81 lines
2.3 KiB
Python
81 lines
2.3 KiB
Python
import threading
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buffer = []
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outputs = []
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def worker():
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global buffer, outputs
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import os
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import time
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import random
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import modules.default_pipeline as pipeline
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import modules.path
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from PIL import Image
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from modules.sdxl_styles import apply_style, aspect_ratios
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from modules.util import generate_temp_filename
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def handler(task):
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prompt, negative_prompt, style_selction, performance_selction, \
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aspect_ratios_selction, image_number, image_seed, base_model_name, refiner_model_name, \
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l1, w1, l2, w2, l3, w3, l4, w4, l5, w5 = task
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loras = [(l1, w1), (l2, w2), (l3, w3), (l4, w4), (l5, w5)]
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pipeline.refresh_base_model(base_model_name)
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pipeline.refresh_refiner_model(refiner_model_name)
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pipeline.refresh_loras(loras)
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pipeline.clean_prompt_cond_caches()
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p_txt, n_txt = apply_style(style_selction, prompt, negative_prompt)
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if performance_selction == 'Speed':
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steps = 30
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switch = 20
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else:
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steps = 60
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switch = 40
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width, height = aspect_ratios[aspect_ratios_selction]
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results = []
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seed = image_seed
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if not isinstance(seed, int) or seed < 0 or seed > 65535:
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seed = random.randint(1, 65535)
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all_steps = steps * image_number
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def callback(step, x0, x, total_steps, y):
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done_steps = i * steps + step
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outputs.append(['preview', (
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int(100.0 * float(done_steps) / float(all_steps)),
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f'Step {step}/{total_steps} in the {i}-th Sampling',
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y)])
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for i in range(image_number):
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imgs = pipeline.process(p_txt, n_txt, steps, switch, width, height, seed, callback=callback)
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for x in imgs:
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local_temp_filename = generate_temp_filename(folder=modules.path.temp_outputs_path, extension='png')
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os.makedirs(os.path.dirname(local_temp_filename), exist_ok=True)
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Image.fromarray(x).save(local_temp_filename)
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seed += 1
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results += imgs
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outputs.append(['results', results])
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return
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while True:
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time.sleep(0.01)
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if len(buffer) > 0:
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task = buffer.pop(0)
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handler(task)
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pass
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threading.Thread(target=worker, daemon=True).start()
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