fantos commited on
Commit
6960db5
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1 Parent(s): 4f076f3

Update app.py

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Files changed (1) hide show
  1. app.py +20 -5
app.py CHANGED
@@ -4,11 +4,15 @@ import torch
4
  from PIL import Image
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  from diffusers import DiffusionPipeline
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  import random
 
7
 
8
  torch.backends.cudnn.deterministic = True
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  torch.backends.cudnn.benchmark = False
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  torch.backends.cuda.matmul.allow_tf32 = True
11
 
 
 
 
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  base_model = "black-forest-labs/FLUX.1-dev"
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  pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
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@@ -21,7 +25,18 @@ pipe.to("cuda")
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  MAX_SEED = 2**32-1
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  @spaces.GPU()
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- def run_lora(prompt, cfg_scale, steps, randomize_seed, seed, width, height, lora_scale, progress=gr.Progress(track_tqdm=True)):
 
 
 
 
 
 
 
 
 
 
 
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  if randomize_seed:
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  seed = random.randint(0, MAX_SEED)
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  generator = torch.Generator(device="cuda").manual_seed(seed)
@@ -33,7 +48,7 @@ def run_lora(prompt, cfg_scale, steps, randomize_seed, seed, width, height, lora
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  progress(i / steps * 100, f"Processing step {i} of {steps}...")
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  image = pipe(
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- prompt=f"{prompt} {trigger_word}",
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  num_inference_steps=steps,
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  guidance_scale=cfg_scale,
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  width=width,
@@ -75,8 +90,8 @@ with gr.Blocks(css=css) as app:
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  with gr.Column(scale=3):
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  with gr.Group(elem_classes="parameter-box"):
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  prompt = gr.TextArea(
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- label="โœ๏ธ Your Prompt",
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- placeholder="Describe the image you want to generate...",
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  lines=5
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  )
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@@ -156,7 +171,7 @@ with gr.Blocks(css=css) as app:
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  )
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158
  generate_button.click(
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- run_lora,
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  inputs=[prompt, cfg_scale, steps, randomize_seed, seed, width, height, lora_scale],
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  outputs=[result, seed]
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  )
 
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  from PIL import Image
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  from diffusers import DiffusionPipeline
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  import random
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+ from transformers import pipeline
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  torch.backends.cudnn.deterministic = True
10
  torch.backends.cudnn.benchmark = False
11
  torch.backends.cuda.matmul.allow_tf32 = True
12
 
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+ # ๋ฒˆ์—ญ ๋ชจ๋ธ ์ดˆ๊ธฐํ™”
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+ translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ko-en")
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+
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  base_model = "black-forest-labs/FLUX.1-dev"
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  pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
18
 
 
25
  MAX_SEED = 2**32-1
26
 
27
  @spaces.GPU()
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+ def translate_and_generate(prompt, cfg_scale, steps, randomize_seed, seed, width, height, lora_scale, progress=gr.Progress(track_tqdm=True)):
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+ # ํ•œ๊ธ€ ๊ฐ์ง€ ๋ฐ ๋ฒˆ์—ญ
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+ def contains_korean(text):
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+ return any(ord('๊ฐ€') <= ord(char) <= ord('ํžฃ') for char in text)
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+
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+ if contains_korean(prompt):
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+ # ํ•œ๊ธ€์„ ์˜์–ด๋กœ ๋ฒˆ์—ญ
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+ translated = translator(prompt)[0]['translation_text']
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+ actual_prompt = translated
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+ else:
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+ actual_prompt = prompt
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+
40
  if randomize_seed:
41
  seed = random.randint(0, MAX_SEED)
42
  generator = torch.Generator(device="cuda").manual_seed(seed)
 
48
  progress(i / steps * 100, f"Processing step {i} of {steps}...")
49
 
50
  image = pipe(
51
+ prompt=f"{actual_prompt} {trigger_word}",
52
  num_inference_steps=steps,
53
  guidance_scale=cfg_scale,
54
  width=width,
 
90
  with gr.Column(scale=3):
91
  with gr.Group(elem_classes="parameter-box"):
92
  prompt = gr.TextArea(
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+ label="โœ๏ธ Your Prompt (ํ•œ๊ธ€ ๋˜๋Š” ์˜์–ด)",
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+ placeholder="์ด๋ฏธ์ง€๋ฅผ ์„ค๋ช…ํ•˜์„ธ์š”... (ํ•œ๊ธ€ ์ž…๋ ฅ์‹œ ์ž๋™์œผ๋กœ ์˜์–ด๋กœ ๋ฒˆ์—ญ๋ฉ๋‹ˆ๋‹ค)",
95
  lines=5
96
  )
97
 
 
171
  )
172
 
173
  generate_button.click(
174
+ translate_and_generate,
175
  inputs=[prompt, cfg_scale, steps, randomize_seed, seed, width, height, lora_scale],
176
  outputs=[result, seed]
177
  )