Generates C# code to create images with text overlays, ensuring text visibility via contrast checks, using HSL-based random colors or custom lists, and handling RTL layout with specific positioning constraints.
Generates ASCII art using Braille patterns block characters with strict constraints to exclude descriptions, explanations, newlines, and any non-Braille formatting.
Generates ASCII art using only Braille Unicode characters without any descriptive text, explanations, or markdown formatting.
A Python program to detect anomalies in videos using the VideoMAEForPreTraining model. It processes videos by dividing them into 16-frame clips, extracts embeddings using an unmasked boolean mask, and compares them against a normal behavior profile using Mean Squared Error (MSE).
Script Python pour extraire des segments vidéo basés sur les pics d'amplitude audio, offrant à l'utilisateur le choix de placer ce pic au début (1/3), au milieu (1/2), à la fin (2/3) ou aléatoirement dans le segment extrait.
Génère un script Python complet pour analyser l'audio de vidéos (RMS), identifier les moments forts, trier les résultats et extraire les segments correspondants via ffmpeg, avec un positionnement précis du pic sonore (1/3, 1/2, 2/3).
Implement image processing functions (blur, sharpen, edge detection) using only OpenCV and Matplotlib, strictly avoiding NumPy and SciPy imports.
Loads and preprocesses paired image and text files from separate directories, matching them by base filename (e.g., screen_13.png with html_13.html) for machine learning training.
Load audio files from a directory, parse labels from filenames, generate random VAD segments, extract STFT features (mean along axis 1, converted to dB), and split the dataset into train/test sets.
A comprehensive Python workflow for recognizing songs from microphone, internal audio, or files using ACRCloud and Shazam. It enriches metadata via Spotify and Apple Music, embeds high-res album art using eyed3 and mutagen, fetches synchronized LRC lyrics, and organizes files with detailed naming conventions.
Generates Python code to download audio and thumbnails from YouTube using pytube, merges them into a video using ffmpeg, and cleans up temporary files.
Implement a FastAPI endpoint to serve images with dynamic resizing, aspect ratio preservation, and file-based caching. Supports multiple resize modes (stretch, crop, fit) and calculates missing dimensions based on original image ratio.
A Python function to load and preprocess paired screenshot and HTML files from separate directories, matching them by base filename (e.g., screen_13.png with html_13.html), resizing images, and normalizing pixel values for model training.
Generates a Python script to download YouTube playlists as MP3 files, including video thumbnails and artist metadata tags.
Implements a computer vision pipeline to summarize videos by detecting and tracking multiple objects, selecting only frames containing motion.
Implement MATLAB functions for numerical analysis, including curve fitting, regression, and integration, based on user-provided mathematical formulas and specific constraints.
Generates a table of all 32 binary combinations of the Big Five personality traits (O, C, E, A, N), sorted by binary order, using +/- notation, and populated with fictional character examples and rationales.
Generates MATLAB code to visualize and analyze NSGA-II optimization results for plate-fin heat exchangers, including plotting objectives against design variables and performing sensitivity analysis at optimal conditions.
Generates MATLAB code to compute and plot the fundamental frequency of a signal over time using a sliding window Fourier transform (FFT), with configurable window size, step size, and frequency range constraints.
Calculates the required diameter of PE4710 pontoon pipes for floating docks and performs comprehensive structural verification (ULS/SLS), including buoyancy, detailed lateral load checks (wind/berthing) with mooring pile mechanics, wave-induced flexure, and vibration.
