Search Results for "map it" - Page 4
Sort By:
Showing 211 open source projects for "map it"
View related business solutions-
Veeam Data Platform v13.1Try Veeam Data Platform today. Experience the unified platform that's secure by design, portable by default, and proven to recover clean, fast, and anywhere.
-
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
1
Earth Enterprise
Google Earth Enterprise - Open Source
...Unlike Google Maps or Google Earth, Earth Enterprise does not include Google’s proprietary imagery but instead provides the tools needed to manage and visualize private geospatial datasets. The system is composed of three main components: Fusion, which processes and integrates imagery, vector, and terrain data into unified map layers; Server, which hosts the resulting globes or maps via Apache or Tornado-based web servers; and Client, which includes the Google Earth Enterprise Client (EC) for 3D visualization and the Google Maps JavaScript API V3 for 2D viewing. Designed for enterprise, research, and government use, it allows for secure, scalable deployment of geospatial visualization systems within private infrastructure. -
2
Multi-Agent path planning in Python
Python implementation of a bunch of multi-robot path-planning
multi_agent_path_planning is a Python-based implementation of multi-agent pathfinding algorithms for coordinating multiple agents in shared environments without collisions. It is useful in robotics, warehouse automation, and gaming AI. -
3
DensePose
A real-time approach for mapping all human pixels of 2D RGB images
...DensePose is widely used in augmented reality, motion capture, virtual try-on, and visual effects applications because it enables real-time 3D human mapping from 2D inputs. The model architecture builds on Mask R-CNN, using additional regression heads to predict UV coordinates that map image pixels to 3D surfaces. -
4
earthengine-py-notebooks
A collection of 360+ Jupyter Python notebook examples
...These notebooks are organized into thematic areas such as image processing, machine learning, visualization, filtering, and asset management, exposing users to real geospatial analysis tasks. The repository makes it easier to explore Earth Engine’s large geospatial data catalog, interactively display map layers, and generate visual insights without the need for external GIS software by leveraging interactive widgets and mapping libraries. Many of the notebooks integrate with tools like folium, ipyleaflet, and geemap to bridge Earth Engine data with Python’s rich ecosystem for plotting and analysis. Users can quickly adapt the examples for their own remote sensing, environmental monitoring, or spatial data science projects, and can run the code in environments like Google Colab. -
Paessler: Easy to Use With Enterprise Power. Free TrialYou shouldn't have to choose between a monitoring tool that's easy to use and one that's powerful enough for a complex environment. PRTG's low-code interface lets any admin build dashboards, set alerts and monitor devices without scripting, while custom sensors and full API access are there when your team needs deeper control. One platform, no compromise. Download a free 30-day trial now.
-
5
parent-map
Analyze parental contributions to evolved or engineered protein or DNA
Documentation: https://parent-map.readthedocs.io/ -
6
joy2key
Steer in GTBikeV with any unsupported joystick
Map joystick buttons to keyboard keys, to steer in GTBikeV with any (unsupported) joystick. Uses Python Windows joystick API and sample code from How to generate keyboard events in Python? If your joystick has an analog stick you may prefer using x360ce for steering. You can still use joy2key to enable/disable auto drive and change radio station, just leave buttons 3 and 4 unmapped in x360ce. -
7
GPlates
Interactive visualization of plate tectonics.
GPlates is a plate-tectonics program. Manipulate reconstructions of geological and paleo-geographic features through geological time. Interactively visualize vector, raster and volume data. PyGPlates is the GPlates Python library. Get fine-grained access to GPlates functionality in your Python scripts. -
8
VideoPose3D
Efficient 3D human pose estimation in video using 2D keypoint
VideoPose3D is a deep learning framework that reconstructs 3D human poses from 2D keypoint sequences extracted from videos. It builds on top of convolutional and temporal networks that map 2D joint coordinates over time to consistent 3D skeletons, enabling robust motion capture without specialized sensors. The model is trained on large motion capture datasets and can generalize well to unseen environments by leveraging temporal context for smoothing and error correction. By using only 2D detections (such as those from OpenPose or Detectron), it enables markerless 3D pose estimation with relatively lightweight computational requirements. ... -
9
GluonNLP
NLP made easy
GluonNLP is a toolkit that helps you solve NLP problems. It provides easy-to-use tools that helps you load the text data, process the text data, and train models. To facilitate both the engineers and researchers, we provide command-line-toolkits for downloading and processing the NLP datasets. Gluon NLP makes it easy to evaluate and train word embeddings. Here are examples to evaluate the pre-trained embeddings included in the Gluon NLP toolkit as well as example scripts for training... -
99.99% Uptime for MySQL and PostgreSQL DatabasesCloud SQL Enterprise Plus delivers near-zero downtime with 35 days of point-in-time recovery. Supports MySQL, PostgreSQL, and SQL Server.
-
10
SageMaker Containers
Create SageMaker-compatible Docker containers
Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. A container provides an effectively isolated environment, ensuring a consistent runtime and reliable training process. The SageMaker Training Toolkit can be easily added to... -
11
Hénon map browser
Program for exploring the Hénon attractor
A Python program for exploring the Hénon attractor. For an explanation of what the Hénon attractor is please see Wikipedia (http://en.wikipedia.org/wiki/H%C3%A9non_map). With this program you can draw the Hénon attractor and interact with it in various ways. You can zoom in by selecting an area, vary the Henon parameters manually and even make animations with them. The functionality is demonstrated in a Youtube video. There is a help function included that explains in more detail how to use... -
12
imgaug
Image augmentation for machine learning experiments
...Affine transformations, perspective transformations, contrast changes, gaussian noise, dropout of regions, hue/saturation changes, cropping/padding, blurring, etc. Rotate image and segmentation map on it by the same value sampled. Convert keypoints to distance maps, extract pixels within bounding boxes from images, clip polygon to the image plane, etc. Scale segmentation maps, average/max pool of images/maps, pad images to aspect ratios (e.g. to square them). Draw heatmaps, segmentation maps, keypoints, bounding boxes, etc. -
13
YouTube-8M
Starter code for working with the YouTube-8M dataset
...The code demonstrates how to process frame-level features, train logistic and deep learning models, evaluate them using metrics like global Average Precision (gAP) and mean Average Precision (mAP), and export trained models for MediaPipe inference. -
14
Zabbix-in-Telegram
Zabbix Notifications with graphs in Telegram
Zabbix Notifications with graphs in Telegram. -
15
GeoNotebook
A Jupyter notebook extension for geospatial visualization and analysis
...It supports workflows that include map reprojection, layer interaction, and tile serving, which are essential for real world geoscience and environmental analysis. -
16
data-science-ipython-notebooks
Data science Python notebooks: Deep learning
Data Science IPython Notebooks is a broad, curated set of Jupyter notebooks covering Python, data wrangling, visualization, machine learning, deep learning, and big data tools. It aims to be a practical map of the ecosystem, showing hands-on examples with libraries such as NumPy, pandas, matplotlib, scikit-learn, and others. Many notebooks introduce concepts step by step, then apply them to real datasets so readers can see techniques in action. Advanced sections touch on neural networks and distributed computing topics, helping you bridge from basics to production-adjacent workflows. ... -
17
Game Programmer
A Study Path for Game Programmer
...The project is useful for self-taught developers who need a long-term curriculum and a way to identify gaps in their knowledge. Its main value is organizing a complex discipline into a visual, staged study map. -
18
twitchslam
A toy implementation of monocular SLAM written while livestreaming
twitchslam is a small educational implementation of monocular simultaneous localization and mapping created during a livestream. It processes ordinary video while estimating camera motion and building a map of observed 3D points. Frames contain extracted visual features, while map points retain their 2D correspondences across frames. OpenCV handles feature extraction, SDL2 provides a 2D view, and Pangolin renders the reconstructed map in 3D. The project includes pose optimization, projection-based point recovery, a kinematic model, and map loading and saving. ... -
19
mAP
Evaluates the performance of your neural net for object recognition
In practice, a higher mAP value indicates a better performance of your neural net, given your ground truth and set of classes. The performance of your neural net will be judged using the mAP criteria defined in the PASCAL VOC 2012 competition. We simply adapted the official Matlab code into Python (in our tests they both give the same results). First, your neural net detection-results are sorted by decreasing confidence and are assigned to ground-truth objects. -
20
Twitter Intelligence
Twitter Intelligence OSINT project performs tracking and analysis
...Tweet data is stored on the Tweet, User, Location, Hashtag, HashtagTweet tables. The database is created automatically. analysis.py performs analysis processing. User, hashtag, and location analyzes are performed. You must write Google Map API Key in setting.py to display Google Maps. -
21
SSD Keras
A Keras port of single shot MultiBox detector
...Ports of the trained weights of all the original models are provided below. This implementation is accurate, meaning that both the ported weights and models trained from scratch produce the same mAP values as the respective models of the original Caffe implementation. The main goal of this project is to create an SSD implementation that is well documented for those who are interested in a low-level understanding of the model. The provided tutorials, documentation and detailed comments hopefully make it a bit easier to dig into the code and adapt or build upon the model than with most other implementations out there (Keras or otherwise) that provide little to no documentation and comments. ... -
22
iTelliHashCSV
Cryptographic Hashing Application for CSV Files
...Additionally, if such datasets are subsequently modified or enhanced through value-added services or products provided by other organizations or individuals and then returned, the data owner retains the ability to “re-map” the hashed sensitive data values back to their original values. -
23
iTelliHashExcel
Cryptographic Hashing Application for Excel Files
...Additionally, if such datasets are subsequently modified or enhanced through value-added services or products provided by other organizations or individuals and then returned, the data owner retains the ability to “re-map” the hashed sensitive data values back to their original values. -
24
DeepLearn
Implementation of research papers on Deep Learning+ NLP+ CV in Python
Welcome to DeepLearn. This repository contains an implementation of the following research papers on NLP, CV, ML, and deep learning. The required dependencies are mentioned in requirement.txt. I will also use dl-text modules for preparing the datasets. If you haven't use it, please do have a quick look at it. CV, transfer learning, representation learning. -
25
Siamese and triplet learning
Siamese and triplet networks with online triplet mining in PyTorch
Siamese and triplet learning is a PyTorch implementation of Siamese and triplet neural network architectures designed for learning embedding representations in machine learning tasks. These types of networks learn to map images into a compact feature space where the distance between vectors reflects the similarity between inputs. Such embeddings are commonly used in applications like face recognition, image similarity search, and few-shot learning. The repository demonstrates how to train these models using contrastive loss and triplet loss functions, which encourage embeddings of similar samples to be close while pushing dissimilar samples farther apart. ...
