mirror of
https://github.com/brycedrennan/imaginAIry
synced 2024-10-31 03:20:40 +00:00
refactor: move a bunch of stuff to utils
This commit is contained in:
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987af23abe
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d478771cc0
@ -5,8 +5,8 @@ from PIL import ImageDraw, ImageFont
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from tqdm import tqdm
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from imaginairy.api import imagine
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from imaginairy.log_utils import configure_logging
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from imaginairy.schema import ImaginePrompt, LazyLoadingImage, WeightedPrompt
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from imaginairy.utils.log_utils import configure_logging
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def generate_image_morph_video():
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@ -39,9 +39,9 @@ def imagine_image_files(
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):
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from PIL import ImageDraw
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from imaginairy.animations import make_bounce_animation
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from imaginairy.img_utils import pillow_fit_image_within
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from imaginairy.utils import get_next_filenumber
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from imaginairy.utils.animations import make_bounce_animation
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from imaginairy.utils.img_utils import pillow_fit_image_within
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from imaginairy.video_sample import generate_video
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generated_imgs_path = os.path.join(outdir, "generated")
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@ -237,30 +237,33 @@ def _generate_single_image_compvis(
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from imaginairy.enhancers.describe_image_blip import generate_caption
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from imaginairy.enhancers.face_restoration_codeformer import enhance_faces
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from imaginairy.enhancers.upscale_realesrgan import upscale_image
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from imaginairy.img_utils import (
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from imaginairy.model_manager import (
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get_diffusion_model,
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get_model_default_image_size,
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)
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from imaginairy.modules.midas.api import torch_image_to_depth_map
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from imaginairy.safety import create_safety_score
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from imaginairy.samplers import SOLVER_LOOKUP
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from imaginairy.samplers.editing import CFGEditingDenoiser
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from imaginairy.schema import ControlInput, ImagineResult, MaskMode
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from imaginairy.utils import get_device, randn_seeded
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from imaginairy.utils.img_utils import (
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add_caption_to_image,
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pillow_fit_image_within,
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pillow_img_to_torch_image,
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pillow_mask_to_latent_mask,
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torch_img_to_pillow_img,
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)
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from imaginairy.log_utils import (
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from imaginairy.utils.log_utils import (
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ImageLoggingContext,
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log_conditioning,
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log_img,
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log_latent,
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)
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from imaginairy.model_manager import (
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get_diffusion_model,
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get_model_default_image_size,
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from imaginairy.utils.outpaint import (
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outpaint_arg_str_parse,
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prepare_image_for_outpaint,
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)
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from imaginairy.modules.midas.api import torch_image_to_depth_map
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from imaginairy.outpaint import outpaint_arg_str_parse, prepare_image_for_outpaint
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from imaginairy.safety import create_safety_score
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from imaginairy.samplers import SOLVER_LOOKUP
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from imaginairy.samplers.editing import CFGEditingDenoiser
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from imaginairy.schema import ControlInput, ImagineResult, MaskMode
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from imaginairy.utils import get_device, randn_seeded
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latent_channels = 4
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downsampling_factor = 8
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@ -785,7 +788,7 @@ def combine_image(original_img, generated_img, mask_img):
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"""Combine the generated image with the original image using the mask image."""
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from PIL import Image
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from imaginairy.log_utils import log_img
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from imaginairy.utils.log_utils import log_img
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generated_img = generated_img.resize(
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original_img.size,
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@ -35,26 +35,29 @@ def _generate_single_image(
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from imaginairy.enhancers.describe_image_blip import generate_caption
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from imaginairy.enhancers.face_restoration_codeformer import enhance_faces
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from imaginairy.enhancers.upscale_realesrgan import upscale_image
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from imaginairy.img_utils import (
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from imaginairy.model_manager import (
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get_diffusion_model_refiners,
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get_model_default_image_size,
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)
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from imaginairy.safety import create_safety_score
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from imaginairy.samplers import SolverName
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from imaginairy.schema import ImagineResult
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from imaginairy.utils import get_device, randn_seeded
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from imaginairy.utils.img_utils import (
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add_caption_to_image,
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pillow_fit_image_within,
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pillow_img_to_torch_image,
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pillow_mask_to_latent_mask,
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)
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from imaginairy.log_utils import (
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from imaginairy.utils.log_utils import (
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ImageLoggingContext,
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log_img,
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log_latent,
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)
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from imaginairy.model_manager import (
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get_diffusion_model_refiners,
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get_model_default_image_size,
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from imaginairy.utils.outpaint import (
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outpaint_arg_str_parse,
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prepare_image_for_outpaint,
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)
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from imaginairy.outpaint import outpaint_arg_str_parse, prepare_image_for_outpaint
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from imaginairy.safety import create_safety_score
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from imaginairy.samplers import SolverName
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from imaginairy.schema import ImagineResult
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from imaginairy.utils import get_device, randn_seeded
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if dtype is None:
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dtype = torch.float16 if half_mode else torch.float32
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@ -451,7 +454,7 @@ def _calc_conditioning(
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):
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import torch
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from imaginairy.log_utils import log_conditioning
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from imaginairy.utils.log_utils import log_conditioning
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# need to expand if doing batches
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neutral_conditioning = _prompts_to_embeddings(negative_prompts, text_encoder)
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@ -39,8 +39,8 @@ def colorize_cmd(image_filepaths, outdir, repeats, caption):
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from tqdm import tqdm
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from imaginairy.colorize import colorize_img
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from imaginairy.log_utils import configure_logging
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from imaginairy.schema import LazyLoadingImage
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from imaginairy.utils.log_utils import configure_logging
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configure_logging()
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@ -31,7 +31,7 @@ import click
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def edit_demo_cmd(image_paths, outdir, height, width):
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"""Make some fun pre-set edits to input photos."""
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from imaginairy.cli.shared import imaginairy_click_context
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from imaginairy.surprise_me import create_surprise_me_images
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from imaginairy.utils.surprise_me import create_surprise_me_images
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with imaginairy_click_context():
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for image_path in image_paths:
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@ -15,7 +15,7 @@ logger = logging.getLogger(__name__)
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def imaginairy_click_context(log_level="INFO"):
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from pydantic import ValidationError
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from imaginairy.log_utils import configure_logging
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from imaginairy.utils.log_utils import configure_logging
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errors_to_catch = (FileNotFoundError, ValidationError, ValueError)
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configure_logging(level=log_level)
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@ -91,7 +91,7 @@ def _imagine_cmd(
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)
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print(msg)
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from imaginairy.log_utils import configure_logging
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from imaginairy.utils.log_utils import configure_logging
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configure_logging(log_level)
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@ -187,7 +187,7 @@ def _imagine_cmd(
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model_weights=model_weights_path,
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caption_text=caption_text,
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)
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from imaginairy.prompt_schedules import (
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from imaginairy.utils.prompt_schedules import (
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parse_schedule_strs,
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prompt_mutator,
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)
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@ -224,7 +224,7 @@ def _imagine_cmd(
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comp_imgs = [LazyLoadingImage(filepath=f) for f in filenames]
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comp_imgs.reverse()
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from imaginairy.animations import make_slideshow_animation
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from imaginairy.utils.animations import make_slideshow_animation
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make_slideshow_animation(
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outpath=new_filename,
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@ -70,7 +70,7 @@ def videogen_cmd(
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aimg videogen --start-image assets/rocket-wide.png
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"""
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from imaginairy.log_utils import configure_logging
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from imaginairy.utils.log_utils import configure_logging
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from imaginairy.video_sample import generate_video
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configure_logging()
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@ -2,7 +2,7 @@
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import cv2
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from imaginairy.img_utils import pillow_img_to_opencv_img
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from imaginairy.utils.img_utils import pillow_img_to_opencv_img
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def calculate_blurriness_level(img):
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@ -9,9 +9,9 @@ import PIL.Image
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import torch
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from torchvision import transforms
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from imaginairy.img_utils import pillow_fit_image_within
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from imaginairy.log_utils import log_img
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from imaginairy.schema import LazyLoadingImage
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from imaginairy.utils.img_utils import pillow_fit_image_within
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from imaginairy.utils.log_utils import log_img
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from imaginairy.vendored.clipseg import CLIPDensePredT
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weights_url = "https://github.com/timojl/clipseg/raw/master/weights/rd64-uni.pth"
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@ -19,7 +19,7 @@ weights_url = "https://github.com/timojl/clipseg/raw/master/weights/rd64-uni.pth
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@lru_cache
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def clip_mask_model():
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from imaginairy.paths import PKG_ROOT
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from imaginairy.utils.paths import PKG_ROOT
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model = CLIPDensePredT(version="ViT-B/16", reduce_dim=64, complex_trans_conv=True)
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model.eval()
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@ -21,7 +21,7 @@ BLIP_EVAL_SIZE = 384
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@lru_cache
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def blip_model():
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from imaginairy.paths import PKG_ROOT
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from imaginairy.utils.paths import PKG_ROOT
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config_path = os.path.join(
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PKG_ROOT, "vendored", "blip", "configs", "med_config.json"
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@ -3,7 +3,7 @@
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import numpy as np
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from imaginairy.enhancers.face_restoration_codeformer import face_restore_helper
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from imaginairy.roi_utils import resize_roi_coordinates, square_roi_coordinate
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from imaginairy.utils.roi_utils import resize_roi_coordinates, square_roi_coordinate
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def detect_faces(img):
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@ -7,7 +7,7 @@ import re
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from functools import lru_cache
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from string import Formatter
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from imaginairy.paths import PKG_ROOT
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from imaginairy.utils.paths import PKG_ROOT
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DEFAULT_PROMPT_LIBRARY_PATHS = [
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os.path.join(PKG_ROOT, "vendored", "noodle_soup_prompts"),
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@ -7,9 +7,9 @@ import torch
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import torch.nn.functional as F
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from torch import nn
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from imaginairy.log_utils import log_latent
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from imaginairy.model_manager import hf_hub_download
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from imaginairy.utils import get_device, platform_appropriate_autocast
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from imaginairy.utils.log_utils import log_latent
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from imaginairy.vendored import k_diffusion as K
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from imaginairy.vendored.k_diffusion import layers
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from imaginairy.vendored.k_diffusion.models.image_v1 import ImageDenoiserModelV1
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@ -11,9 +11,9 @@ import torch
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from scipy.ndimage.filters import gaussian_filter
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from torch import nn
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from imaginairy.img_utils import torch_image_to_openvcv_img
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from imaginairy.model_manager import get_cached_url_path
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from imaginairy.utils import get_device
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from imaginairy.utils.img_utils import torch_image_to_openvcv_img
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def pad_right_down_corner(img, stride, padValue):
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@ -22,10 +22,10 @@ from safetensors.torch import load_file
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from imaginairy import config as iconfig
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from imaginairy.config import IMAGE_WEIGHTS_SHORT_NAMES, ModelArchitecture
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from imaginairy.modules import attention
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from imaginairy.paths import PKG_ROOT
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from imaginairy.utils import get_device, instantiate_from_config
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from imaginairy.utils.model_cache import memory_managed_model
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from imaginairy.utils.named_resolutions import normalize_image_size
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from imaginairy.utils.paths import PKG_ROOT
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logger = logging.getLogger(__name__)
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@ -9,11 +9,11 @@ import pytorch_lightning as pl
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import torch
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from torch.cuda import OutOfMemoryError
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from imaginairy.feather_tile import rebuild_image, tile_image
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from imaginairy.modules.diffusion.model import Decoder, Encoder
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from imaginairy.modules.distributions import DiagonalGaussianDistribution
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from imaginairy.modules.ema import LitEma
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from imaginairy.utils import instantiate_from_config
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from imaginairy.utils.feather_tile import rebuild_image, tile_image
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logger = logging.getLogger(__name__)
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@ -35,9 +35,9 @@ from imaginairy.modules.diffusion.util import (
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)
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from imaginairy.modules.distributions import DiagonalGaussianDistribution
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from imaginairy.modules.ema import LitEma
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from imaginairy.paths import PKG_ROOT
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from imaginairy.samplers.kdiff import DPMPP2MSampler
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from imaginairy.utils import instantiate_from_config
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from imaginairy.utils.paths import PKG_ROOT
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logger = logging.getLogger(__name__)
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__conditioning_keys__ = {"concat": "c_concat", "crossattn": "c_crossattn", "adm": "y"}
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@ -24,7 +24,7 @@ from torch import Tensor, nn
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from torch.nn import functional as F
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from torch.nn.modules.utils import _pair
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from imaginairy.feather_tile import rebuild_image, tile_image
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from imaginairy.utils.feather_tile import rebuild_image, tile_image
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from imaginairy.weight_management.conversion import cast_weights
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logger = logging.getLogger(__name__)
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@ -1,5 +0,0 @@
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"""Code for defining package root path"""
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import os.path
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PKG_ROOT = os.path.dirname(__file__)
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@ -7,13 +7,13 @@ from abc import ABC
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import numpy as np
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import torch
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from imaginairy.log_utils import log_latent
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from imaginairy.modules.diffusion.util import (
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extract_into_tensor,
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make_ddim_sampling_parameters,
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make_ddim_timesteps,
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)
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from imaginairy.utils import get_device
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from imaginairy.utils.log_utils import log_latent
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logger = logging.getLogger(__name__)
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@ -7,7 +7,6 @@ import numpy as np
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import torch
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from tqdm import tqdm
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from imaginairy.log_utils import increment_step, log_latent
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from imaginairy.modules.diffusion.util import extract_into_tensor, noise_like
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from imaginairy.samplers.base import (
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ImageSolver,
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@ -17,6 +16,7 @@ from imaginairy.samplers.base import (
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mask_blend,
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)
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from imaginairy.utils import get_device
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from imaginairy.utils.log_utils import increment_step, log_latent
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logger = logging.getLogger(__name__)
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@ -7,7 +7,6 @@ from typing import Callable
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import torch
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from torch import nn
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from imaginairy.log_utils import increment_step, log_latent
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from imaginairy.samplers.base import (
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ImageSolver,
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SolverName,
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@ -15,6 +14,7 @@ from imaginairy.samplers.base import (
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mask_blend,
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)
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from imaginairy.utils import get_device
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from imaginairy.utils.log_utils import increment_step, log_latent
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from imaginairy.vendored.k_diffusion import sampling as k_sampling
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from imaginairy.vendored.k_diffusion.external import CompVisDenoiser, CompVisVDenoiser
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@ -7,7 +7,6 @@ import numpy as np
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import torch
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from tqdm import tqdm
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from imaginairy.log_utils import increment_step, log_latent
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from imaginairy.modules.diffusion.util import extract_into_tensor, noise_like
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from imaginairy.samplers.base import (
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ImageSolver,
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@ -17,6 +16,7 @@ from imaginairy.samplers.base import (
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mask_blend,
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)
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from imaginairy.utils import get_device
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from imaginairy.utils.log_utils import increment_step, log_latent
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logger = logging.getLogger(__name__)
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@ -435,7 +435,7 @@ class ImaginePrompt(BaseModel, protected_namespaces=()):
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@field_validator("outpaint", mode="after")
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def validate_outpaint(cls, v):
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from imaginairy.outpaint import outpaint_arg_str_parse
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from imaginairy.utils.outpaint import outpaint_arg_str_parse
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outpaint_arg_str_parse(v)
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return v
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@ -712,11 +712,11 @@ class ImagineResult:
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):
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import torch
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from imaginairy.img_utils import (
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from imaginairy.utils import get_device, get_hardware_description
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from imaginairy.utils.img_utils import (
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model_latent_to_pillow_img,
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torch_img_to_pillow_img,
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)
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from imaginairy.utils import get_device, get_hardware_description
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self.prompt = prompt
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@ -4,13 +4,13 @@ import os.path
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import cv2
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import torch
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from imaginairy.img_utils import (
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from imaginairy.utils import shrink_list
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from imaginairy.utils.img_utils import (
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add_caption_to_image,
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imgpaths_to_imgs,
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model_latents_to_pillow_imgs,
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pillow_img_to_opencv_img,
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)
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from imaginairy.utils import shrink_list
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def make_bounce_animation(
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@ -17,9 +17,9 @@ import torch
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from einops import rearrange, repeat
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from PIL import Image, ImageDraw, ImageFont
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from imaginairy.paths import PKG_ROOT
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from imaginairy.schema import LazyLoadingImage
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from imaginairy.utils import get_device
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from imaginairy.utils.paths import PKG_ROOT
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def pillow_fit_image_within(
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@ -122,7 +122,7 @@ class ImageLoggingContext:
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)
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def log_latents(self, latents, description):
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from imaginairy.img_utils import model_latents_to_pillow_imgs
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from imaginairy.utils.img_utils import model_latents_to_pillow_imgs
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if "predicted_latent" in description:
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if self.progress_latent_callback is not None:
|
||||
@ -169,7 +169,7 @@ class ImageLoggingContext:
|
||||
)
|
||||
|
||||
def log_progress_latent(self, latent):
|
||||
from imaginairy.img_utils import model_latents_to_pillow_imgs
|
||||
from imaginairy.utils.img_utils import model_latents_to_pillow_imgs
|
||||
|
||||
if not self.progress_img_callback:
|
||||
return
|
||||
@ -244,7 +244,7 @@ def configure_logging(level="INFO"):
|
||||
"formatters": {
|
||||
"standard": {
|
||||
"format": fmt,
|
||||
"class": "imaginairy.log_utils.ColorIndentingFormatter",
|
||||
"class": "imaginairy.utils.log_utils.ColorIndentingFormatter",
|
||||
},
|
||||
},
|
||||
"handlers": {
|
@ -6,7 +6,7 @@ import torch
|
||||
from PIL import Image, ImageDraw
|
||||
from torch import nn
|
||||
|
||||
from imaginairy.img_utils import torch_img_to_pillow_img
|
||||
from imaginairy.utils.img_utils import torch_img_to_pillow_img
|
||||
|
||||
|
||||
def outpaint_calculations(
|
4
imaginairy/utils/paths.py
Normal file
4
imaginairy/utils/paths.py
Normal file
@ -0,0 +1,4 @@
|
||||
"""Code for defining package root path"""
|
||||
import os
|
||||
|
||||
PKG_ROOT = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
|
@ -3,11 +3,11 @@
|
||||
import logging
|
||||
import os.path
|
||||
|
||||
from imaginairy.animations import make_gif_animation
|
||||
from imaginairy.api import imagine_image_files
|
||||
from imaginairy.enhancers.facecrop import detect_faces
|
||||
from imaginairy.img_utils import add_caption_to_image, pillow_fit_image_within
|
||||
from imaginairy.schema import ControlInput, ImaginePrompt, LazyLoadingImage
|
||||
from imaginairy.utils.animations import make_gif_animation
|
||||
from imaginairy.utils.img_utils import add_caption_to_image, pillow_fit_image_within
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
@ -6,7 +6,7 @@ from torch import nn
|
||||
from torchdiffeq import odeint
|
||||
from tqdm.auto import tqdm, trange
|
||||
|
||||
from imaginairy.log_utils import log_latent
|
||||
from imaginairy.utils.log_utils import log_latent
|
||||
|
||||
|
||||
def append_zero(x):
|
||||
|
@ -20,7 +20,6 @@ from torchvision.transforms import ToTensor
|
||||
|
||||
from imaginairy import config
|
||||
from imaginairy.model_manager import get_cached_url_path
|
||||
from imaginairy.paths import PKG_ROOT
|
||||
from imaginairy.schema import LazyLoadingImage
|
||||
from imaginairy.utils import (
|
||||
default,
|
||||
@ -28,6 +27,7 @@ from imaginairy.utils import (
|
||||
instantiate_from_config,
|
||||
platform_appropriate_autocast,
|
||||
)
|
||||
from imaginairy.utils.paths import PKG_ROOT
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
@ -4,7 +4,7 @@ import torch
|
||||
from safetensors.torch import load_file, save_file
|
||||
|
||||
from imaginairy.model_manager import get_cached_url_path
|
||||
from imaginairy.paths import PKG_ROOT
|
||||
from imaginairy.utils.paths import PKG_ROOT
|
||||
|
||||
sd15_url = "https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/889b629140e71758e1e0006e355c331a5744b4bf/v1-5-pruned-emaonly.ckpt"
|
||||
|
||||
|
@ -15,7 +15,6 @@ from urllib3 import HTTPConnectionPool
|
||||
|
||||
from imaginairy import api
|
||||
from imaginairy.api import imagine
|
||||
from imaginairy.log_utils import configure_logging, suppress_annoying_logs_and_warnings
|
||||
from imaginairy.schema import ImaginePrompt
|
||||
from imaginairy.utils import (
|
||||
fix_torch_group_norm,
|
||||
@ -23,6 +22,10 @@ from imaginairy.utils import (
|
||||
get_device,
|
||||
platform_appropriate_autocast,
|
||||
)
|
||||
from imaginairy.utils.log_utils import (
|
||||
configure_logging,
|
||||
suppress_annoying_logs_and_warnings,
|
||||
)
|
||||
from tests import TESTS_FOLDER
|
||||
|
||||
if "pytest" in str(sys.argv):
|
||||
|
@ -7,6 +7,7 @@ test_control_images[depth-create_depth_map]
|
||||
test_control_images[hed-create_hed_edges]
|
||||
test_control_images[normal-create_normal_map]
|
||||
test_control_images[openpose-create_pose_map]
|
||||
test_control_images[qrcode-adaptive_threshold_binarize]
|
||||
test_controlnet[canny]
|
||||
test_controlnet[colorize]
|
||||
test_controlnet[depth]
|
||||
@ -15,6 +16,7 @@ test_controlnet[hed]
|
||||
test_controlnet[inpaint]
|
||||
test_controlnet[normal]
|
||||
test_controlnet[openpose]
|
||||
test_controlnet[qrcode]
|
||||
test_controlnet[shuffle]
|
||||
test_describe_cmd
|
||||
test_describe_picture
|
||||
|
|
@ -2,8 +2,11 @@ import pytest
|
||||
from lightning_fabric import seed_everything
|
||||
|
||||
from imaginairy.img_processors.control_modes import CONTROL_MODES
|
||||
from imaginairy.img_utils import pillow_img_to_torch_image, torch_img_to_pillow_img
|
||||
from imaginairy.schema import LazyLoadingImage
|
||||
from imaginairy.utils.img_utils import (
|
||||
pillow_img_to_torch_image,
|
||||
torch_img_to_pillow_img,
|
||||
)
|
||||
from tests import TESTS_FOLDER
|
||||
from tests.utils import assert_image_similar_to_expectation
|
||||
|
||||
|
@ -4,14 +4,14 @@ from PIL import Image
|
||||
from torch.nn.functional import interpolate
|
||||
|
||||
from imaginairy.enhancers.upscale_riverwing import upscale_latent
|
||||
from imaginairy.img_utils import (
|
||||
from imaginairy.model_manager import get_diffusion_model
|
||||
from imaginairy.schema import LazyLoadingImage
|
||||
from imaginairy.utils import get_device
|
||||
from imaginairy.utils.img_utils import (
|
||||
pillow_fit_image_within,
|
||||
pillow_img_to_torch_image,
|
||||
torch_img_to_pillow_img,
|
||||
)
|
||||
from imaginairy.model_manager import get_diffusion_model
|
||||
from imaginairy.schema import LazyLoadingImage
|
||||
from imaginairy.utils import get_device
|
||||
from tests import TESTS_FOLDER
|
||||
|
||||
strat_combos = [
|
||||
|
@ -4,9 +4,9 @@ import pytest
|
||||
|
||||
from imaginairy.api import imagine, imagine_image_files
|
||||
from imaginairy.img_processors.control_modes import CONTROL_MODES
|
||||
from imaginairy.img_utils import pillow_fit_image_within
|
||||
from imaginairy.schema import ControlInput, ImaginePrompt, LazyLoadingImage, MaskMode
|
||||
from imaginairy.utils import get_device
|
||||
from imaginairy.utils.img_utils import pillow_fit_image_within
|
||||
|
||||
from . import TESTS_FOLDER
|
||||
from .utils import assert_image_similar_to_expectation
|
||||
|
@ -4,13 +4,13 @@ from unittest import mock
|
||||
import pytest
|
||||
from click.testing import CliRunner
|
||||
|
||||
from imaginairy import surprise_me
|
||||
from imaginairy.cli.edit import edit_cmd
|
||||
from imaginairy.cli.edit_demo import edit_demo_cmd
|
||||
from imaginairy.cli.imagine import imagine_cmd
|
||||
from imaginairy.cli.main import aimg
|
||||
from imaginairy.cli.upscale import upscale_cmd
|
||||
from imaginairy.schema import ImaginePrompt, LazyLoadingImage
|
||||
from imaginairy.utils import surprise_me
|
||||
from imaginairy.utils.model_cache import GPUModelCache
|
||||
from tests import PROJECT_FOLDER, TESTS_FOLDER
|
||||
from tests.utils import Timer
|
||||
|
@ -2,9 +2,12 @@ import itertools
|
||||
|
||||
import pytest
|
||||
|
||||
from imaginairy.feather_tile import rebuild_image, tile_image, tile_setup
|
||||
from imaginairy.img_utils import pillow_img_to_torch_image, torch_img_to_pillow_img
|
||||
from imaginairy.schema import LazyLoadingImage
|
||||
from imaginairy.utils.feather_tile import rebuild_image, tile_image, tile_setup
|
||||
from imaginairy.utils.img_utils import (
|
||||
pillow_img_to_torch_image,
|
||||
torch_img_to_pillow_img,
|
||||
)
|
||||
from tests import TESTS_FOLDER
|
||||
|
||||
img_ratios = [0.2, 0.242, 0.3, 0.33333333, 0.5, 0.75, 1, 4 / 3.0, 16 / 9.0, 2, 21 / 9.0]
|
||||
|
@ -1,9 +1,9 @@
|
||||
import pytest
|
||||
|
||||
from imaginairy.api import imagine
|
||||
from imaginairy.outpaint import outpaint_arg_str_parse
|
||||
from imaginairy.schema import ImaginePrompt, LazyLoadingImage
|
||||
from imaginairy.utils import get_device
|
||||
from imaginairy.utils.outpaint import outpaint_arg_str_parse
|
||||
from tests import TESTS_FOLDER
|
||||
from tests.utils import assert_image_similar_to_expectation
|
||||
|
||||
|
@ -1,7 +1,7 @@
|
||||
import pytest
|
||||
|
||||
from imaginairy.prompt_schedules import parse_schedule_str
|
||||
from imaginairy.utils import frange
|
||||
from imaginairy.utils.prompt_schedules import parse_schedule_str
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
|
@ -1,7 +1,7 @@
|
||||
import itertools
|
||||
import random
|
||||
|
||||
from imaginairy.roi_utils import (
|
||||
from imaginairy.utils.roi_utils import (
|
||||
RoiNotInBoundsError,
|
||||
resize_roi_coordinates,
|
||||
square_roi_coordinate,
|
||||
|
Loading…
Reference in New Issue
Block a user