Novita AI Python SDK

This SDK is based on the official API documentation.

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Installation

pip install novita-client

Examples

• fine tune example
• cleanup
• controlnet
• img2img
• img2video
• inpainting
• instantid
• merge-face
• model-search
• reimagine
• remove-background
• remove-text
• replace-background
• txt2img-with-hiresfix
• txt2img-with-lora
• txt2img-with-refiner
• txt2video

Code Examples

cleanup

importosfromnovita_clientimportNovitaClientfromnovita_client.utilsimportbase64_to_imageclient=NovitaClient(os.getenv('NOVITA_API_KEY'), os.getenv('NOVITA_API_URI', None))
res=client.cleanup(
image="https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png",
mask="https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo_mask.png"
)
base64_to_image(res.image_file).save("./cleanup.png")

controlnet

#!/usr/bin/env python# -*- coding: UTF-8 -*-importosfromnovita_clientimportNovitaClient, Img2ImgV3Request, Img2ImgV3ControlNetUnit, ControlnetUnit, Samplers, Img2ImgV3Embeddingfromnovita_client.utilsimportbase64_to_imageclient=NovitaClient(os.getenv('NOVITA_API_KEY'), os.getenv('NOVITA_API_URI', None))
res=client.img2img_v3(
input_image="https://img.freepik.com/premium-photo/close-up-dogs-face-with-big-smile-generative-ai_900101-62851.jpg",
model_name="dreamshaper_8_93211.safetensors",
prompt="a cute dog",
sampler_name=Samplers.DPMPP_M_KARRAS,
width=512,
height=512,
steps=30,
controlnet_units=[
Img2ImgV3ControlNetUnit(
image_base64="https://img.freepik.com/premium-photo/close-up-dogs-face-with-big-smile-generative-ai_900101-62851.jpg",
model_name="control_v11f1p_sd15_depth",
strength=1.0
)
],
embeddings=[Img2ImgV3Embedding(model_name=_) for_in [
"BadDream_53202",
]],
seed=-1,
)
base64_to_image(res.images_encoded[0]).save("./img2img-controlnet.png")

img2img

importpdbimportosfromnovita_clientimportNovitaClient, Img2ImgV3ControlNetUnit, ControlNetPreprocessor, Img2ImgV3Embeddingfromnovita_client.utilsimportbase64_to_image, input_image_to_pilclient=NovitaClient(os.getenv('NOVITA_API_KEY'), os.getenv('NOVITA_API_URI', None))
res=client.img2img_v3(
model_name="MeinaHentai_V5.safetensors",
steps=30,
height=512,
width=512,
input_image="https://img.freepik.com/premium-photo/close-up-dogs-face-with-big-smile-generative-ai_900101-62851.jpg",
prompt="1 cute dog",
strength=0.5,
guidance_scale=7,
embeddings=[Img2ImgV3Embedding(model_name=_) for_in [
"bad-image-v2-39000",
"verybadimagenegative_v1.3_21434",
"BadDream_53202",
"badhandv4_16755",
"easynegative_8955.safetensors"]],
seed=-1,
sampler_name="DPM++ 2M Karras",
clip_skip=2,
# controlnet_units=[Img2ImgV3ControlNetUnit(# model_name="control_v11f1p_sd15_depth",# preprocessor="depth",# image_base64="./20240309-003206.jpeg",# strength=1.0# )]
)
base64_to_image(res.images_encoded[0]).save("./img2img.png")

img2video

importosfromnovita_clientimportNovitaClientfromnovita_client.utilsimportbase64_to_imageclient=NovitaClient(os.getenv('NOVITA_API_KEY'), os.getenv('NOVITA_API_URNOVITA_API_URII', None))
res=client.img2video(
model_name="SVD-XT",
steps=30,
frames_num=25,
image="https://replicate.delivery/pbxt/JvLi9smWKKDfQpylBYosqQRfPKZPntuAziesp0VuPjidq61n/rocket.png",
enable_frame_interpolation=True
)
withopen("test.mp4", "wb") asf:
f.write(res.video_bytes[0])

inpainting

importosimportbase64fromnovita_clientimportNovitaClientfromnovita_client.utilsimportbase64_to_imageclient=NovitaClient(os.getenv('NOVITA_API_KEY'), os.getenv('NOVITA_API_URI', None))
res=client.inpainting(
model_name="realisticVisionV40_v40VAE-inpainting_81543.safetensors",
image="https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png",
mask="https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png",
seed=1,
guidance_scale=15,
steps=20,
image_num=4,
prompt="black rabbit",
negative_prompt="white rabbit",
sampler_name="Euler a",
inpainting_full_res=1,
inpainting_full_res_padding=32,
inpainting_mask_invert=0,
initial_noise_multiplier=1,
mask_blur=1,
clip_skip=1,
strength=0.85,
)
withopen("result/result_image/inpaintingsdk.jpeg", "wb") asimage_file:
image_file.write(base64.b64decode(res.images_encoded[0]))```### instantid```pythonimportosfromnovita_clientimportNovitaClient, InstantIDControlnetUnitimportbase64if__name__=='__main__':
client=NovitaClient(os.getenv('NOVITA_API_KEY'), os.getenv('NOVITA_API_URI', None))
res=client.instant_id(
model_name="sdxlUnstableDiffusers_v8HEAVENSWRATH_133813.safetensors",
face_images=[
"https://raw.githubusercontent.com/InstantID/InstantID/main/examples/yann-lecun_resize.jpg",
],
prompt="Flat illustration, a Chinese a man, ancient style, wearing a red cloth, smile face, white skin, clean background, fireworks blooming, red lanterns",
negative_prompt="(lowres, low quality, worst quality:1.2), (text:1.2), watermark, (frame:1.2), deformed, ugly, deformed eyes, blur, out of focus, blurry, deformed cat, deformed, photo, anthropomorphic cat, monochrome, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green",
id_strength=0.8,
adapter_strength=0.8,
steps=20,
seed=42,
width=1024,
height=1024,
controlnets=[
InstantIDControlnetUnit(
model_name='controlnet-openpose-sdxl-1.0',
strength=0.4,
preprocessor='openpose',
),
InstantIDControlnetUnit(
model_name='controlnet-canny-sdxl-1.0',
strength=0.3,
preprocessor='canny',
),
],
response_image_type='jpeg',
enterprise_plan=False,
)
print('res:', res)
ifhasattr(res, 'images_encoded'):
withopen(f"instantid.png", "wb") asf:
f.write(base64.b64decode(res.images_encoded[0]))

merge-face

importosfromnovita_clientimportNovitaClientfromnovita_client.utilsimportbase64_to_imageclient=NovitaClient(os.getenv('NOVITA_API_KEY'), os.getenv('NOVITA_API_URI', None))
res=client.merge_face(
image="https://toppng.com/uploads/preview/cut-out-people-png-personas-en-formato-11563277290kozkuzsos5.png",
face_image="https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcQDy7sXtuvCNUQoQZvTbLRbX6qK9_kP3PlQfg&s",
enterprise_plan=False,
)
base64_to_image(res.image_file).save("./merge_face.png")

model-search

#!/usr/bin/env python# -*- coding: UTF-8 -*-fromnovita_clientimportNovitaClient, ModelType# get your api key refer to https://docs.novita.ai/get-started/client=NovitaClient(os.getenv('NOVITA_API_KEY'), os.getenv('NOVITA_API_URI', None))
# filter by model typeprint("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 tagsclient.models().filter_by_civi_tags('anime')
# filter by nsfwclient.models().filter_by_nsfw(False) # or True# sort by civitai downloadclient.models().sort_by_civitai_download()
# chain filtersclient.models().\
filter_by_type(ModelType.CHECKPOINT).\
filter_by_nsfw(False).\
filter_by_civitai_tags('anime')

reimagine

importosfromnovita_clientimportNovitaClientfromnovita_client.utilsimportbase64_to_imageclient=NovitaClient(os.getenv('NOVITA_API_KEY'), os.getenv('NOVITA_API_URI', None))
res=client.reimagine(
image="/home/anyisalin/develop/novita-client-python/examples/doodle-generated.png"
)
base64_to_image(res.image_file).save("./reimagine.png")

remove-background

importosfromnovita_clientimportNovitaClientfromnovita_client.utilsimportbase64_to_imageclient=NovitaClient(os.getenv('NOVITA_API_KEY'), os.getenv('NOVITA_API_URI', None))
res=client.remove_background(
image="https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png",
)
base64_to_image(res.image_file).save("./remove_background.png")

remove-text

importosfromnovita_clientimportNovitaClientfromnovita_client.utilsimportbase64_to_imageclient=NovitaClient(os.getenv('NOVITA_API_KEY'), os.getenv('NOVITA_API_URI', None))
res=client.remove_text(
image="https://images.uiiiuiii.com/wp-content/uploads/2023/07/i-banner-20230714-1.jpg"
)
base64_to_image(res.image_file).save("./remove_text.png")

replace-background

importosfromnovita_clientimportNovitaClientfromnovita_client.utilsimportbase64_to_imageclient=NovitaClient(os.getenv('NOVITA_API_KEY'), os.getenv('NOVITA_API_URI', None))
res=client.replace_background(
image="./telegram-cloud-photo-size-2-5408823814353177899-y.jpg",
prompt="in living room, Christmas tree",
)
base64_to_image(res.image_file).save("./replace_background.png")

txt2img-with-hiresfix

importosfromnovita_clientimportNovitaClient, Samplers, Txt2ImgV3HiresFixfromnovita_client.utilsimportbase64_to_imagefromPILimportImageclient=NovitaClient(os.getenv('NOVITA_API_KEY'), os.getenv('NOVITA_API_URI', None))
res=client.txt2img_v3(
model_name='dreamshaper_8_93211.safetensors',
prompt="a cute girl",
width=384,
height=512,
image_num=1,
guidance_scale=7.5,
seed=12345,
sampler_name=Samplers.EULER_A,
hires_fix=Txt2ImgV3HiresFix(
# upscaler='Latent'target_width=768,
target_height=1024,
strength=0.5
)
)
base64_to_image(res.images_encoded[0]).save("./txt2img_with_hiresfix.png")

txt2img-with-lora

#!/usr/bin/env python# -*- coding: UTF-8 -*-importosfromnovita_clientimportNovitaClient, Txt2ImgV3LoRA, Samplers, ProgressResponseStatusCode, ModelType, add_lora_to_prompt, save_imagefromnovita_client.utilsimportbase64_to_image, input_image_to_pilfromPILimportImagedefmake_image_grid(images, rows: int, cols: int, resize: int=None):
""" Prepares a single grid of images. Useful for visualization purposes. """assertlen(images) ==rows*colsifresizeisnotNone:
images= [img.resize((resize, resize)) forimginimages]
w, h=images[0].sizegrid=Image.new("RGB", size=(cols*w, rows*h))
fori, imginenumerate(images):
grid.paste(img, box=(i%cols*w, i//cols*h))
returngridclient=NovitaClient(os.getenv('NOVITA_API_KEY'), os.getenv('NOVITA_API_URI', None))
res1=client.txt2img_v3(
prompt="a photo of handsome man, close up",
image_num=1,
guidance_scale=7.0,
sampler_name=Samplers.DPMPP_M_KARRAS,
model_name="dreamshaper_8_93211.safetensors",
height=512,
width=512,
seed=1024,
)
res2=client.txt2img_v3(
prompt="a photo of handsome man, close up",
image_num=1,
guidance_scale=7.0,
sampler_name=Samplers.DPMPP_M_KARRAS,
model_name="dreamshaper_8_93211.safetensors",
height=512,
width=512,
seed=1024,
loras=[
Txt2ImgV3LoRA(
model_name="add_detail_44319",
strength=0.9,
)
]
)
make_image_grid([base64_to_image(res1.images_encoded[0]), base64_to_image(res2.images_encoded[0])], 1, 2, 512).save("./txt2img-lora-compare.png")

txt2img-with-refiner

importosfromnovita_clientimportNovitaClient, Txt2ImgV3Refiner, Samplersfromnovita_client.utilsimportbase64_to_imagefromPILimportImagedefmake_image_grid(images, rows: int, cols: int, resize: int=None):
""" Prepares a single grid of images. Useful for visualization purposes. """assertlen(images) ==rows*colsifresizeisnotNone:
images= [img.resize((resize, resize)) forimginimages]
w, h=images[0].sizegrid=Image.new("RGB", size=(cols*w, rows*h))
fori, imginenumerate(images):
grid.paste(img, box=(i%cols*w, i//cols*h))
returngridclient=NovitaClient(os.getenv('NOVITA_API_KEY'), os.getenv('NOVITA_API_URI', None))
r1=client.txt2img_v3(
model_name='sd_xl_base_1.0.safetensors',
prompt='a astronaut riding a bike on the moon',
width=1024,
height=1024,
image_num=1,
guidance_scale=7.5,
sampler_name=Samplers.EULER_A,
)
r2=client.txt2img_v3(
model_name='sd_xl_base_1.0.safetensors',
prompt='a astronaut riding a bike on the moon',
width=1024,
height=1024,
image_num=1,
guidance_scale=7.5,
sampler_name=Samplers.EULER_A,
refiner=Txt2ImgV3Refiner(
switch_at=0.7
)
)
r3=client.txt2img_v3(
model_name='sd_xl_base_1.0.safetensors',
prompt='a astronaut riding a bike on the moon',
width=1024,
height=1024,
image_num=1,
guidance_scale=7.5,
sampler_name=Samplers.EULER_A,
refiner=Txt2ImgV3Refiner(
switch_at=0.5
)
)
make_image_grid([base64_to_image(r1.images_encoded[0]), base64_to_image(r2.images_encoded[0]), base64_to_image(r3.images_encoded[0])], 1, 3, 1024).save("./txt2img-refiner-compare.png")

txt2video

importosfromnovita_clientimportNovitaClientfromnovita_client.utilsimportsave_imageclient=NovitaClient(os.getenv('NOVITA_API_KEY'), os.getenv('NOVITA_API_URI', None))
res=client.txt2video(
model_name="dreamshaper_8_93211.safetensors",
prompts= [{
"prompt": "A girl, baby, portrait, 5 years old",
"frames": 16,},
{
"prompt": "A girl, child, portrait, 10 years old",
"frames": 16,
}
],
steps=20,
guidance_scale=10,
height=512,
width=768,
clip_skip=4,
negative_prompt="a rainy day",
response_video_type="mp4",
)
save_image(res.video_bytes[0], 'output.mp4')