معرفی شرکت ها

تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر

تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر

تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر

تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر

تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر

توضیحات

UI tool to help you generate art (and experiment) with multimodal (text, image) AI models (stable diffusion)

ویژگی	مقدار
سیستم عامل	OS Independent
نام فایل	Peacasso-0.0.9a0
نام	Peacasso
نسخه کتابخانه	0.0.9a0
نگهدارنده	[]
ایمیل نگهدارنده	[]
نویسنده	-
ایمیل نویسنده	Victor Dibia <victor.dibia@gmail.com>
آدرس صفحه اصلی	-
آدرس اینترنتی	https://pypi.org/project/Peacasso/
مجوز	MIT License Copyright (c) 2022 Victor Dibia Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

# Peacasso [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/victordibia/peacasso/blob/master/notebooks/tutorial.ipynb) Peacasso [Beta] is a UI tool to help you generate art (and experiment) with multimodal (text, image) AI models (stable diffusion). This project is still in development (see roadmap below). ![](https://github.com/victordibia/peacasso/blob/master/docs/images/screenpc.png?raw=true) ## Why Use Peacasso? <img width="100%" src="https://github.com/victordibia/peacasso/blob/master/docs/images/peacasso.gif?raw=true" /> Because you deserve a nice UI and great workflow that makes exploring stable diffusion models fun! But seriously, here are a few things that make Peacasson interesting: - **Easy installation**. Instead of cobbling together command line scripts, Peacasso provides a `pip install` flow and a UI that supports a set of curated default operations. - **UI with good defaults**. The current implementation of Peacasso provides a UI for basic operations - text and image based prompting (+ inpainting), remixing generated images as prompts, model parameter selection, image download. Also covers the little things .. like light and dark mode. - **Python API**. While the UI is the focus here, there is an underlying python api which will bake in experimentation features (e.g. saving intermediate images in the sampling loop, exploring model explanations etc. . see roadmap below). Clearly, Peacasso (UI) might not be for those interested in low level code. ## Requirements and Installation - Step 1: **Access to Weights via HuggingFace** Access to the diffusion model weights requires a HuggingFace model account and access token. Please create an account at [huggingface.co](https://huggingface.co/), get an [access token](https://huggingface.co/settings/tokens) and agree to the model terms [here](https://huggingface.co/CompVis/stable-diffusion-v1-4). Next, create a `HF_API_TOKEN` environment variable containing your token. `export HF_API_TOKEN=your_token`. Note that the first time you run peacasso, the weights for the SD model are [cached locally](https://huggingface.co/transformers/v4.0.1/installation.html#caching-models) on your machine. In theory, you can download the weights, and run peacasso by pointing to the folder with the weights. - Step 2: **Verify Environment - Pythong 3.7+ and CUDA** Setup and verify that your python environment is `python 3.7` or higher (preferably, use Conda). Also verify that you have CUDA installed correctly (`torch.cuda.is_available()` is true) and your GPU has about [7GB of VRAM memory](https://stability.ai/blog/stable-diffusion-public-release). Once requirements are met, run the following command to install the library: ```bash pip install peacasso ``` Don't have a GPU, you can still use the python api and UI in a colab notebook. See this [colab notebook](https://colab.research.google.com/github/victordibia/peacasso/blob/master/notebooks/tutorial.ipynb) for more details. ## Usage - UI and Python API You can use the library from the ui by running the following command: ```bash peacasso ui --port=8080 ``` Then navigate to http://localhost:8080/ in your browser. You can also use the python api by running the following command: ```python import os from dotenv import load_dotenv from peacasso.generator import ImageGenerator from peacasso.datamodel import GeneratorConfig token = os.environ.get("HF_API_TOKEN") gen = ImageGenerator(token=token, model="CompVis/stable-diffusion-v1-4") prompt = "A sea lion wandering the streets of post apocalyptic London" prompt_config = GeneratorConfig( prompt=prompt, num_images=3, width=512, height=512, guidance_scale=7.5, num_inference_steps=50, mode="prompt", # prompt, image return_intermediates=True, # return intermediate images in the generate dict response ) result = gen.generate(prompt_config) for i, image in enumerate(result["images"]): image.save(f"image_{i}.png") ``` ## Features and Road Map - [x] Command line interface - [x] UI Features. Query models with multiple parametrs - [x] Text prompting (text2img) - [x] Image based prompting (img2img) - [x] Inpainting (img2img) - [ ] Editor (for outpainting) - [ ] Latent space exploration - [ ] Model explanations - [ ] Experimentation tools - [x] Save intermediate images in the sampling loop - [ ] Prompt recommendation tools - [ ] Model explanations - [ ] Curation/sharing experiment results - [ ] Defined Workflows (e.g., tiles, composition etc.) ## Acknowledgement This work builds on the stable diffusion model and code is adapted from the HuggingFace [implementation](https://huggingface.co/blog/stable_diffusion). Please note the - [CreativeML Open RAIL-M](https://huggingface.co/spaces/CompVis/stable-diffusion-license) license associated with the stable diffusion model.

نیازمندی

مقدار	نام
-	transformers
-	scipy
-	ftfy
==0.3.0	diffusers
-	torch
-	pydantic
-	uvicorn
-	typer
-	fastapi

زبان مورد نیاز

مقدار	نام
>=3.7	Python

نحوه نصب

نصب پکیج whl Peacasso-0.0.9a0:

pip install Peacasso-0.0.9a0.whl

نصب پکیج tar.gz Peacasso-0.0.9a0:

pip install Peacasso-0.0.9a0.tar.gz