Show HN: AI assisted image editing with audio instructions
The GitHub repository hosts "AAIELA: AI Assisted Image Editing with Language and Audio," a project enabling image editing via audio commands and AI models. It integrates various technologies for object detection, language processing, and image inpainting. Future plans involve model enhancements and feature integrations.
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The GitHub repository at the provided URL pertains to the project "AAIELA: AI Assisted Image Editing with Language and Audio." This project aims to enable users to edit images through audio commands and AI models, incorporating computer vision, speech-to-text, language models, and text-to-image inpainting. The project structure encompasses components for object detection, audio transcription, language models, and inpainting models. The workflow involves image upload, segmentation, audio input, transcription, language understanding, image inpainting, and output generation. Future research directions include retraining the inpainting model, automatic mask generation, contextual reasoning, multi-object mask generation, and visual language model integration. The project's to-do list features tasks like integrating TensorRT for Stable Diffusion models, ControlNet integration, Mediapipe Face Mesh integration for facial features modification, pose landmark detection, super-resolution model implementation, and interactive mask editing using Segment Anything.
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The biggest reason we should be adding conversational UI to everything is the harm done by RSI and sedentary keyboard and mouse interfaces. We're crippling entire generations of people by sticking to outdated hardware. The good news is we can break free of this now that we have huge improvements in LLMs and AR hardware. We'll be back to healthy levels of activity in 5 to 10 years. Sorry Keeb builders, it's time to join the stamp collectors and typewriter enthusiasts. We'll be working in the park today.
This is why usually when you're doing this sort of traditional inpainting in automatic1111 you generate several iterations with various mask blurs, whole picture vs only masked section, padding and of course the optimal inpainting checkpoint model to use depends on whether or not the original images is photorealistic versus illustrated, etc.
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