𝐒𝐚𝐲𝐡𝐞𝐥𝐥𝐨𝟎𝐨✔️

Unlocking the Power of CUDA 12.1 with DWPose and Onnxruntime-GPU: A Simple GuideIf you're looking to harness the capabilities of DWPOSE or Onnxruntime with CUDA 12.1, follow these straightforward steps to get started.Step-by-Step Installation Guide:Uninstall Old Version of Onnxruntime-GPU:Begin by removing any existing version of Onnxruntime-GPU to avoid conflicts.shpip uninstall onnxruntime-gpuCopy codepip uninstall onnxruntime-gpuInstall PyTorch with CUDA 12.1:Install the specific versions of PyTorch, Torchvision, and Torchaudio that are compatible with CUDA 12.1.shpip install torch==2.3.0+cu121 torchvision==0.18.0+cu121 torchaudio==2.3.0+cu121 --extra-index-url https://download.pytorch.org/whl/cu121Copy codepip install torch==2.3.0+cu121 torchvision==0.18.0+cu121 torchaudio==2.3.0+cu121 --extra-index-url https://download.pytorch.org/whl/cu121Install Onnx and Onnxruntime:Next, install the Onnx and Onnxruntime packages.shpip install onnx onnxruntimeCopy codepip install onnx onnxruntimeInstall Onnxruntime-GPU for CUDA 12.1:Finally, install the Onnxruntime-GPU package compatible with CUDA 12.1 using the provided extra index URL.shpip install onnxruntime-gpu --extra-index-url https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/onnxruntime-cuda-12/pypi/simple/Copy codepip install onnxruntime-gpu --extra-index-url https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/onnxruntime-cuda-12/pypi/simple/Portable Version Installation:If you need a portable setup, follow this method:shpython_embeded\python.exe -m pip install onnxruntime-gpu --extra-index-url https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/onnxruntime-cuda-12/pypi/simple/Copy codepython_embeded\python.exe -m pip install onnxruntime-gpu --extra-index-url https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/onnxruntime-cuda-12/pypi/simple/By following these steps, you'll be equipped to fully utilize the power of CUDA 12.1 with DWPOSE and Onnxruntime-GPU, ensuring optimal performance and compatibility for your projects. Happy coding!

Graph Representation Learning: Unveiling the Secrets of Node Mapping and Random WalksNode Mapping: Simplifying ComplexityNode mapping is like using mathematical functions to represent images. By translating an image into a function, we can drastically simplify it. This technique also allows us to reduce the dimensionality of three-dimensional data, shrinking the overall data magnitude from an n-th power of singular data to a magnitude of 2n, thus significantly reducing the total data volume.The Magic of Random WalksUnbiased Random Walks: Imagine exploring a maze where every path is equally probable. Unbiased random walks represent this scenario, where the probability of moving in any direction is the same.Biased Random Walks: Now, picture a maze where some paths are more likely to be chosen. Biased random walks occur when there is a higher probability of moving in a certain direction.Decoding with EncodersFeature Processing: Encoders help us process data features, enabling us to understand the similarities between different data points based on their paths.Similarity Representation: Think of it as measuring the closeness of two friends based on how often their paths cross.Deep Walks with Consistent StepsRandom Walk: Begin by performing a random walk on the graph. Start at a node and move randomly along the edges of the graph for a set number of steps, forming a random walk sequence. This is like exploring the connections between nodes by wandering through the graph.Word2Vec Model: Apply the Word2Vec model to each random walk sequence to learn the vector representation of nodes. The model treats node sequences as word sequences, using a neural network to learn node vectors. Nodes that frequently appear together in sequences are closer in vector space.Node Representation Learning: Finally, map each node into a low-dimensional vector space using the trained Word2Vec model. These representations can be used for graph analysis, node classification, link prediction, and more.Visualizing Graphs in ImagesFor a generated image, the walk path represents the movement path of pixels or feature points in the image. This path records the movement trajectory on the image, starting from an initial position and following certain rules.Specifically, the walk path can be interpreted as:Feature Point Movement Trajectory: If the nodes in the image represent feature points or key points, the walk path can be understood as the movement trajectory between these points. This path captures the structural information or key features of the image.Pixel Scanning Order: If the image is a collection of pixels, the walk path represents the scanning order of these pixels. This path helps traverse the image and capture its content or texture information.Object Movement Path: If the nodes in the image represent objects, the walk path can be understood as the movement path of these objects. This path simulates the motion or behavior of objects within the image.Graph representation learning unveils the hidden connections and movements within data, transforming complex relationships into understandable patterns. Through node mapping and random walks, we can unlock new insights and applications in data analysis and visualization.

Captivating Script Creation and Animation Preparation for Knitted ProductsImage Generation:Precision and Style: Harnessing the power of SD for ultimate control, ensuring a cohesive series of images (utilizing masks, showcasing the same attire on different models, and seamlessly switching model poses).Seamless Transitions:Immersive Zoom Out: Experience the magic of scene transitions with Midjourney's captivating zoom-out effects.Product Showcase:Dynamic Scene Changes: Highlight your products through smooth and engaging scene transitions.Animation Production:Advanced Techniques: Employ cutting-edge tools like Ipiv's Morph, img2vid, AnimateDiff, LCM, and Hyper-SD for superior continuity and fluidity between keyframes.Keyframe Mastery:Auxiliary Elements: Enhance the narrative with detailed auxiliary elements.Unified Elements: Combine auxiliary elements with main elements for a richer visual experience.Style Transformation: Watch as main elements undergo stunning style transitions.Final Masterpiece: Culminate in a breathtaking final image.Deform:Unique AI Visuals: Dive into scene transitions that feature AI’s distinctive, large-scale imagery.Runway Magic:Dynamic Movements: Capture small yet impactful model movements and action close-ups for a compelling visual experience.Enchanting Style Transfer:Fantasy Meets Reality: Blend fantasy with the knitted aesthetic for a mesmerizing look.Script Preparation:Perfect Timing: Craft a 15-second masterpiece, with each segment highlighting a unique workflow effect.Segment One:Eight Stunning Images:Zoom out (1)Texture close-up (2)Fabric close-up (3)Product close-up (4)Model close-up (5, 6, 7)Scene close-up (8)Each image displayed for a tantalizing 0.5 seconds.Segment Two:Dreamlike Transitions:Fall into a surreal lake, maintaining the main element’s action frames while switching scenes.Segment Three:Keyframe Brilliance:Four keyframes featuring Ipiv's Morph, showcasing auxiliary elements (water splashes, lines) and the main elements (knitted product models).Segment Four:Artistic Style Transfer:Transform realistic water splash images into a knitted fantasy style using LoRa.Compare materials and IP effects for a stunning conclusion.Bring your knitted products to life with this captivating and visually enchanting script and animation preparation. Let your audience be mesmerized by the blend of advanced techniques and artistic creativity.

You Can Sell Models, LoRAs, ..etc on Ko-fi and SociabuzzIn today's digital era, machine learning and AI tools are valuable assets that can be leveraged in various applications, from developing innovative technologies to conducting cutting-edge research. If you have the skills to create high-quality models, LoRAs, and other related resources, you have a great opportunity to monetize those skills. Two platforms where you can sell ready-to-use AI resources are Ko-fi and Sociabuzz.Why Sell AI Resources?Well-prepared models and more are in high demand among researchers, developers, and tech companies. The process of creating and fine-tuning these resources often requires significant time and expertise. By providing ready-to-use AI resources, you can help others save time and effort while earning financial rewards for your work.-Ko-fi PlatformKo-fi is a popular platform (Global) that allows creators to receive financial support from their fans / buyers. Although initially designed to support artists and content creators, Ko-fi has become a good place to sell digital products, including AI models and more.Steps to Sell AI Resources on Ko-fi:Create a Ko-fi Account: Sign up and create a profile on Ko-fi.Add Digital Products: Use the "Shop" feature to add your models, LoRAs, or other AI resources as digital products.Describe the Resource: Create an informative and engaging description of your resource, including details such as the type of model, use cases, and performance metrics.Set a Price: Determine a reasonable price for your resource, considering the quality and uniqueness of the product you offer.Promote Your Product: Share the link to your Ko-fi page on social media, blogs, or relevant communities to attract potential buyers.-Sociabuzz PlatformSociabuzz is another popular platform in Indonesia (can be used by anyone from any country such as ko-fi, etc.) that allows creators to receive support from their fans / buyers. Additionally, Sociabuzz provides features for selling services and digital products.Steps to Sell AI Resources on Sociabuzz:Create a Sociabuzz Account: Sign up and create a profile on Sociabuzz.Add Services or Products: Use the "Create Service" feature to add your models, LoRAs, or other AI resources as products for sale.Describe the Resource: Write a detailed description of your resource, including important information like the type of model, use cases, and performance metrics.Set a Price: Set a competitive price for your resource.Promote Your Sociabuzz Page: Use social media, forums, and blogs to promote your Sociabuzz page and attract interested buyers.Tips for SuccessQuality is Key: Ensure that the models and resources you sell are high-quality, well-tested, and relevant to market needs.Clear Descriptions: Clearly explain what is included in your resource and how it can be used.Free Samples: Consider providing free samples of your resources to attract buyer interest.Active Promotion: Actively promote your product on various platforms and relevant communities.By leveraging platforms like Ko-fi and Sociabuzz, you can sell ready-to-use AI models, LoRAs, and other related resources to a broader audience while earning income from your hard work in creating and fine-tuning these tools. Start today and see how your AI resources can become a valuable source of revenue!