3D Photo Inpainting with Python and PyTorch
A comprehensive guide to setting up and using 3D Photo Inpainting on Windows, including Miniconda environment setup, dependency installation, and usage instructions.
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Deep Floyd IF
My tentative work flow for running Deep Floyd IF locally for image generation.
Thin Plate Spline Motion Model
A practical guide to using the Thin Plate Spline Motion Model for animating static images by transferring motion from a driving video, with setup instructions and observations about optimal video dimensions and motion tracking limitations.
OpenAI Whisper Speech Recognition Guide
Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multi-task model that can perform multilingual speech recognition as well as speech translation and language identification. GitHub Repository Installation pip install git+https://github.com/openai/whisper.git Fix CUDA not detecting GPU Whisper will default to the CPU if a GPU is not detected, which is considerably slower. pip uninstall torch pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu116 Example usage # Transcribe whisper input.mp3 --model medium.en --language en --task transcribe # Translate whisper japanese.wav --model large --language Japanese --task translate Available models and languages There are five model sizes, four with English-only versions, offering speed and accuracy tradeoffs. Below are the names of the available models and their approximate memory requirements and relative speed.
Phishing Email Decoding Tools
atob() obfuscation This p5.js script is designed to find and decode base64-encoded strings that are nested within one another. The script has several functions that work together to achieve this goal: isBase64(str): This function checks if a given string str is a valid base64-encoded string. It uses a regular expression to test the string and the atob() function to try decoding the string. If the decoding is successful, the function returns true; otherwise, it returns false.
MiDaS Depth Estimation Guide
GitHub Repository During installation, I ran into an issue where the CUDA package wasn’t found. Had to modify environment.yaml to: name: midas-py310 channels: - pytorch - defaults dependencies: - nvidia::cuda-toolkit=11.7.0 - python=3.10.8 - pytorch::pytorch=1.13.0 - torchvision=0.14.0 - pip=22.3.1 - numpy=1.23.4 - pip: - opencv-python==4.6.0.66 - imutils==0.5.4 - timm==0.6.12 - einops==0.6.0 Commands that were helpful for troubleshooting CUDA:
Stable Diffusion Scripts
A comprehensive collection of utility scripts for automating image processing tasks with Stable Diffusion outputs, including batch file renaming, color grading, pixel art conversion, and video processing tools.
Frame Interpolation Large Motion (FILM)
A comprehensive guide to setting up and using Google’s Frame Interpolation Large Motion (FILM) TensorFlow implementation, enabling the creation of smooth animations by generating intermediate frames between existing images using deep learning techniques.
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- Convert Markdown To PDF With Python
- Automated Batch Image Compression with Python
- Visualizing and Analyzing Windows Folder Permissions
- Window Monitoring with Machine Vision
- Local AI API: Image-to-Text, Text-to-Speech, and LLM APIs
- Visualizing Directory Structures with PyVis
- Graphing a LAN with PyVis
- Generating Knowledge Graphs with LLMs and PyVis
- Setting Up a Local Large Language Model (LLM) Environment
- Python NetworkX Library for Network Graph Visualization
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The 10 most recently updated entries, sorted by each entry's last modification date.
- Python NetworkX Library for Network Graph Visualization
- Convert Markdown To PDF With Python
- Window Monitoring with Machine Vision
- Deep Floyd IF
- Phishing Email Decoding Tools
- Stable Diffusion Scripts
- Frame Interpolation Large Motion (FILM)
- Generating Knowledge Graphs with LLMs and PyVis
- Automated Batch Image Compression with Python
- Visualizing and Analyzing Windows Folder Permissions
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