Pinned Repositories
DiffMorpher
Official Code for DiffMorpher: Unleashing the Capability of Diffusion Models for Image Morphing (CVPR 2024)
video-retalking
[SIGGRAPH Asia 2022] VideoReTalking: Audio-based Lip Synchronization for Talking Head Video Editing In the Wild
ComfyUI_Kosmos2_BBox_Cutter
Image identification with Kosmos2 model, drawing and cutting bbox with object detection
ComfyUI_StoryCreator
This project offers a user-friendly interface that allows users to easily create stories and enrich them with visuals. It supports creativity with story creation and visualisation features.
SummativeInfoResearcherAgents
This project is an automated research and summarization tool that allows users to conduct research on a specific question and summarize the information found and present it as a blog post.
VisQueryPDF
It automatically describes images in PDF files and generates questions from these descriptions. With its advanced RAG structure, it directs these questions directly to PDF text content, providing comprehensive information extraction and analysis.
ultralytics
NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite
oztrkoguz's Repositories
oztrkoguz/ComfyUI_StoryCreator
This project offers a user-friendly interface that allows users to easily create stories and enrich them with visuals. It supports creativity with story creation and visualisation features.
oztrkoguz/ComfyUI_Kosmos2_BBox_Cutter
Image identification with Kosmos2 model, drawing and cutting bbox with object detection
oztrkoguz/SummativeInfoResearcherAgents
This project is an automated research and summarization tool that allows users to conduct research on a specific question and summarize the information found and present it as a blog post.
oztrkoguz/VisQueryPDF
It automatically describes images in PDF files and generates questions from these descriptions. With its advanced RAG structure, it directs these questions directly to PDF text content, providing comprehensive information extraction and analysis.
oztrkoguz/RAG-Framework-Evaluation
This project aims to compare different Retrieval-Augmented Generation (RAG) frameworks in terms of speed and performance.