Omniinfer Python SDK for Stable Diffusion API
这个软件开发工具包(SDK)是基于官方API文档制作的。
使用过程如果需要支持,可以在 discord 联系
SDK 保持了API 完整的功能,含文生图 Txt2Img、图生图 Img2Img、ControlNet、 VAE 等功能。
使用SDK 同样可以快速生成高质量的图片,有10000个模型支持选择,按图片生成张数计费,不会有资源浪费,每张0.0015$。
1.安装指南
pip install omniinfer-client
2.快速启动启动
第一步:获取api密钥 [docs.omniinfer.io/get-started]
import os
from omniinfer_client import OmniClient, Txt2ImgRequest, Samplers, ModelType, save_image
client = OmniClient(os.getenv('OMNI_API_KEY'))
req = Txt2ImgRequest(
model_name='sd_xl_base_1.0.safetensors',
prompt='a dog flying in the sky',
batch_size=1,
cfg_scale=7.5,
height=1024,
width=1024,
sampler_name=Samplers.EULER_A,
)
save_image(client.sync_txt2img(req).data.imgs_bytes[0], 'output.png')
3. 示例
#!/usr/bin/env python
# -*- coding: UTF-8 -*-
import os
from omniinfer_client import OmniClient, Txt2ImgRequest, Samplers, ProgressResponseStatusCode, ModelType, add_lora_to_prompt, save_image
client = OmniClient(os.getenv('OMNI_API_KEY'))
models = client.models()
# Anything V5/Ink, https://civitai.com/models/9409/or-anything-v5ink
checkpoint_model = models.filter_by_type(ModelType.CHECKPOINT).get_by_civitai_version_id(90854)
# Detail Tweaker LoRA, https://civitai.com/models/58390/detail-tweaker-lora-lora
lora_model = models.filter_by_type(ModelType.LORA).get_by_civitai_version_id(62833)
prompt = add_lora_to_prompt('a dog flying in the sky', lora_model.sd_name, "0.8")
res = client.sync_txt2img(Txt2ImgRequest(
prompt=prompt,
batch_size=1,
cfg_scale=7.5,
sampler_name=Samplers.EULER_A,
model_name=checkpoint_model.sd_name,
seed=103304,
))
if res.data.status != ProgressResponseStatusCode.SUCCESSFUL:
raise Exception('Failed to generate image with error: ' +
res.data.failed_reason)
save_image(res.data.imgs_bytes[0], "test.png")
4. 模型搜索
from omniinfer_client import OmniClient, ModelType
client = OmniClient(os.getenv('OMNI_API_KEY'))
# filter by model type
print("lora count", len(client.models().filter_by_type(ModelType.LORA)))
print("checkpoint count", len(client.models().filter_by_type(ModelType.CHECKPOINT)))
print("textinversion count", len(
client.models().filter_by_type(ModelType.TEXT_INVERSION)))
print("vae count", len(client.models().filter_by_type(ModelType.VAE)))
print("controlnet count", len(client.models().filter_by_type(ModelType.CONTROLNET)))
# filter by civitai tags
client.models().filter_by_civi_tags('anime')
# filter by nsfw
client.models().filter_by_nsfw(False) # or True
# sort by civitai download
client.models().sort_by_civitai_download()
# chain filters
client.models().\
filter_by_type(ModelType.CHECKPOINT).\
filter_by_nsfw(False).\
filter_by_civitai_tags('anime')
5. ControlNet QRCode
import os
from omniinfer_client import *
# get your api key refer to https://docs.omniinfer.io/get-started/
client = OmniClient(os.getenv('OMNI_API_KEY'))
controlnet_model = client.models().filter_by_type(ModelType.CONTROLNET).get_by_name("control_v1p_sd15_qrcode_monster_v2")
if controlnet_model is None:
raise Exception("controlnet model not found")
req = Txt2ImgRequest(
prompt="a beautify butterfly in the colorful flowers, best quality, best details, masterpiece",
sampler_name=Samplers.DPMPP_M_KARRAS,
width=512,
height=512,
steps=30,
controlnet_units=[
ControlnetUnit(
input_image=read_image_to_base64(os.path.join(os.path.abspath(os.path.dirname(__file__)), "fixtures/qrcode.png")),
control_mode=ControlNetMode.BALANCED,
model=controlnet_model.sd_name,
module=ControlNetPreprocessor.NULL,
resize_mode=ControlNetResizeMode.JUST_RESIZE,
weight=2.0,
)
]
)
res = client.sync_txt2img(req)
if res.data.status != ProgressResponseStatusCode.SUCCESSFUL:
raise Exception('Failed to generate image with error: ' +
res.data.failed_reason)
save_image(res.data.imgs_bytes[0], "qrcode-art.png")
6. Testing
export OMNI_API_KEY=<YOUR_API_KEY>
python -m pytest