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import torch |
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import os |
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from huggingface_hub import HfApi |
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from pathlib import Path |
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from diffusers.utils import load_image |
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import cv2 |
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from PIL import Image |
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import numpy as np |
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from diffusers import ( |
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ControlNetModel, |
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EulerDiscreteScheduler, |
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StableDiffusionControlNetPipeline, |
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StableDiffusionXLControlNetPipeline, |
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UniPCMultistepScheduler, |
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) |
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import sys |
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checkpoint = sys.argv[1] |
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prompts = [ |
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"beautiful room", |
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"a photo-realistic image of two paradise birds", |
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"a snowy house behind a forest", |
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"a couple watching a romantic sunset", |
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"boats in the Amazonas", |
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"a photo of a beautiful face of a woman", |
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"a skater in Brooklyn", |
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"a tornado in Iowa" |
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] |
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sd_xl = "control_v11p" not in checkpoint |
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if sd_xl: |
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base_ckpt = "stabilityai/stable-diffusion-xl-base-0.9" |
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controlnet = ControlNetModel.from_pretrained(checkpoint, torch_dtype=torch.float16) |
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pipe = StableDiffusionXLControlNetPipeline.from_pretrained( |
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base_ckpt, controlnet=controlnet, torch_dtype=torch.float16 |
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) |
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size = 1024 |
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else: |
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base_ckpt = "runwayml/stable-diffusion-v1-5" |
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controlnet = ControlNetModel.from_pretrained(checkpoint, torch_dtype=torch.float16) |
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pipe = StableDiffusionControlNetPipeline.from_pretrained( |
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base_ckpt, controlnet=controlnet, torch_dtype=torch.float16 |
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) |
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size = 512 |
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import ipdb; ipdb.set_trace() |
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pipe.to("cuda") |
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for i in range(8): |
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for seed in range(4): |
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image = load_image( |
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f"https://huggingface.co/datasets/patrickvonplaten/webdatasets_images/resolve/main/image_{i}.png" |
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) |
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image = image.resize((size, size)) |
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prompt = prompts[i] |
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image = np.array(image) |
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low_threshold = 100 |
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high_threshold = 200 |
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image = cv2.Canny(image, low_threshold, high_threshold) |
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image = image[:, :, None] |
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image = np.concatenate([image, image, image], axis=2) |
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canny_image = Image.fromarray(image) |
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generator = torch.manual_seed(seed) |
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out_image = pipe(prompt, generator=generator, num_inference_steps=20, image=canny_image, controlnet_conditioning_scale=1.0).images[0] |
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path = os.path.join(Path.home(), "images", "control_sdxl", f"{i}_{seed}.png") |
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path_in_repo = "/".join(path.split("/")[-2:]) |
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out_image.save(path) |
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api = HfApi() |
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api.upload_file( |
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path_or_fileobj=path, |
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path_in_repo=path_in_repo, |
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repo_id="patrickvonplaten/images", |
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repo_type="dataset", |
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) |
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print(f"https://huggingface.co/datasets/patrickvonplaten/images/blob/main/control_sdxl/{i}_{seed}.png") |
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