Merge remote-tracking branch 'upstream/main'

app.py

@@ -1,278 +0,0 @@
-import logging
-import gradio as gr
-import numpy as np
-import cv2
-import os
-import base64
-
-from try_on_diffusion_client import TryOnDiffusionClient
-
-LOG_LEVEL = logging.INFO
-LOG_FORMAT = "%(asctime)s %(thread)-8s %(name)-16s %(levelname)-8s %(message)s"
-LOG_DATE_FORMAT = "%Y-%m-%d %H:%M:%S"
-
-EXAMPLE_PATH = os.path.join(os.path.dirname(__file__), "examples")
-
-API_URL = os.getenv("TRY_ON_DIFFUSION_DEMO_API_URL", "http://localhost:8000")
-API_KEY = os.getenv("TRY_ON_DIFFUSION_DEMO_API_KEY", "")
-
-SHOW_RAPIDAPI_LINK = os.getenv("TRY_ON_DIFFUSION_DEMO_SHOW_RAPIDAPI_LINK", "1") == "1"
-
-CONCURRENCY_LIMIT = int(os.getenv("TRY_ON_DIFFUSION_DEMO_CONCURRENCY_LIMIT", "2"))
-
-logging.basicConfig(level=LOG_LEVEL, format=LOG_FORMAT, datefmt=LOG_DATE_FORMAT)
-
-client = TryOnDiffusionClient(base_url=API_URL, api_key=API_KEY)
-
-
-def get_image_base64(file_name: str) -> str:
-    _, ext = os.path.splitext(file_name.lower())
-
-    content_type = "image/jpeg"
-
-    if ext == ".png":
-        content_type = "image/png"
-    elif ext == ".webp":
-        content_type = "image/webp"
-    elif ext == ".gif":
-        content_type = "image/gif"
-
-    with open(file_name, "rb") as f:
-        return f"data:{content_type};base64," + base64.b64encode(f.read()).decode("utf-8")
-
-
-def get_examples(example_dir: str) -> list[str]:
-    file_list = [f for f in os.listdir(os.path.join(EXAMPLE_PATH, example_dir)) if f.endswith(".jpg")]
-    file_list.sort()
-
-    return [os.path.join(EXAMPLE_PATH, example_dir, f) for f in file_list]
-
-
-def try_on(
-    clothing_image: np.ndarray = None,
-    clothing_prompt: str = None,
-    avatar_image: np.ndarray = None,
-    avatar_prompt: str = None,
-    avatar_sex: str = None,
-    background_image: np.ndarray = None,
-    background_prompt: str = None,
-    seed: int = -1,
-) -> tuple:
-    result = client.try_on_file(
-        clothing_image=cv2.cvtColor(clothing_image, cv2.COLOR_RGB2BGR) if clothing_image is not None else None,
-        clothing_prompt=clothing_prompt,
-        avatar_image=cv2.cvtColor(avatar_image, cv2.COLOR_RGB2BGR) if avatar_image is not None else None,
-        avatar_prompt=avatar_prompt,
-        avatar_sex=avatar_sex if avatar_sex in ["male", "female"] else None,
-        background_image=cv2.cvtColor(background_image, cv2.COLOR_RGB2BGR) if background_image is not None else None,
-        background_prompt=background_prompt,
-        seed=seed,
-    )
-
-    if result.status_code == 200:
-        return cv2.cvtColor(result.image, cv2.COLOR_BGR2RGB), f"<h3>Success</h3><p>Seed: {result.seed}</p>"
-    else:
-        error_message = f"<h3>Error {result.status_code}</h3>"
-
-        if result.error_details is not None:
-            error_message += f"<p>{result.error_details}</p>"
-
-        return None, error_message
-
-
-with gr.Blocks(theme=gr.themes.Soft(), delete_cache=(3600, 3600)) as app:
-    gr.HTML(
-        f"""
-       
-    """
-    )
-
-    if SHOW_RAPIDAPI_LINK:
-        gr.Button(
-           
-        )
-
-        gr.HTML(
-            """
-            <center>
-               
-            </center>
-            """
-        )
-
-    gr.HTML("</p>")
-
-    with gr.Row():
-        with gr.Column():
-            gr.HTML(
-                """
-                <h2>Clothing</h2>
-                <p>
-                    Clothing may be specified with a reference image or a text prompt. 
-                    For more exotic use cases image and prompt can be also used together.
-                    If both image and prompt are empty the model will generate random clothing.
-                    <br/><br/>
-                </p>
-                """
-            )
-
-            with gr.Tab("Image"):
-                clothing_image = gr.Image(label="Clothing Image", sources=["upload"], type="numpy")
-
-                clothing_image_examples = gr.Examples(
-                    inputs=clothing_image, examples_per_page=18, examples=get_examples("clothing")
-                )
-
-            with gr.Tab("Prompt"):
-                clothing_prompt = gr.TextArea(
-                    label="Clothing Prompt",
-                    info='Compel weighting <a href="https://github.com/damian0815/compel/blob/main/doc/syntax.md">syntax</a> is supported.',
-                )
-
-                clothing_prompt_examples = gr.Examples(
-                    inputs=clothing_prompt,
-                    examples_per_page=8,
-                    examples=[
-                        "a sheer blue sleeveless mini dress",
-                        "a beige woolen sweater and white pleated skirt",
-                        "a black leather jacket and dark blue slim-fit jeans",
-                        "a floral pattern blouse and leggings",
-                        "a paisley pattern purple shirt and beige chinos",
-                        "a striped white and blue polo shirt and blue jeans",
-                        "a colorful t-shirt and black shorts",
-                        "a checked pattern shirt and dark blue cargo pants",
-                    ],
-                )
-
-        with gr.Column():
-            gr.HTML(
-                """
-                <h2>Avatar</h2>
-                <p>
-                    Avatar may be specified with a subject photo or a text prompt.
-                    Latter can be used, for example, to replace person while preserving clothing. 
-                    For more exotic use cases image and prompt can be also used together.
-                    If both image and prompt are empty the model will generate random avatars.
-                </p>
-                """
-            )
-
-            with gr.Tab("Image"):
-                avatar_image = gr.Image(label="Avatar Image", sources=["upload"], type="numpy")
-
-                avatar_image_examples = gr.Examples(
-                    inputs=avatar_image,
-                    examples_per_page=18,
-                    examples=get_examples("avatar"),
-                )
-
-            with gr.Tab("Prompt"):
-                avatar_prompt = gr.TextArea(
-                    label="Avatar Prompt",
-                    info='Compel weighting <a href="https://github.com/damian0815/compel/blob/main/doc/syntax.md">syntax</a> is supported.',
-                )
-
-                avatar_prompt_examples = gr.Examples(
-                    inputs=avatar_prompt,
-                    examples_per_page=8,
-                    examples=[
-                        "a beautiful blond girl with long hair",
-                        "a cute redhead girl with freckles",
-                        "a plus size female model wearing sunglasses",
-                        "a woman with dark hair and blue eyes",
-                        "a fit man with dark beard and blue eyes",
-                        "a young blond man posing for a photo",
-                        "a gentleman with beard and mustache",
-                        "a plus size man walking",
-                    ],
-                )
-
-            avatar_sex = gr.Dropdown(
-                label="Avatar Sex",
-                choices=[("Auto", ""), ("Male", "male"), ("Female", "female")],
-                value="",
-                info="Avatar sex selector can be used to enforce a specific sex of the avatar.",
-            )
-
-        with gr.Column():
-            gr.HTML(
-                """
-                <h2>Background</h2>
-                <p>
-                    Replacing the background is optional. 
-                    Resulting background may be specified with a reference image or a text prompt.
-                    If omitted the original avatar background will be preserved.
-                    <br/><br/><br/>
-                </p>
-                """
-            )
-
-            with gr.Tab("Image"):
-                background_image = gr.Image(label="Background Image", sources=["upload"], type="numpy")
-
-                background_image_examples = gr.Examples(
-                    inputs=background_image, examples_per_page=18, examples=get_examples("background")
-                )
-
-            with gr.Tab("Prompt"):
-                background_prompt = gr.TextArea(
-                    label="Background Prompt",
-                    info='Compel weighting <a href="https://github.com/damian0815/compel/blob/main/doc/syntax.md">syntax</a> is supported.',
-                )
-
-                background_prompt_examples = gr.Examples(
-                    inputs=background_prompt,
-                    examples_per_page=8,
-                    examples=[
-                        "in an autumn park",
-                        "in front of a brick wall",
-                        "near an old tree",
-                        "on a busy city street",
-                        "in front of a staircase",
-                        "on an ocean beach with palm trees",
-                        "in a shopping mall",
-                        "in a modern office",
-                    ],
-                )
-
-        with gr.Column():
-            gr.HTML(
-                """
-                <h2>Generation</h2>
-                """
-            )
-
-            seed = gr.Number(
-                label="Seed",
-                value=-1,
-                minimum=-1,
-                info="Seed used for generation, specify -1 for random seed for each generation.",
-            )
-
-            generate_button = gr.Button(value="Generate", variant="primary")
-
-            result_image = gr.Image(label="Result", show_share_button=False, format="jpeg")
-            result_details = gr.HTML(label="Details")
-
-    generate_button.click(
-        fn=try_on,
-        inputs=[
-            clothing_image,
-            clothing_prompt,
-            avatar_image,
-            avatar_prompt,
-            avatar_sex,
-            background_image,
-            background_prompt,
-            seed,
-        ],
-        outputs=[result_image, result_details],
-        api_name=False,
-        concurrency_limit=CONCURRENCY_LIMIT,
-    )
-
-    app.title = "Virtual Try-On Diffusion by Texel.Moda"
-
-
-if __name__ == "__main__":
-    app.queue(api_open=False).launch(show_api=False, ssr_mode=False)