https://github.com/mxagar/pyimagesearch_tutorials
This repository contains code from some of the tutorials at PyImageSearch.
https://github.com/mxagar/pyimagesearch_tutorials
computer-vision deep-learning image-classification image-processing object-detection ocr
Last synced: about 1 year ago
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This repository contains code from some of the tutorials at PyImageSearch.
- Host: GitHub
- URL: https://github.com/mxagar/pyimagesearch_tutorials
- Owner: mxagar
- License: other
- Created: 2023-04-17T14:48:57.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2023-08-09T08:52:07.000Z (almost 3 years ago)
- Last Synced: 2025-02-15T12:49:49.178Z (over 1 year ago)
- Topics: computer-vision, deep-learning, image-classification, image-processing, object-detection, ocr
- Language: Jupyter Notebook
- Homepage:
- Size: 4.71 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
Awesome Lists containing this project
README
# PyImageSearch Tutorials
This repository contains code from some of the tutorials at [PyImageSearch](https://pyimagesearch.com/), as well as from other sources, properly referenced.
## Tutorials and Examples
Each tutorial has a dedicated folder with the code and a `README.md`.
In addition to these tutorials, I have the following repositories with related content:
- [deep_learning_udacity](https://github.com/mxagar/deep_learning_udacity)
- [computer_vision_udacity](https://github.com/mxagar/computer_vision_udacity)
- [deep-learning-v2-pytorch](https://github.com/mxagar/deep-learning-v2-pytorch)
- [detection_segmentation_pytorch](https://github.com/mxagar/detection_segmentation_pytorch)
- [ocr_guide](https://github.com/mxagar/ocr_guide)
- [hyperparameter-optimization](https://github.com/mxagar/hyperparameter-optimization)
### Siamese Networks
Folder: [`siamese_networks/`](./siamese_networks/).
- Building Image Pairs for Siamese Networks
- Implementing Your First Siamese Network with Keras and TensorFlow
- Comparing Images for Similarity with Siamese Networks
- Improving Accuracy with Contrastive Loss
- Face Recognition with Siamese Networks, Keras, and TensorFlow
- Building a Dataset for Triplet Loss with Keras and TensorFlow
- Triplet Loss with Keras and TensorFlow
- Training and Making Predictions with Siamese Networks and Triplet Loss
### NeRFs
:construction:
TBD.
- Computer Graphics and Deep Learning with NeRF using TensorFlow and Keras: Part 1
- Computer Graphics and Deep Learning with NeRF using TensorFlow and Keras: Part 2
- Computer Graphics and Deep Learning with NeRF using TensorFlow and Keras: Part 3
### Data Pipelines
:construction:
TBD.
- A Gentle Introduction to tf.data with TensorFlow
- Data Pipelines with tf.data and TensorFlow
- Data Augmentation with tf.data and TensorFlow
### Hyperparameter Tuning
:construction:
TBD.
- Introduction to Hyperparameter Tuning
- Hyperparameter Tuning for Computer Vision Projects
- Using scikit-learn to Tune Deep Learning Model Hyperparameters
- Easy Hyperparameter Tuning with Keras Tuner
### Vision Fusion
:construction:
TBD.
- Welcome to the Visual Fusion Mini-Course
- What to Expect From This Course
- Understanding Cameras
- Understanding LiDARs
- Review of the 2 Sensors
- Introduction to Sensor Fusion
- Point Pixel Projection
- Projecting a LiDAR Point (3D) to an Image (2D)
- Applying the Magic Formula
- Using Google Colab
- 3D-2D Visualization and Code
- Coding the Magic Formula
### OAK
:construction:
TBD.
- Introduction to OAK (OpenCV AI Kit)
- OAK-D: Understanding and Running Neural Network Inference with DepthAI API
- Training a Custom Image Classification Network for OAK-D
- Deploying a Custom Image Classifier on an OAK-D
- Training the YOLOv8 Object Detector for OAK-D - Part 1
- Training the YOLOv8 Object Detector for OAK-D - Part 2
- Training the YOLOv8 Object Detector for OAK-D - Part 3
- Training the YOLOv8 Object Detector for OAK-D - Part 4
- Training the YOLOv8 Object Detector for OAK-D - Part 5
- Training the YOLOv8 Object Detector for OAK-D - Part 6
- Training the YOLOv8 Object Detector for OAK-D - Part 7
- Training the YOLOv8 Object Detector for OAK-D - Part 8
- Hand Gesture Recognition with YOLOv8 on OAK-D in Near Real-Time - Part 1
- Hand Gesture Recognition with YOLOv8 on OAK-D in Near Real-Time - Part 2
- Hand Gesture Recognition with YOLOv8 on OAK-D in Near Real-Time - Part 3
- Hand Gesture Recognition with YOLOv8 on OAK-D in Near Real-Time - Part 4
- Hand Gesture Recognition with YOLOv8 on OAK-D in Near Real-Time - Part 5
- Hand Gesture Recognition with YOLOv8 on OAK-D in Near Real-Time - Part 6
- Hand Gesture Recognition with YOLOv8 on OAK-D in Near Real-Time - Part 7
- Hand Gesture Recognition with YOLOv8 on OAK-D in Near Real-Time - Part 8
- Hand Gesture Recognition with YOLOv8 on OAK-D in Near Real-Time - Part 9
- Hand Gesture Recognition with YOLOv8 on OAK-D in Near Real-Time - Part 10
### Hugging Face
:construction:
TBD.
- Train a MaskFormer Segmentation Model with Hugging Face Transformers
### OpenCV Tools
:construction:
TBD.
### Augmented Reality - Fiducial Tracking
:construction:
TBD.
## Authorship, License
Most of the original code was created by Adrian Rosebrock et al. and is hosted at [PyImageSearch](https://pyimagesearch.com/).
I (Mikel Sagardia) modified some files to the present state.
For more information on the allowed usage, check the [LICENSE.md](LICENSE.md).