๐ฅ Trending Repository: SPlayer
๐ Description: ๐ ไธไธช็ฎ็บฆ็้ณไนๆญๆพๅจ๏ผๆฏๆ้ๅญๆญ่ฏ๏ผไธ่ฝฝๆญๆฒ๏ผๅฑ็คบ่ฏ่ฎบๅบ๏ผ้ณไนไบ็ๅๆญๅ็ฎก็๏ผ้ณไน้ข่ฐฑ๏ผ็งปๅจ็ซฏๅบ็ก้้ | ็ฝๆไบ้ณไน | A minimalist music player
๐ Repository URL: https://github.com/imsyy/SPlayer
๐ Readme: https://github.com/imsyy/SPlayer#readme
๐ Statistics:
๐ Stars: 4.7K stars
๐ Watchers: 16
๐ด Forks: 835 forks
๐ป Programming Languages: Vue - TypeScript - HTML - JavaScript - SCSS - Shell
๐ท๏ธ Related Topics:
==================================
๐ง By: https://t.iss.one/DataScienceM
๐ Description: ๐ ไธไธช็ฎ็บฆ็้ณไนๆญๆพๅจ๏ผๆฏๆ้ๅญๆญ่ฏ๏ผไธ่ฝฝๆญๆฒ๏ผๅฑ็คบ่ฏ่ฎบๅบ๏ผ้ณไนไบ็ๅๆญๅ็ฎก็๏ผ้ณไน้ข่ฐฑ๏ผ็งปๅจ็ซฏๅบ็ก้้ | ็ฝๆไบ้ณไน | A minimalist music player
๐ Repository URL: https://github.com/imsyy/SPlayer
๐ Readme: https://github.com/imsyy/SPlayer#readme
๐ Statistics:
๐ Stars: 4.7K stars
๐ Watchers: 16
๐ด Forks: 835 forks
๐ป Programming Languages: Vue - TypeScript - HTML - JavaScript - SCSS - Shell
๐ท๏ธ Related Topics:
#javascript #music #music_player #vue #music_library #musicplayer #splayer #vue3 #vite #pinia
==================================
๐ง By: https://t.iss.one/DataScienceM
โค2
๐ฅ Trending Repository: GhostTrack
๐ Description: Useful tool to track location or mobile number
๐ Repository URL: https://github.com/HunxByts/GhostTrack
๐ Readme: https://github.com/HunxByts/GhostTrack#readme
๐ Statistics:
๐ Stars: 1.9K stars
๐ Watchers: 51
๐ด Forks: 313 forks
๐ป Programming Languages: Python
๐ท๏ธ Related Topics:
==================================
๐ง By: https://t.iss.one/DataScienceM
๐ Description: Useful tool to track location or mobile number
๐ Repository URL: https://github.com/HunxByts/GhostTrack
๐ Readme: https://github.com/HunxByts/GhostTrack#readme
๐ Statistics:
๐ Stars: 1.9K stars
๐ Watchers: 51
๐ด Forks: 313 forks
๐ป Programming Languages: Python
๐ท๏ธ Related Topics:
#python #linux #osint #phone_number #information #fyp #hacking #cybersecurity #indonesia #pentesting #ip_geolocation #termux #hacking_tool #information_gathering #python_hacking #termux_tool #osint_python #osint_tool #termux_hacks
==================================
๐ง By: https://t.iss.one/DataScienceM
๐ฅ Trending Repository: UI-TARS
๐ Description: No description available
๐ Repository URL: https://github.com/bytedance/UI-TARS
๐ Readme: https://github.com/bytedance/UI-TARS#readme
๐ Statistics:
๐ Stars: 7.1K stars
๐ Watchers: 79
๐ด Forks: 492 forks
๐ป Programming Languages: Python - Makefile
๐ท๏ธ Related Topics:
==================================
๐ง By: https://t.iss.one/DataScienceM
๐ Description: No description available
๐ Repository URL: https://github.com/bytedance/UI-TARS
๐ Readme: https://github.com/bytedance/UI-TARS#readme
๐ Statistics:
๐ Stars: 7.1K stars
๐ Watchers: 79
๐ด Forks: 492 forks
๐ป Programming Languages: Python - Makefile
๐ท๏ธ Related Topics:
#research
==================================
๐ง By: https://t.iss.one/DataScienceM
๐ฅ Trending Repository: puter
๐ Description: ๐ The Internet OS! Free, Open-Source, and Self-Hostable.
๐ Repository URL: https://github.com/HeyPuter/puter
๐ Website: https://puter.com
๐ Readme: https://github.com/HeyPuter/puter#readme
๐ Statistics:
๐ Stars: 35K stars
๐ Watchers: 189
๐ด Forks: 2.7K forks
๐ป Programming Languages: JavaScript - CSS - HTML - Shell - Dockerfile - Nix
๐ท๏ธ Related Topics:
==================================
๐ง By: https://t.iss.one/DataScienceM
๐ Description: ๐ The Internet OS! Free, Open-Source, and Self-Hostable.
๐ Repository URL: https://github.com/HeyPuter/puter
๐ Website: https://puter.com
๐ Readme: https://github.com/HeyPuter/puter#readme
๐ Statistics:
๐ Stars: 35K stars
๐ Watchers: 189
๐ด Forks: 2.7K forks
๐ป Programming Languages: JavaScript - CSS - HTML - Shell - Dockerfile - Nix
๐ท๏ธ Related Topics:
#javascript #open_source #gui #cloud #dropbox #storage #os #desktop #cloud_storage #osjs #operating_system #remote_desktop #webtop #web_desktop #desktop_environment #nas #web_os #good_first_issue #cloud_os #puter
==================================
๐ง By: https://t.iss.one/DataScienceM
๐ฅ Trending Repository: mcp
๐ Description: AWS MCP Servers โ helping you get the most out of AWS, wherever you use MCP.
๐ Repository URL: https://github.com/awslabs/mcp
๐ Website: https://awslabs.github.io/mcp/
๐ Readme: https://github.com/awslabs/mcp#readme
๐ Statistics:
๐ Stars: 5.6K stars
๐ Watchers: 55
๐ด Forks: 747 forks
๐ป Programming Languages: Python - Shell - Dockerfile - HTML - Jinja - TypeScript - CSS
๐ท๏ธ Related Topics:
==================================
๐ง By: https://t.iss.one/DataScienceM
๐ Description: AWS MCP Servers โ helping you get the most out of AWS, wherever you use MCP.
๐ Repository URL: https://github.com/awslabs/mcp
๐ Website: https://awslabs.github.io/mcp/
๐ Readme: https://github.com/awslabs/mcp#readme
๐ Statistics:
๐ Stars: 5.6K stars
๐ Watchers: 55
๐ด Forks: 747 forks
๐ป Programming Languages: Python - Shell - Dockerfile - HTML - Jinja - TypeScript - CSS
๐ท๏ธ Related Topics:
#aws #mcp #mcp_servers #mcp_server #modelcontextprotocol #mcp_client #mcp_tools #mcp_host #mcp_clients
==================================
๐ง By: https://t.iss.one/DataScienceM
โค1
Get top-tier market analysis: world events meet technical trading.
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I'm Michael ๐. My team and I share our market insights daily on our Telegram channel. Over the past weekend, our strategies delivered up to +39% gains.
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Join the channel below! ๐
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โค1
โจ Training YOLOv12 for Detecting Pothole Severity Using a Custom Dataset โจ
๐ Table of Contents Training YOLOv12 for Detecting Pothole Severity Using a Custom Dataset Introduction Dataset and Task Overview About the Dataset What Are We Detecting? Defining Pothole Severity Can the Pothole Severity Logic Be Improved? Configuring Your Development Environment Trainingโฆ...
๐ท๏ธ #ComputerVision #DeepLearning #ObjectDetection #Tutorial #YOLO
๐ Table of Contents Training YOLOv12 for Detecting Pothole Severity Using a Custom Dataset Introduction Dataset and Task Overview About the Dataset What Are We Detecting? Defining Pothole Severity Can the Pothole Severity Logic Be Improved? Configuring Your Development Environment Trainingโฆ...
๐ท๏ธ #ComputerVision #DeepLearning #ObjectDetection #Tutorial #YOLO
๐1
โจ Breaking the CNN Mold: YOLOv12 Brings Attention to Real-Time Object Detection โจ
๐ Table of Contents Breaking the CNN Mold: YOLOv12 Brings Attention to Real-Time Object Detection The YOLO Evolution (Quick Recap) YOLOv8: Introducing the C2f Module and OBB Support YOLOv9: Programmable Gradient Information and GELAN YOLOv10: NMS-Free Training and Dual Assignments YOLOv11:โฆ...
๐ท๏ธ #AttentionMechanisms #DeepLearning #RealTimeObjectDetection #Tutorial #YOLOSeries
๐ Table of Contents Breaking the CNN Mold: YOLOv12 Brings Attention to Real-Time Object Detection The YOLO Evolution (Quick Recap) YOLOv8: Introducing the C2f Module and OBB Support YOLOv9: Programmable Gradient Information and GELAN YOLOv10: NMS-Free Training and Dual Assignments YOLOv11:โฆ...
๐ท๏ธ #AttentionMechanisms #DeepLearning #RealTimeObjectDetection #Tutorial #YOLOSeries
โจ Training YOLOv12 for Detecting Pothole Severity Using a Custom Dataset โจ
๐ Table of Contents Training YOLOv12 for Detecting Pothole Severity Using a Custom Dataset Introduction Dataset and Task Overview About the Dataset What Are We Detecting? Defining Pothole Severity Can the Pothole Severity Logic Be Improved? Configuring Your Development Environment Trainingโฆ...
๐ท๏ธ #ComputerVision #DeepLearning #ObjectDetection #Tutorial #YOLO
๐ Table of Contents Training YOLOv12 for Detecting Pothole Severity Using a Custom Dataset Introduction Dataset and Task Overview About the Dataset What Are We Detecting? Defining Pothole Severity Can the Pothole Severity Logic Be Improved? Configuring Your Development Environment Trainingโฆ...
๐ท๏ธ #ComputerVision #DeepLearning #ObjectDetection #Tutorial #YOLO
โจ Breaking the CNN Mold: YOLOv12 Brings Attention to Real-Time Object Detection โจ
๐ Table of Contents Breaking the CNN Mold: YOLOv12 Brings Attention to Real-Time Object Detection The YOLO Evolution (Quick Recap) YOLOv8: Introducing the C2f Module and OBB Support YOLOv9: Programmable Gradient Information and GELAN YOLOv10: NMS-Free Training and Dual Assignments YOLOv11:โฆ...
๐ท๏ธ #AttentionMechanisms #DeepLearning #RealTimeObjectDetection #Tutorial #YOLOSeries
๐ Table of Contents Breaking the CNN Mold: YOLOv12 Brings Attention to Real-Time Object Detection The YOLO Evolution (Quick Recap) YOLOv8: Introducing the C2f Module and OBB Support YOLOv9: Programmable Gradient Information and GELAN YOLOv10: NMS-Free Training and Dual Assignments YOLOv11:โฆ...
๐ท๏ธ #AttentionMechanisms #DeepLearning #RealTimeObjectDetection #Tutorial #YOLOSeries
โจ Building a Multimodal Gradio Chatbot with Llama 3.2 Using the Ollama API โจ
๐ Table of Contents Building a Multimodal Gradio Chatbot with Llama 3.2 Using the Ollama API What Is Gradio and Why Is It Ideal for Chatbots? The Chatbot Youโll Build Today ๐ What Is Ollama and the Ollama API Functionality Ollamaโฆ...
๐ท๏ธ #AIApplications #Chatbots #DeepLearning #Gradio #LargeLanguageModels #OpenSource #Tutorial
๐ Table of Contents Building a Multimodal Gradio Chatbot with Llama 3.2 Using the Ollama API What Is Gradio and Why Is It Ideal for Chatbots? The Chatbot Youโll Build Today ๐ What Is Ollama and the Ollama API Functionality Ollamaโฆ...
๐ท๏ธ #AIApplications #Chatbots #DeepLearning #Gradio #LargeLanguageModels #OpenSource #Tutorial
โจ NeRFs Explained: Goodbye Photogrammetry? โจ
๐ Table of Contents NeRFs Explained: Goodbye Photogrammetry? How Do NeRFs Work? Block #A: We Begin with a 5D Input Block #B: The Neural Network and Its Output Block #C: Volumetric Rendering The NeRF Problem and Evolutions Summary and Next Stepsโฆ...
๐ท๏ธ #3DComputerVision #3DReconstruction #DeepLearning #NeuralNetworks #Photogrammetry #Tutorial
๐ Table of Contents NeRFs Explained: Goodbye Photogrammetry? How Do NeRFs Work? Block #A: We Begin with a 5D Input Block #B: The Neural Network and Its Output Block #C: Volumetric Rendering The NeRF Problem and Evolutions Summary and Next Stepsโฆ...
๐ท๏ธ #3DComputerVision #3DReconstruction #DeepLearning #NeuralNetworks #Photogrammetry #Tutorial
โจ Face detection with dlib (HOG and CNN) โจ
๐ In this tutorial, you will learn how to perform face detection with the dlib library using both HOG + Linear SVM and CNNs. The dlib library is arguably one of the most utilized packages for face recognition. A Python packageโฆ...
๐ท๏ธ #dlib #FaceApplications #Tutorials
๐ In this tutorial, you will learn how to perform face detection with the dlib library using both HOG + Linear SVM and CNNs. The dlib library is arguably one of the most utilized packages for face recognition. A Python packageโฆ...
๐ท๏ธ #dlib #FaceApplications #Tutorials
โค1
โจ Optimizing dlib shape predictor accuracy with find_min_global โจ
๐ In this tutorial you will learn how to use dlibโs find_min_global function to optimize the options and hyperparameters to dlibโs shape predictor, yielding a more accurate model. A few weeks ago I published a two-part series on using dlib toโฆ...
๐ท๏ธ #dlib #FaceApplications #FacialLandmarks #ShapePredictors #Tutorials
๐ In this tutorial you will learn how to use dlibโs find_min_global function to optimize the options and hyperparameters to dlibโs shape predictor, yielding a more accurate model. A few weeks ago I published a two-part series on using dlib toโฆ...
๐ท๏ธ #dlib #FaceApplications #FacialLandmarks #ShapePredictors #Tutorials
โจ Tuning dlib shape predictor hyperparameters to balance speed, accuracy, and model size โจ
๐ In this tutorial, you will learn how to optimally tune dlibโs shape predictor hyperparameters and options to obtain a shape predictor that balances speed, accuracy, and model size. Today is part two in our two-part series on training custom shapeโฆ...
๐ท๏ธ #dlib #FaceApplications #FacialLandmarks #ShapePredictors #Tutorials
๐ In this tutorial, you will learn how to optimally tune dlibโs shape predictor hyperparameters and options to obtain a shape predictor that balances speed, accuracy, and model size. Today is part two in our two-part series on training custom shapeโฆ...
๐ท๏ธ #dlib #FaceApplications #FacialLandmarks #ShapePredictors #Tutorials
โจ Training a custom dlib shape predictor โจ
๐ In this tutorial, you will learn how to train your own custom dlib shape predictor. Youโll then learn how to take your trained dlib shape predictor and use it to predict landmarks on input images and real-time video streams. Todayโฆ...
๐ท๏ธ #dlib #FaceApplications #FacialLandmarks #ShapePredictors #Tutorials
๐ In this tutorial, you will learn how to train your own custom dlib shape predictor. Youโll then learn how to take your trained dlib shape predictor and use it to predict landmarks on input images and real-time video streams. Todayโฆ...
๐ท๏ธ #dlib #FaceApplications #FacialLandmarks #ShapePredictors #Tutorials
โค1
โจ Introduction to OpenCV AI Kit (OAK) โจ
๐ Table of Contents Introduction to OpenCV AI Kit (OAK) Introduction OAK Hardware OAK-1 OAK-D Limitation OAK-FFC OAK USB Hardware Offerings OAK PoE Hardware Offerings OAK Developer Kit OAK Modules Comparison Applications on OAK Image Classifier On-Device Face Detection Face Maskโฆ...
๐ท๏ธ #EmbeddedIoTandComputerVision #EmbeddedIoTComputerVision #OAK #Tutorials
๐ Table of Contents Introduction to OpenCV AI Kit (OAK) Introduction OAK Hardware OAK-1 OAK-D Limitation OAK-FFC OAK USB Hardware Offerings OAK PoE Hardware Offerings OAK Developer Kit OAK Modules Comparison Applications on OAK Image Classifier On-Device Face Detection Face Maskโฆ...
๐ท๏ธ #EmbeddedIoTandComputerVision #EmbeddedIoTComputerVision #OAK #Tutorials
โค1
โจ An interview with Jagadish Mahendran, 1st place winner of the OpenCV Spatial AI Competition โจ
๐ In this post, I interview Jagadish Mahendran, senior Computer Vision/Artificial Intelligence (AI) engineer who recently won 1st place in the OpenCV Spatial AI Competition using the new OpenCV AI Kit (OAK). Jagadishโs winning project was a computer vision system forโฆ...
๐ท๏ธ #EmbeddedIoTandComputerVision #Interviews #OpenCVAIKit
๐ In this post, I interview Jagadish Mahendran, senior Computer Vision/Artificial Intelligence (AI) engineer who recently won 1st place in the OpenCV Spatial AI Competition using the new OpenCV AI Kit (OAK). Jagadishโs winning project was a computer vision system forโฆ...
๐ท๏ธ #EmbeddedIoTandComputerVision #Interviews #OpenCVAIKit
โจ An interview with Brandon Gilles, creator of the OpenCV AI Kit (OAK) โจ
๐ In this post, I interview Brandon Gilles, a longtime PyImageSearch reader, and creator of the OpenCV AI Kit (OAK), which is revolutionizing how we are performing embedded computer vision and deep learning. To celebrate the 20th anniversary of the OpenCVโฆ...
๐ท๏ธ #DeepLearning #EmbeddedIoTandComputerVision #Interviews #OpenCVAIKit
๐ In this post, I interview Brandon Gilles, a longtime PyImageSearch reader, and creator of the OpenCV AI Kit (OAK), which is revolutionizing how we are performing embedded computer vision and deep learning. To celebrate the 20th anniversary of the OpenCVโฆ...
๐ท๏ธ #DeepLearning #EmbeddedIoTandComputerVision #Interviews #OpenCVAIKit
โค1
โจ How to configure your NVIDIA Jetson Nano for Computer Vision and Deep Learning โจ
๐ In todayโs tutorial, you will learn how to configure your NVIDIA Jetson Nano for Computer Vision and Deep Learning with TensorFlow, Keras, TensorRT, and OpenCV. Two weeks ago, we discussed how to use my pre-configured Nano .img file โ today,โฆ...
๐ท๏ธ #DeepLearning #EmbeddedIoTandComputerVision #IoT #Tutorials
๐ In todayโs tutorial, you will learn how to configure your NVIDIA Jetson Nano for Computer Vision and Deep Learning with TensorFlow, Keras, TensorRT, and OpenCV. Two weeks ago, we discussed how to use my pre-configured Nano .img file โ today,โฆ...
๐ท๏ธ #DeepLearning #EmbeddedIoTandComputerVision #IoT #Tutorials
โค2