recoilme

from diffusers import StableDiffusionXLPipeline
from sd_embed.embedding_funcs import get_weighted_text_embeddings_sdxl
from sd_embed.embedding_funcs import get_weighted_text_embeddings_sdxl_2p
from sd_embed.embedding_funcs import group_tokens_and_weights
from sd_embed.prompt_parser import parse_prompt_attention
from diffusers import DiffusionPipeline,EulerAncestralDiscreteScheduler
from transformers import CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers.utils import make_image_grid
import torch, gc

recoilme

azureuser@aiartlab-1:~$ python3 -m pip freeze
absl-py==2.1.0
accelerate==0.25.0
aiohttp==3.9.5
aiosignal==1.3.1
altair==4.2.2
async-timeout==4.0.3
attrs==21.2.0
Automat==20.2.0
Babel==2.8.0

recoilme

from diffusers import DiffusionPipeline,EulerAncestralDiscreteScheduler
from transformers import CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
import torch

MODEL_PATH = "models/colorfulxl"
pipe = DiffusionPipeline.from_pretrained(
    MODEL_PATH,
    text_encoder=None, tokenizer=None,
    text_encoder_2=None, tokenizer_2=None,
    torch_dtype=torch.float16,

recoilme

from diffusers import StableDiffusionXLPipeline
from sd_embed.embedding_funcs import get_weighted_text_embeddings_sdxl
from sd_embed.embedding_funcs import get_weighted_text_embeddings_sdxl_2p
from sd_embed.prompt_parser import parse_prompt_attention
from diffusers import DiffusionPipeline,EulerAncestralDiscreteScheduler
from transformers import CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers.utils import make_image_grid
import torch

MODEL_PATH = "models/colorfulxl"

recoilme

from diffusers import DiffusionPipeline,EulerAncestralDiscreteScheduler
from transformers import CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
import torch

MODEL_PATH = "models/colorfulxl"
pipe = DiffusionPipeline.from_pretrained(
    MODEL_PATH,
    text_encoder=None, tokenizer=None,
    text_encoder_2=None, tokenizer_2=None,
    torch_dtype=torch.float16,

recoilme

recoilme

[{"prompt":"An ancient man is riding in a carriage along a mountain road.","txt":"Venerable man journeys in ancient mountains. Carriage creaks, revealing deep wisdom. Twilight paints dreamlike tableau.","_id":"65b7ba0cfb9aff6d419a368e"},
{"prompt":"Great Wall of China","txt":"Ancient wall, setting sun, breathtaking beauty.","_id":"65b7b89ffb9aff6d419a3688"},
{"prompt":"A resident of the mountains is riding in a carriage along a rocky road","txt":"Mountaineer finds solace in antique carriage, rugged path of rocks, rustic charm, creaking wheels, calm resolve, beautiful mountains, untamed road, orange sunset, approaching night.","_id":"65b7b71ffb9aff6d419a3684"},
{"prompt":"A person in primitive clothing traveling on Earth. Their hands hold simple tools reflecting their primitive wisdom. They stand under a breathtaking sunset, painting the sky in beautiful shades. Mountains in the background and a winding river complete the lush landscape. Ancient creatures can be seen in the distance, seemingly unaware of these

recoilme

recoilme

import cv2
import os
import time
import mediapipe as mp
import numpy as np

def extract_faces(image):
    center_faces = []
    BaseOptions = mp.tasks.BaseOptions
    FaceDetector = mp.tasks.vision.FaceDetector

recoilme

import cv2
import numpy as np
import dlib
import mediapipe as mp
import argparse
import torch
from diffusers import StableDiffusionImg2ImgPipeline
from diffusers import EulerAncestralDiscreteScheduler
from typing import Any, Callable, Dict, List, Optional, Union
import PIL