Results for “ima”

Read, write, and modify DICOM medical imaging files, including pixel data extraction, metadata manipulation, anonymization, and format conversion.

ImageNet-21K Pretraining for the Masses

GLIP: Grounded Language-Image Pre-training

Mantis: Interleaved Multi-Image Instruction Tuning

Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models. Supports multi-turn image chat, visual question answering, and instruction following. Use for vision-language chatbots or image understanding tasks. Best for conversational image analysis.

Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models. Supports multi-turn image chat, visual question answering, and instruction following. Use for vision-language chatbots or image understanding tasks. Best for conversational image analysis.

Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models. Supports multi-turn image chat, visual question answering, and instruction following. Use for vision-language chatbots or image understanding tasks. Best for conversational image analysis.

Creates original educational comics with flexible art styles and tones, supporting detailed panel layouts and batch image generation.

Realize every typed [VISUAL:...] placeholder in the cited draft into an actual asset — Playwright screenshots of brand UI, Replicate-generated images (GPT Image 2 default, Nano Banana backup), matplotlib charts. Manual-capture flag for video/external/gif/adult-image. Updates the draft to reference local image paths.

Convert an image between PNG, JPEG, and WebP formats with quality control for web optimization.

Integrate client-side video and audio ads using the IMA SDK across web, Android, iOS, and TV platforms with VAST/VMAP support.

Add visual callouts like rectangles, arrows, and labels to screenshots, diagrams, and images using PIL/Pillow, with support for animated GIF annotations.

AI video generation with LTX-2.3 22B — text-to-video, image-to-video clips for video production. Use when generating video clips, animating images, creating b-roll, animated backgrounds, or motion content. Triggers include video generation, animate image, b-roll, motion, video clip, text-to-video, image-to-video.

Build, configure, and troubleshoot GraalVM Native Image applications using native-image CLI, Maven, or Gradle Native Build Tools, including reachability metadata and issue diagnosis.

Sigmoid Loss for Language Image Pre-Training

CapsFusion: Rethinking Image-Text Data at Scale

TextVQA: Towards Reasoning about Text in Images

Copies overlay files and built artifacts into a staged BSP image for NVIDIA Jetson platforms, preparing it for flashing without modifying the workspace.

Apply a text watermark to a photo using layer-based image composition for brand protection and copyright.

Perform comprehensive forensic analysis of disk images using Autopsy to recover files, examine artifacts, and build investigation timelines.

AI video generation with LTX-2.3 22B — text-to-video, image-to-video clips for video production. Use when generating video clips, animating images, creating b-roll, animated backgrounds, or motion content. Triggers include video generation, animate image, b-roll, motion, video clip, text-to-video, image-to-video.

Adds GraalVM native image support to Java applications by analyzing the project structure, configuring the build tool, and iteratively resolving build errors.

Create forensically sound bit-for-bit disk images using dd and dcfldd while preserving evidence integrity through hash verification.

Generate a complete Amazon product listing image set — hero image, lifestyle shot, feature infographic, and detail closeup optimized for Amazon standards.

Vision-language pre-training framework bridging frozen image encoders and LLMs. Use when you need image captioning, visual question answering, image-text retrieval, or multimodal chat with state-of-the-art zero-shot performance.

Vision-language pre-training framework bridging frozen image encoders and LLMs. Use when you need image captioning, visual question answering, image-text retrieval, or multimodal chat with state-of-the-art zero-shot performance.

DALL-E: Zero-Shot Text-to-Image Generation

DreamLIP: Language-Image Pre-training with Long Captions

Breaks down complex content into eye-catching image card series with 12 visual styles, 8 layouts, and 3 color palettes, optimized for social media engagement.

Conducts disk forensics investigations using forensic imaging, file system analysis, artifact recovery, and timeline reconstruction to support incident response cases.

Generates premium website design images, then deeply analyzes them to implement faithful frontend code for hero sections, landing pages, and marketing sites.

Runs the open-source LLaVA vision-language model for image understanding, captioning, visual question answering, and multi-turn image conversations, including setup, inference, and training guidance.

Generate a high-converting ad creative set — hero image, ad copy variations, and platform-optimized crops for Meta, Google Display, and LinkedIn.

DALL-E 3: Improving Image Generation with Better Captions

Geracao de imagens humanizadas via Google AI Studio (Gemini). Fotos realistas estilo influencer ou educacional com iluminacao natural e imperfeicoes sutis.

Use this skill when the user requests to generate, create, or imagine videos. Supports structured prompts and reference image for guided generation.