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import os
import filelock
from diffusers import DiffusionPipeline
import torch
from src.utils import makedirs
from src.vision.sdxl_turbo import get_device
def get_pipe_make_image(gpu_id):
device = get_device(gpu_id)
pipe = DiffusionPipeline.from_pretrained(
# "playgroundai/playground-v2-1024px-aesthetic",
"playgroundai/playground-v2.5-1024px-aesthetic",
torch_dtype=torch.float16,
use_safetensors=True,
add_watermarker=False,
variant="fp16"
).to(device)
return pipe
def make_image(prompt, filename=None, gpu_id='auto', pipe=None,
image_guidance_scale=5.0, # 5 is optimal for playv2.5
image_size="1024x1024",
image_quality='standard',
image_num_inference_steps=50,
max_sequence_length=512):
if pipe is None:
pipe = get_pipe_make_image(gpu_id=gpu_id)
if image_quality == 'manual':
# listen to guidance_scale and num_inference_steps passed in
pass
else:
if image_quality == 'quick':
image_num_inference_steps = 10
image_size = "512x512"
elif image_quality == 'standard':
image_num_inference_steps = 20
elif image_quality == 'hd':
image_num_inference_steps = 50
lock_type = 'image'
base_path = os.path.join('locks', 'image_locks')
base_path = makedirs(base_path, exist_ok=True, tmp_ok=True, use_base=True)
lock_file = os.path.join(base_path, "%s.lock" % lock_type)
makedirs(os.path.dirname(lock_file)) # ensure made
with filelock.FileLock(lock_file):
image = pipe(prompt=prompt,
height=int(image_size.lower().split('x')[0]),
width=int(image_size.lower().split('x')[1]),
num_inference_steps=image_num_inference_steps,
max_sequence_length=max_sequence_length,
guidance_scale=image_guidance_scale,
).images[0]
if filename:
image.save(filename)
return filename
return image
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