Assisting you to increase your dataset images & labels quality and reduce your data operations costs at an unparalleled scale.

Yet Another Compiler Visualizer

Langstats ⭐ 53

A visual color bar of the programming languages in your directory, with percentages and labels

TVM Relay IR Visualization Tool (TVM 可视化工具)

Python toolkit for GEOS-Chem. Contains basic plotting scripts, plus the suite of GEOS-Chem benchmarking utilities.

GenoVi, an automated customizable circular genome visualizer for bacteria and archaea

Dearbagplayer ⭐ 34

DearBagPlayer is a flexible rosbag player based on Dear PyGui in Python.

The official PyTorch implementation - Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective (CVPR'22).

Pyteltools ⭐ 27

Python Telemac Tools for post-processing tasks (includes a workflow)

Robot Log Visualizer ⭐ 19

Visualizer to display the data logged with YarpRobotLoggerDevice

Cnn Raccoon ⭐ 19

Create interactive dashboards for your Convolutional Neural Networks with a single line of code!

Visualbim ⭐ 12

Docvisor ⭐ 11

An open-source tool for visualisation of outputs of deep-learning models for document analysis tasks such as fully automatic, bounding box and OCR.

Network Visualizer ⭐ 10

Visualize your network connections!

Smallsets ⭐ 10

Visual documentation for data preprocessing in R and Python

Routing Visualization ⭐ 8

Routing Visualization for Physical Design

Videocomparisontool ⭐ 8

Zoom in, video comparsion, topdown flash, vertial flash

Dynamic Shap Plots ⭐ 5

Enabling interactive plotting of the visualizations from the SHAP project.

This library is designed to generate visualizations of neural networks by analyzing PyTorch code. Unlike conventional methods, our approach eliminates the need for large parameter files (pth) or specific input formats. With minimal AI knowledge, users can leverage this tool to create visualizations that aid in understanding complex networks.

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