Stable diffusion img2img

In [ ]:

!git clone https://github.com/soumik12345/wandb-addons
!pip install ./wandb-addons[huggingface]

!git clone https://github.com/soumik12345/wandb-addons !pip install ./wandb-addons[huggingface]

In [ ]:

import requests
import torch
from PIL import Image
from io import BytesIO

from diffusers import StableDiffusionImg2ImgPipeline

from wandb_addons.diffusers import get_wandb_callback

import requests import torch from PIL import Image from io import BytesIO from diffusers import StableDiffusionImg2ImgPipeline from wandb_addons.diffusers import get_wandb_callback

In [ ]:

pipe = StableDiffusionImg2ImgPipeline.from_pretrained(
    "runwayml/stable-diffusion-v1-5", torch_dtype=torch.float16
)
pipe = pipe.to("cuda")

pipe = StableDiffusionImg2ImgPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", torch_dtype=torch.float16 ) pipe = pipe.to("cuda")

In [ ]:

url = "https://raw.githubusercontent.com/CompVis/stable-diffusion/main/assets/stable-samples/img2img/sketch-mountains-input.jpg"

response = requests.get(url)
init_image = Image.open(BytesIO(response.content)).convert("RGB")
init_image = init_image.resize((768, 512))

prompt = "A fantasy landscape, trending on artstation"

url = "https://raw.githubusercontent.com/CompVis/stable-diffusion/main/assets/stable-samples/img2img/sketch-mountains-input.jpg" response = requests.get(url) init_image = Image.open(BytesIO(response.content)).convert("RGB") init_image = init_image.resize((768, 512)) prompt = "A fantasy landscape, trending on artstation"

In [ ]:

num_images_per_prompt = 1
num_inference_steps = 50
strength = 0.75

callback = get_wandb_callback(
    pipeline=pipe, prompt=prompt,
    input_images=init_image,
    wandb_project="diffusers-2",
    wandb_entity="geekyrakshit",
    weave_mode=True,
    num_images_per_prompt=num_images_per_prompt,
    num_inference_steps=num_inference_steps,
    strength=strength,
)

results = pipe(
    prompt=prompt,
    image=init_image,
    strength=strength,
    num_images_per_prompt=num_images_per_prompt,
    num_inference_steps=num_inference_steps,
    callback=callback
)

num_images_per_prompt = 1 num_inference_steps = 50 strength = 0.75 callback = get_wandb_callback( pipeline=pipe, prompt=prompt, input_images=init_image, wandb_project="diffusers-2", wandb_entity="geekyrakshit", weave_mode=True, num_images_per_prompt=num_images_per_prompt, num_inference_steps=num_inference_steps, strength=strength, ) results = pipe( prompt=prompt, image=init_image, strength=strength, num_images_per_prompt=num_images_per_prompt, num_inference_steps=num_inference_steps, callback=callback )