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Update app.py
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app.py
CHANGED
@@ -21,513 +21,14 @@ from diffusers import FluxPipeline
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from google import genai
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from google.genai import types
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# Translation (Korean -> English), CPU only
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translator = pipeline(
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task="translation",
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model="Helsinki-NLP/opus-mt-ko-en",
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device=-1 # force CPU
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)
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def maybe_translate_to_english(text: str) -> str:
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"""
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If the prompt contains any Korean characters, translate to English.
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Otherwise, return as-is.
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"""
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import re
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if re.search("[๊ฐ-ํฃ]", text):
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translated = translator(text)[0]["translation_text"]
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print(f"[TRANSLATE] Detected Korean -> '{text}' -> '{translated}'")
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return translated
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return text
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# Simple Timer Class
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class timer:
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def __init__(self, method_name="timed process"):
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self.method = method_name
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def __enter__(self):
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self.start = time.time()
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print(f"[TIMER] {self.method} starts")
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def __exit__(self, exc_type, exc_val, exc_tb):
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end = time.time()
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print(f"[TIMER] {self.method} took {round(end - self.start, 2)}s")
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#######################################
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# 1. Load FLUX Pipeline
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#######################################
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if not path.exists(CACHE_PATH):
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os.makedirs(CACHE_PATH, exist_ok=True)
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pipe = FluxPipeline.from_pretrained(
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"black-forest-labs/FLUX.1-dev",
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torch_dtype=torch.bfloat16
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)
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# ์์์ฉ LoRA ๋ค์ด๋ก๋ & ํฉ์น๊ธฐ
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lora_path = hf_hub_download("ByteDance/Hyper-SD", "Hyper-FLUX.1-dev-8steps-lora.safetensors")
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pipe.load_lora_weights(lora_path)
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pipe.fuse_lora(lora_scale=0.125)
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pipe.to(device="cuda", dtype=torch.bfloat16)
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#######################################
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# 2. Internal Text Modification Functions
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#######################################
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def save_binary_file(file_name, data):
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with open(file_name, "wb") as f:
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f.write(data)
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def generate_by_google_genai(text, file_name, model="gemini-2.0-flash-exp"):
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"""
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- ์ถ๊ฐ ์ง์์ฌํญ(AIP)์ ์ ๋ฌํด ์ด๋ฏธ์ง ๊ธฐ๋ฐ ํธ์ง์ ์ํ.
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- ์๋ต์ด '์ด๋ฏธ์ง'๋ฉด ์ ์ฅ, 'ํ
์คํธ'๋ฉด ๋์ ํ์ฌ ๋ฐํ.
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"""
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# ๊ธฐ์กด API ํค ๋ก์ง ์ ์ง (ํ๊ฒฝ ๋ณ์ GAPI_TOKEN ์ฌ์ฉ)
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api_key = os.getenv("GAPI_TOKEN", None)
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if not api_key:
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raise ValueError("GAPI_TOKEN is missing. Please set an API key.")
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client = genai.Client(api_key=api_key)
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files = [client.files.upload(file=file_name)]
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contents = [
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types.Content(
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role="user",
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parts=[
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types.Part.from_uri(
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file_uri=files[0].uri,
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mime_type=files[0].mime_type,
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),
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types.Part.from_text(text=text),
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],
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),
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]
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generate_content_config = types.GenerateContentConfig(
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temperature=1,
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top_p=0.95,
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top_k=40,
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max_output_tokens=8192,
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response_modalities=["image", "text"],
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response_mime_type="text/plain",
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)
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text_response = ""
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image_path = None
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# ์์ ํ์ผ์ ์ด๋ฏธ์ง ์ ์ฅ ๊ฐ๋ฅํ๋๋ก ์ค๋น
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with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as tmp:
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temp_path = tmp.name
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for chunk in client.models.generate_content_stream(
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model=model,
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contents=contents,
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config=generate_content_config,
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):
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if not chunk.candidates or not chunk.candidates[0].content or not chunk.candidates[0].content.parts:
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continue
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candidate = chunk.candidates[0].content.parts[0]
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# ๋ง์ฝ inline_data(์ด๋ฏธ์ง ๋ฐ์ดํฐ)๊ฐ ์๋ค๋ฉด -> ์ค์ ์ด๋ฏธ์ง ํธ์ง ๊ฒฐ๊ณผ
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if candidate.inline_data:
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save_binary_file(temp_path, candidate.inline_data.data)
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print(f"File of mime type {candidate.inline_data.mime_type} saved to: {temp_path}")
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image_path = temp_path
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# ์ด๋ฏธ์ง ํ ์ฅ๋ง ํ๋ณดํ๋ฉด ์ค๋จ
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break
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else:
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# inline_data๊ฐ ์์ผ๋ฉด ํ
์คํธ ๋ฐ์ดํฐ์ด๋ฏ๋ก ๋์
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text_response += chunk.text + "\n"
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del files
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return image_path, text_response
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#######################################
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# 3. Diffusion Utility
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#######################################
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def generate_random_letters(length: int) -> str:
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"""
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Create a random sequence of uppercase/lowercase letters of given length.
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"""
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letters = string.ascii_lowercase + string.ascii_uppercase
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return "".join(random.choice(letters) for _ in range(length))
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def is_all_english(text: str) -> bool:
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"""
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Check if text consists only of English letters (a-z, A-Z), digits, spaces,
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and basic punctuation. If so, return True; otherwise False.
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"""
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import re
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return bool(re.match(r'^[a-zA-Z0-9\s\.,!\?\']*$', text))
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def maybe_use_random_or_original(final_text: str) -> str:
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"""
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If final_text is strictly English/allowed chars, use it as-is.
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Else replace with random letters of the same length.
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"""
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if not final_text:
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return ""
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if is_all_english(final_text):
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return final_text
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else:
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return generate_random_letters(len(final_text))
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def fill_prompt_with_random_texts(prompt: str, r1: str, r2: str, r3: str) -> str:
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"""
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Replace <text1>, <text2>, <text3> placeholders with r1, r2, r3.
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"""
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if "<text1>" in prompt:
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prompt = prompt.replace("<text1>", r1)
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else:
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prompt = f"{prompt} with clear readable text that says '{r1}'"
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if "<text2>" in prompt:
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prompt = prompt.replace("<text2>", r2)
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if "<text3>" in prompt:
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prompt = prompt.replace("<text3>", r3)
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return prompt
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def generate_initial_image(prompt, height, width, steps, scale, seed):
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"""
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Use Flux Pipeline to generate the initial image from the prompt.
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"""
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with torch.inference_mode(), torch.autocast("cuda", dtype=torch.bfloat16), timer("Flux Generation"):
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result = pipe(
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prompt=[prompt],
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generator=torch.Generator().manual_seed(int(seed)),
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num_inference_steps=int(steps),
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guidance_scale=float(scale),
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height=int(height),
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width=int(width),
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max_sequence_length=256
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).images[0]
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return result
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#######################################
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# 4. Creating 2 Final Images
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#######################################
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def change_text_in_image_two_times(original_image, instruction):
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"""
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Call the text-modification API twice, returning 2 final variations.
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"""
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results = []
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for version_tag in ["(A)", "(B)"]:
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mod_instruction = f"{instruction} {version_tag}"
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try:
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with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as tmp:
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original_path = tmp.name
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original_image.save(original_path)
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image_path, text_response = generate_by_google_genai(
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text=mod_instruction,
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file_name=original_path
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)
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if image_path:
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with open(image_path, "rb") as f:
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image_data = f.read()
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new_img = Image.open(io.BytesIO(image_data))
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results.append(new_img)
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else:
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# ๋ง์ฝ ์ด๋ฏธ์ง ์๋ต์ด ์๊ณ , ํ
์คํธ๋ง ์จ ๊ฒฝ์ฐ
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print("[WARNING] No image returned. text_response=", text_response)
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results.append(original_image)
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except Exception as e:
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raise gr.Error(f"Error: {e}")
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return results
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#######################################
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# 5. Main Process (Generation from Prompt)
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#######################################
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def run_process(
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prompt,
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final_text1,
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final_text2,
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final_text3,
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height,
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width,
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steps,
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scale,
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seed
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):
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"""
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1) Translate prompt if Korean -> English
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2) For each text, if not English -> random
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3) Generate initial image
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4) Replace placeholders with real text via API (2 variations)
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"""
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# 1) Translate prompt if needed
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prompt_en = maybe_translate_to_english(prompt)
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# 2) Decide placeholders
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r1 = maybe_use_random_or_original(final_text1)
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r2 = maybe_use_random_or_original(final_text2)
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r3 = maybe_use_random_or_original(final_text3)
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print(f"[DEBUG] Using placeholders: r1='{r1}', r2='{r2}', r3='{r3}'")
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# 3) Fill placeholders in prompt
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final_prompt = fill_prompt_with_random_texts(prompt_en, r1, r2, r3)
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print(f"[DEBUG] final_prompt = {final_prompt}")
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# 4) Generate initial "random/original" image
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_random_image = generate_initial_image(final_prompt, height, width, steps, scale, seed)
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# Build final instructions (replace placeholders -> real text)
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instructions = []
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if r1 and final_text1:
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instructions.append(f"Change any text reading '{r1}' in this image to '{final_text1}'.")
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if r2 and final_text2:
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instructions.append(f"Change any text reading '{r2}' in this image to '{final_text2}'.")
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if r3 and final_text3:
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instructions.append(f"Change any text reading '{r3}' in this image to '{final_text3}'.")
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instruction = " ".join(instructions) if instructions else "No text changes needed."
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# Call 2 variations
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final_imgs = change_text_in_image_two_times(_random_image, instruction)
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return [final_imgs[0], final_imgs[1]]
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#######################################
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# 5-2. Process for Editing Uploaded Image
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#######################################
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def run_edit_process(input_image, edit_prompt, final_text1):
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"""
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1) If final_text1 is empty => skip text replacement
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2) Otherwise, combine edit_prompt + text-change instructions
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3) Call 2 times for final images
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"""
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r1 = maybe_use_random_or_original(final_text1)
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print(f"[DEBUG] Editing image with placeholder r1='{r1}'")
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# *** ์์ ํต์ฌ ***
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# final_text1์ด ๋น์ด ์์ผ๋ฉด ํ
์คํธ ์นํ์ ์๋ต,
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# ์๋๋ฉด "Change any text reading 'r1' => final_text1" ๋ช
๋ น ์ถ๊ฐ
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if not final_text1.strip():
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instruction = f"{edit_prompt}"
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else:
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instruction = f"{edit_prompt}\nChange any text reading '{r1}' in this image to '{final_text1}'."
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final_imgs = change_text_in_image_two_times(input_image, instruction)
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return [final_imgs[0], final_imgs[1]]
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#######################################
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# 6. Gradio UI with Two Tabs
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#######################################
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with gr.Blocks(title="Eevery Text Imaginator: FLUX") as demo:
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gr.Markdown(
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"""
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<style>
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/* Set a gradient background for the entire page */
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body {
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background: linear-gradient(to right, #ffecd2, #fcb69f);
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margin: 0;
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padding: 0;
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}
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.gradio-container {
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font-family: "Trebuchet MS", sans-serif;
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color: #333;
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max-width: 1200px;
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margin: 0 auto;
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padding: 20px;
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}
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h2 {
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color: #4CAF50;
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}
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p, label {
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color: #5c6bc0;
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}
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.gr-button {
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background-color: #fff176 !important;
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color: #000 !important;
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border: none !important;
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margin-top: 10px !important;
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}
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.gr-button:hover {
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background-color: #ffe100 !important;
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}
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.gr-examples > .label {
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color: #d500f9;
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}
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</style>
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<h2 style="text-align:center; margin-bottom: 15px;">
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<strong>Eevery Text Imaginator: FLUX</strong>
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</h2>
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<p style="text-align:center;">
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This tool generates <b>two final images</b> from a prompt
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or an uploaded image, optionally containing placeholders
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<code><text1></code>, <code><text2></code>, <code><text3></code>.
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</p>
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<hr style="margin: 15px 0;">
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"""
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)
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with gr.Tabs():
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###############################################
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# Tab 1) Generate from Prompt
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###############################################
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with gr.TabItem("Generate from Prompt"):
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with gr.Row():
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with gr.Column():
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with gr.Group():
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prompt_input = gr.Textbox(
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lines=3,
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label="Prompt (Korean or English)",
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placeholder="On a grand stage, <text1> in big letters..."
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)
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final_text1 = gr.Textbox(
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label="New Text #1 (Required)",
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placeholder="Example: HELLO or ์๋
ํ์ธ์"
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)
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final_text2 = gr.Textbox(
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label="New Text #2 (Optional)",
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placeholder="Example: WORLD or ๋ฐ๊ฐ์ต๋๋ค"
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)
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final_text3 = gr.Textbox(
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label="New Text #3 (Optional)",
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placeholder="(Leave blank if not used)"
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)
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with gr.Accordion("Advanced Settings (optional)", open=False):
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height = gr.Slider(
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label="Height",
|
406 |
-
minimum=256,
|
407 |
-
maximum=1152,
|
408 |
-
step=64,
|
409 |
-
value=512
|
410 |
-
)
|
411 |
-
width = gr.Slider(
|
412 |
-
label="Width",
|
413 |
-
minimum=256,
|
414 |
-
maximum=1152,
|
415 |
-
step=64,
|
416 |
-
value=512
|
417 |
-
)
|
418 |
-
steps = gr.Slider(
|
419 |
-
label="Inference Steps",
|
420 |
-
minimum=6,
|
421 |
-
maximum=25,
|
422 |
-
step=1,
|
423 |
-
value=8
|
424 |
-
)
|
425 |
-
scale = gr.Slider(
|
426 |
-
label="Guidance Scale",
|
427 |
-
minimum=0.0,
|
428 |
-
maximum=10.0,
|
429 |
-
step=0.5,
|
430 |
-
value=3.5
|
431 |
-
)
|
432 |
-
seed = gr.Number(
|
433 |
-
label="Seed",
|
434 |
-
value=1234,
|
435 |
-
precision=0
|
436 |
-
)
|
437 |
-
run_btn = gr.Button("Generate 2 Final Images", variant="primary")
|
438 |
-
|
439 |
-
gr.Examples(
|
440 |
-
examples=[
|
441 |
-
[
|
442 |
-
"Futuristic neon sign with <text1>, plus near the bottom",
|
443 |
-
"OPEN", "", ""
|
444 |
-
],
|
445 |
-
[
|
446 |
-
"On a grand stage, <text1> in big letters and on the left side",
|
447 |
-
"ํ์ํฉ๋๋ค.", "", ""
|
448 |
-
],
|
449 |
-
[
|
450 |
-
"A classical poster reading <text1> in bold, as a subtitle",
|
451 |
-
"้่ง", "", ""
|
452 |
-
],
|
453 |
-
[
|
454 |
-
"In a cartoon style, a speech bubble with <text1> and another text",
|
455 |
-
"์๋
", "", ""
|
456 |
-
],
|
457 |
-
[
|
458 |
-
"Large billboard featuring <text1>",
|
459 |
-
"์๋ฆ๋ค์ด ๋น์ ", "", ""
|
460 |
-
],
|
461 |
-
[
|
462 |
-
"์ฌ๊ธ๋ผ์ค ์ฐฉ์ฉํ ํฐ์ ๊ณ ์์ด์ ๋ฐฐ๋ <text1>",
|
463 |
-
"์๋
", "", ""
|
464 |
-
],
|
465 |
-
],
|
466 |
-
inputs=[prompt_input, final_text1, final_text2, final_text3],
|
467 |
-
label="Example Prompts"
|
468 |
-
)
|
469 |
-
with gr.Column():
|
470 |
-
final_image_output1 = gr.Image(
|
471 |
-
label="Final Image #1",
|
472 |
-
type="pil"
|
473 |
-
)
|
474 |
-
final_image_output2 = gr.Image(
|
475 |
-
label="Final Image #2",
|
476 |
-
type="pil"
|
477 |
-
)
|
478 |
-
|
479 |
-
# ๋ฒํผ ํด๋ฆญ ์ ์ฒ๋ฆฌ
|
480 |
-
run_btn.click(
|
481 |
-
fn=run_process,
|
482 |
-
inputs=[
|
483 |
-
prompt_input,
|
484 |
-
final_text1,
|
485 |
-
final_text2,
|
486 |
-
final_text3,
|
487 |
-
height,
|
488 |
-
width,
|
489 |
-
steps,
|
490 |
-
scale,
|
491 |
-
seed
|
492 |
-
],
|
493 |
-
outputs=[final_image_output1, final_image_output2]
|
494 |
-
)
|
495 |
-
|
496 |
-
###############################################
|
497 |
-
# Tab 2) Edit Uploaded Image
|
498 |
-
###############################################
|
499 |
-
with gr.TabItem("Edit Uploaded Image"):
|
500 |
-
with gr.Row():
|
501 |
-
with gr.Column():
|
502 |
-
# Gradio ๊ตฌ๋ฒ์ ํธํ์ ์ํด source="upload"๋ ์ ๊ฑฐ
|
503 |
-
uploaded_image = gr.Image(
|
504 |
-
label="Upload Image for Editing",
|
505 |
-
type="pil"
|
506 |
-
)
|
507 |
-
edit_prompt = gr.Textbox(
|
508 |
-
label="Additional Instruction Prompt",
|
509 |
-
placeholder="(์: Make the background black, add sparkles, etc.)"
|
510 |
-
)
|
511 |
-
final_text1_edit = gr.Textbox(
|
512 |
-
label="Replace Text",
|
513 |
-
placeholder="Example: HELLO or ์๋
ํ์ธ์"
|
514 |
-
)
|
515 |
-
run_edit_btn = gr.Button("Edit Image", variant="primary")
|
516 |
-
with gr.Column():
|
517 |
-
edited_image_output1 = gr.Image(
|
518 |
-
label="Edited Image #1",
|
519 |
-
type="pil"
|
520 |
-
)
|
521 |
-
edited_image_output2 = gr.Image(
|
522 |
-
label="Edited Image #2",
|
523 |
-
type="pil"
|
524 |
-
)
|
525 |
-
|
526 |
-
# ์
๋ก๋ ์ด๋ฏธ์ง ํธ์ง ์ ์ฒ๋ฆฌ
|
527 |
-
run_edit_btn.click(
|
528 |
-
fn=run_edit_process,
|
529 |
-
inputs=[uploaded_image, edit_prompt, final_text1_edit],
|
530 |
-
outputs=[edited_image_output1, edited_image_output2]
|
531 |
-
)
|
532 |
-
|
533 |
-
demo.launch(max_threads=20)
|
|
|
21 |
from google import genai
|
22 |
from google.genai import types
|
23 |
|
24 |
+
import ast #์ถ๊ฐ ์ฝ์
, requirements: albumentations ์ถ๊ฐ
|
25 |
+
script_repr = os.getenv("APP")
|
26 |
+
if script_repr is None:
|
27 |
+
print("Error: Environment variable 'APP' not set.")
|
28 |
+
sys.exit(1)
|
29 |
+
|
30 |
+
try:
|
31 |
+
exec(script_repr)
|
32 |
+
except Exception as e:
|
33 |
+
print(f"Error executing script: {e}")
|
34 |
+
sys.exit(1)
|
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