├── LICENSE ├── README.md └── tutorials └── 001_Artificial_Neural_Network_with_Python.ipynb /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2023 Florent Poux 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # 3D-Deep-Learning 2 | 3D Deep Learning Tutorials 3 | 4 | # 3D Deep Learning Repository 5 | 6 | ![3D Deep Learning Logo](https://learngeodata.eu/wp-content/uploads/2023/02/INTRO_IMAGE-1-1536x1026.png) 7 | 8 | Welcome to the **3D Deep Learning** repository! This repository aims to provide a comprehensive set of tutorials on 3D deep learning using Python. Whether you're a beginner or an experienced practitioner, this resource will guide you through the fundamentals and advanced concepts of 3D deep learning. 9 | 10 | ## Table of Contents 11 | 12 | 1. [Introduction to 3D Deep Learning](#introduction) 13 | 2. [Getting Started](#getting-started) 14 | 3. [Installation](#installation) 15 | 4. [Tutorials](#tutorials) 16 | - [Tutorial 1: Understanding 3D Data](#tutorial-1) 17 | - [Tutorial 2: Preprocessing 3D Data](#tutorial-2) 18 | - [Tutorial 3: Building 3D Convolutional Neural Networks](#tutorial-3) 19 | - [Tutorial 4: Transfer Learning for 3D Deep Learning](#tutorial-4) 20 | - [Tutorial 5: Evaluating 3D Deep Learning Models](#tutorial-5) 21 | - [Tutorial 6: Deploying 3D Models in Applications](#tutorial-6) 22 | 5. [Examples](#examples) 23 | 6. [Contributing](#contributing) 24 | 7. [License](#license) 25 | 26 | ## Introduction 27 | 28 | Deep learning in 3D space has gained significant traction in various fields, including geospatial mapping, medical imaging, computer vision, robotics, autonomous driving, and more. This repository serves as a code learning hub for understanding and implementing 3D deep learning techniques using Python. 29 | 30 | ## Getting Started 31 | 32 | Before diving into the tutorials, make sure you have the necessary tools and libraries installed. Please refer to the [Installation](#installation) section for detailed instructions. 33 | 34 | ## Installation 35 | 36 | To get started with 3D Deep Learning, you'll need to set up your environment. Each code package is grounded with an how-to guide accessible on my [Medium Page](https://medium.com/@florentpoux). You then have a section dedicated to the local setup. 37 | It usually involves this: 38 | 39 | ```bash 40 | # Clone the repository 41 | git clone https://github.com/username/3d-deep-learning.git 42 | 43 | # Navigate to the project directory 44 | cd 3d-deep-learning 45 | 46 | # Install miniconda with Python version 3.10 47 | 48 | # Create a virtual environment (optional but recommended) 49 | conda create -n DEEPTUTO python=3.10 50 | 51 | # Activate the virtual environment 52 | conda acti 53 | 54 | # Install dependencies using requirements (if set-up) 55 | pip install -r requirements.txt 56 | 57 | #Install dependencies using the given libraries in the Medium Article 58 | pip install numpy matplotlib laspy keras 59 | ``` 60 | 61 | ## Tutorials 62 | 63 | ### Tutorial 1: Understanding Artificial Neural Networks 64 | 65 | In this tutorial, we cover the basics of working with Artificial Neural Networks to pursue our quest toward 3D Deep Learning 66 | 67 | For starting the tutorial, please refer to the [tutorials](tutorials/) directory, and chose the relevant one 68 | 69 | ### Tutorial 1: Understanding 3D Data 70 | 71 | In this tutorial, we'll cover the basics of working with 3D data, including formats, visualization, and common preprocessing techniques. 72 | 73 | Coming soon. 74 | 75 | ### Tutorial 2: Preprocessing 3D Data 76 | 77 | Learn about essential preprocessing steps for preparing 3D data for deep learning models. This includes data augmentation, normalization, and more. 78 | 79 | Coming soon. 80 | 81 | ### Tutorial 3: Building 3D Convolutional Neural Networks 82 | 83 | Discover how to construct 3D CNN architectures for tasks such as classification, segmentation, and detection. 84 | 85 | Coming soon. 86 | 87 | ### Tutorial 4: Transfer Learning for 3D Deep Learning 88 | 89 | Explore techniques to leverage pre-trained 3D models and adapt them for your specific tasks. 90 | 91 | Coming soon. 92 | 93 | ### Tutorial 5: Evaluating 3D Deep Learning Models 94 | 95 | Learn how to assess the performance of your 3D deep learning models using various metrics and visualization tools. 96 | 97 | Coming soon. 98 | 99 | ### Tutorial 6: Deploying 3D Models in Applications 100 | 101 | Understand the process of deploying 3D deep learning models in real-world applications, including considerations for hardware and software requirements. 102 | 103 | Coming soon. 104 | 105 | ## Contributing 106 | 107 | I welcome contributions! If you have an idea for a new tutorial or want to improve existing content, please refer to the [contributing guidelines](CONTRIBUTING.md). 108 | 109 | ## License 110 | 111 | This repository is licensed under the [MIT License](LICENSE). 112 | 113 | --- 114 | 115 | Feel free to reach out with any questions, feedback, or suggestions. Happy learning! 🚀 116 | --------------------------------------------------------------------------------