Pinned Repositories
awesome-deep-learning
A curated list of awesome Deep Learning tutorials, projects and communities.
darknet
Useful functionalities added on the original darknet public repository.
Deep-Learning-Topics
DeepLearning-VDAO
Here are some of the results of my experiments applying Deep Learning for object detection.
image_dedupe
Object-Detection-Metrics
Most popular metrics used to evaluate object detection algorithms.
Pos-Palmas-Modulo-CSharp
Aulas do módulo de C# do curso de Pós-Graduação em Desenvolvimento de Software para Dispositivos Móveis (Católica Palmas-TO)
Pos-Palmas-Modulo-Xamarin
Aulas do módulo de Xamarin do curso de Pós-Graduação em Desenvolvimento de Software para Dispositivos Móveis (Católica Palmas-TO)
review_object_detection_metrics
Object Detection Metrics. 14 object detection metrics: mean Average Precision (mAP), Average Recall (AR), Spatio-Temporal Tube Average Precision (STT-AP). This project supports different bounding box formats as in COCO, PASCAL, Imagenet, etc.
TCF-LMO
TCF-LMO is a network made with dedicated modules to process videos and identify the presence of anomalies in frames. It is composed by: dissimilarity model; a differentiable morphology module; temporal consistency; and classification module.
rafaelpadilla's Repositories
rafaelpadilla/Object-Detection-Metrics
Most popular metrics used to evaluate object detection algorithms.
rafaelpadilla/review_object_detection_metrics
Object Detection Metrics. 14 object detection metrics: mean Average Precision (mAP), Average Recall (AR), Spatio-Temporal Tube Average Precision (STT-AP). This project supports different bounding box formats as in COCO, PASCAL, Imagenet, etc.
rafaelpadilla/Deep-Learning-Topics
rafaelpadilla/DeepLearning-VDAO
Here are some of the results of my experiments applying Deep Learning for object detection.
rafaelpadilla/TCF-LMO
TCF-LMO is a network made with dedicated modules to process videos and identify the presence of anomalies in frames. It is composed by: dissimilarity model; a differentiable morphology module; temporal consistency; and classification module.
rafaelpadilla/image_dedupe
rafaelpadilla/spatial-temporal-action-detection
rafaelpadilla/transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
rafaelpadilla/agents-course
This repository contains the Hugging Face Agents Course.
rafaelpadilla/autodistill
Images to inference with no labeling (use foundation models to train supervised models).
rafaelpadilla/autodistill-gpt-4v
GPT-4V(ision) module for use with Autodistill.
rafaelpadilla/autodistill-yolov11
YOLOv11 Target Model plugin for Autodistill
rafaelpadilla/blog
Public repo for HF blog posts
rafaelpadilla/circleci-demo-javascript-express
Sample Javascript/Express app building on CircleCI
rafaelpadilla/datasets
🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
rafaelpadilla/evaluate
🤗 Evaluate: A library for easily evaluating machine learning models and datasets.
rafaelpadilla/flask-school-app-and-api
Web app and REST API built with Flask
rafaelpadilla/imagen-pytorch
Implementation of Imagen, Google's Text-to-Image Neural Network, in Pytorch
rafaelpadilla/langchain
🦜🔗 Build context-aware reasoning applications
rafaelpadilla/ml-server-config
rafaelpadilla/nd9991-c2-Infrastructure-as-Code-v1
Repository for starter code and supporting material
rafaelpadilla/nd9991-c3-hello-world-exercise-solution
Hello world exercise from ND9991 C3 L4
rafaelpadilla/notebooks
Notebooks using the Hugging Face libraries 🤗
rafaelpadilla/pose-detection-keypoints-estimation-yolov8
rafaelpadilla/practicals-2023
Practical courses Khipu 2023
rafaelpadilla/react-slingshot
React + Redux starter kit / boilerplate with Babel, hot reloading, testing, linting and a working example app built in
rafaelpadilla/scene_graph_benchmark
image scene graph generation benchmark
rafaelpadilla/supervision
We write your reusable computer vision tools. 💜
rafaelpadilla/tennis_autodistill
rafaelpadilla/videohash
Near Duplicate Video Detection (Perceptual Video Hashing) - Get a 64-bit comparable hash-value for any video.