Results for “cover-image”

Generates Xiaohongshu (Little Red Book) posts — titles, body copy, and cover images — and manages publishing, searching, and interacting with the platform through a local MCP service.

Generates images from text prompts using diffusion models, covering prompt engineering, inpainting/outpainting, ControlNet, and API integration for production workflows.

Generates images, videos, and audio using fal.ai models via MCP, covering text-to-image, text/image-to-video, text-to-speech, and video-to-audio.

Generates images, videos, and audio using fal.ai models via MCP, covering text-to-image, text/image-to-video, text-to-speech, and video-to-audio.

Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.

Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.

Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.

Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.

Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.

Runs 150+ AI apps in the cloud via the infsh CLI, covering image generation, video creation, search, 3D, and social automation without needing a GPU.

Runs 150+ AI apps in the cloud via the inference.sh CLI, covering image generation, video creation, LLMs, web search, 3D generation, and Twitter automation.

Refine existing images through conversational edits using Nano Banana 2, covering color grading, composition, element changes, style transfer, and cleanup with iterative refinement.

Define every visual attribute as structured VGL JSON for deterministic, reproducible image generation with Bria FIBO models, covering objects, lighting, camera settings, composition, and style.

Integrates on-device and cloud machine learning into Flutter apps with TensorFlow Lite and Firebase ML Kit, covering image classification, object detection, OCR, face detection, and barcode scanning.

Generate visual storyboards with AI image generation, covering shot types, camera angles, movement, continuity rules, and panel layout for video planning and pre-production.

Generate images using AI from OpenAI or Google Gemini, with support for textures, icons, sprites, and visual assets.

State-of-the-art text-to-image generation with Stable Diffusion models via HuggingFace Diffusers. Use when generating images from text prompts, performing image-to-image translation, inpainting, or building custom diffusion pipelines.

Generate and edit high-quality images using OpenRouter's AI models including FLUX.2 Pro and Gemini 3.1 Flash Image Preview.

State-of-the-art text-to-image generation with Stable Diffusion models via HuggingFace Diffusers. Use when generating images from text prompts, performing image-to-image translation, inpainting, or building custom diffusion pipelines.

Generates UGC-style lifestyle photos of a person wearing or using a product, with authentic, social-media-native imagery.

Generate images from text prompts, perform image-to-image translation, inpainting, and build custom diffusion pipelines using Stable Diffusion models via HuggingFace Diffusers.

SNLI-VE: Visual Entailment Dataset

COYO-700M: Image-Text Pair Dataset

End-to-end Kaggle competition workflow for scored submissions, covering code competitions, validation, metrics, public notebook/discussion intel, tabular/text/image modeling, tuning, ensembling, multi-notebook architectures, Kaggle GPU offload, and hidden-test debugging.

Improves the quality of images, especially screenshots, by enhancing resolution, sharpness, and clarity. Perfect for preparing images for presentations, documentation, or social media posts.

Enables zero-shot image classification, image-text matching, and cross-modal retrieval using OpenAI's CLIP model.

Generate image captions, answer visual questions, and perform image-text retrieval using BLIP-2's Q-Former architecture with frozen vision encoders and LLMs.

Analyzes music listening data from Apple Music or Spotify exports to build a taste profile, then generates personalized playlists with AI-generated songs and album covers.

Handle files and binary data in n8n workflows correctly, covering the $binary vs $json split, reading/writing binary, preserving binary across transforms, and the agent-tool binary boundary.

Computer vision engineering skill for object detection, image segmentation, and visual AI systems. Covers CNN and Vision Transformer architectures, YOLO/Faster R-CNN/DETR detection, Mask R-CNN/SAM segmentation, and production deployment with ONNX/TensorRT. Includes PyTorch, torchvision, Ultralytics, Detectron2, and MMDetection frameworks. Use when building detection pipelines, training custom models, optimizing inference, or deploying vision systems.