was-node-suite-comfyui
CLIP
was-node-suite-comfyui | CLIP | |
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13 | 104 | |
822 | 22,316 | |
- | 3.0% | |
9.0 | 1.2 | |
3 days ago | 4 days ago | |
Python | Jupyter Notebook | |
MIT License | MIT License |
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was-node-suite-comfyui
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Batch-processing images by folder on ComfyUI
WAS node suite has a Load Image Batch node. You can get all files in the directory and subdirectory or *.jpg (for example) to select only JPGs.
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Blending images randomly without a prompt with reference only is so fun
workflow includes nodes from https://github.com/WASasquatch/was-node-suite-comfyui and https://github.com/Fannovel16/comfyui_controlnet_aux
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Image to Text custom node?
You're looking for BLIP from WAS Node Suite.
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Organized ComfyUI txt2Img-upscale workflow
WAS Node Suite
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Setting the Output directory in ComfyUI
You must use the "save Image "node from WAS suite : GitHub - WASasquatch/was-node-suite-comfyui: An extensive node suite for ComfyUI with over 180 new nodes
- Seamless or tiled image generation with ComfyUI?
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COMFYUI SDXL WORKFLOW INBOUND! Q&A NOW OPEN! (WIP EARLY ACCESS WORKFLOW INCLUDED!)
ComfyUI Noise can do it. Maybe that WAS has some nodes that let you do it? but haven't checked
- Batch processing, debugging text node.
- SDXL two staged denoising workflow
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On the fly merging of 3 different models in ComfyUI with saving.
You need to have the WAS Suite installed and your filenames should be your prompts.
CLIP
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Anomaly Detection with FiftyOne and Anomalib
pip install -U huggingface_hub umap-learn git+https://github.com/openai/CLIP.git
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How to Cluster Images
We will also need two more libraries: OpenAI’s CLIP GitHub repo, enabling us to generate image features with the CLIP model, and the umap-learn library, which will let us apply a dimensionality reduction technique called Uniform Manifold Approximation and Projection (UMAP) to those features to visualize them in 2D:
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Show HN: Memories, FOSS Google Photos alternative built for high performance
Biggest missing feature for all these self hosted photo hosting is the lack of a real search. Being able to search for things like "beach at night" is a time saver instead of browsing through hundreds or thousands of photos. There are trained neural networks out there like https://github.com/openai/CLIP which are quite good.
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Zero-Shot Prediction Plugin for FiftyOne
In computer vision, this is known as zero-shot learning, or zero-shot prediction, because the goal is to generate predictions without explicitly being given any example predictions to learn from. With the advent of high quality multimodal models like CLIP and foundation models like Segment Anything, it is now possible to generate remarkably good zero-shot predictions for a variety of computer vision tasks, including:
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A History of CLIP Model Training Data Advances
(Github Repo | Most Popular Model | Paper | Project Page)
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NLP Algorithms for Clustering AI Content Search Keywords
the first thing that comes to mind is CLIP: https://github.com/openai/CLIP
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How to Build a Semantic Search Engine for Emojis
Whenever I’m working on semantic search applications that connect images and text, I start with a family of models known as contrastive language image pre-training (CLIP). These models are trained on image-text pairs to generate similar vector representations or embeddings for images and their captions, and dissimilar vectors when images are paired with other text strings. There are multiple CLIP-style models, including OpenCLIP and MetaCLIP, but for simplicity we’ll focus on the original CLIP model from OpenAI. No model is perfect, and at a fundamental level there is no right way to compare images and text, but CLIP certainly provides a good starting point.
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COMFYUI SDXL WORKFLOW INBOUND! Q&A NOW OPEN! (WIP EARLY ACCESS WORKFLOW INCLUDED!)
in the modal card it says: pretrained text encoders (OpenCLIP-ViT/G and CLIP-ViT/L).
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Stability Matrix v1.1.0 - Portable mode, Automatic updates, Revamped console, and more
Command: "C:\StabilityMatrix\Packages\stable-diffusion-webui\venv\Scripts\python.exe" -m pip install https://github.com/openai/CLIP/archive/d50d76daa670286dd6cacf3bcd80b5e4823fc8e1.zip --prefer-binary
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[D] LLM or model that does image -> prompt?
CLIP might work for your needs.
What are some alternatives?
ComfyUI - The most powerful and modular stable diffusion GUI, api and backend with a graph/nodes interface.
open_clip - An open source implementation of CLIP.
images-grid-comfy-plugin - A simple comfyUI plugin for images grid (X/Y Plot)
sentence-transformers - Multilingual Sentence & Image Embeddings with BERT
efficiency-nodes-comfyui - A collection of ComfyUI custom nodes. ⚠️ WARNING: This repo is no longer maintained.
latent-diffusion - High-Resolution Image Synthesis with Latent Diffusion Models
comfyui-dynamicprompts - ComfyUI custom nodes for Dynamic Prompts
disco-diffusion
ComfyUI_TiledKSampler - Tiled samplers for ComfyUI
DALLE2-pytorch - Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch
ComfyUI_UltimateSDUpscale - ComfyUI nodes for the Ultimate Stable Diffusion Upscale script by Coyote-A.
BLIP - PyTorch code for BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation