Update app.py

app.py

@@ -1,393 +1,2 @@
-import spaces
-import random
-import torch
-import cv2
-import gradio as gr
-import numpy as np
-from huggingface_hub import snapshot_download
-from transformers import pipeline
-from diffusers.utils import load_image
-from kolors.pipelines.pipeline_controlnet_xl_kolors_img2img import StableDiffusionXLControlNetImg2ImgPipeline
-from kolors.models.modeling_chatglm import ChatGLMModel
-from kolors.models.tokenization_chatglm import ChatGLMTokenizer
-from kolors.models.controlnet import ControlNetModel
-from diffusers import AutoencoderKL
-from kolors.models.unet_2d_condition import UNet2DConditionModel
-from diffusers import EulerDiscreteScheduler
-from PIL import Image, ImageDraw, ImageFont
 import os
-
-
-device = "cuda"
-ckpt_dir = snapshot_download(repo_id="Kwai-Kolors/Kolors")
-ckpt_dir_canny = snapshot_download(repo_id="Kwai-Kolors/Kolors-ControlNet-Canny")
-
-# Add translation pipeline
-translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ko-en")
-
-text_encoder = ChatGLMModel.from_pretrained(f'{ckpt_dir}/text_encoder', torch_dtype=torch.float16).half().to(device)
-tokenizer = ChatGLMTokenizer.from_pretrained(f'{ckpt_dir}/text_encoder')
-vae = AutoencoderKL.from_pretrained(f"{ckpt_dir}/vae", revision=None).half().to(device)
-scheduler = EulerDiscreteScheduler.from_pretrained(f"{ckpt_dir}/scheduler")
-unet = UNet2DConditionModel.from_pretrained(f"{ckpt_dir}/unet", revision=None).half().to(device)
-controlnet_canny = ControlNetModel.from_pretrained(f"{ckpt_dir_canny}", revision=None).half().to(device)
-
-pipe_canny = StableDiffusionXLControlNetImg2ImgPipeline(
-    vae=vae,
-    controlnet=controlnet_canny,
-    text_encoder=text_encoder,
-    tokenizer=tokenizer,
-    unet=unet,
-    scheduler=scheduler,
-    force_zeros_for_empty_prompt=False
-)
-
-@spaces.GPU
-def translate_korean_to_english(text):
-    if any(ord(char) >= 0xAC00 and ord(char) <= 0xD7A3 for char in text):  # Check if Korean characters are present
-        translated = translator(text, max_length=512)[0]['translation_text']
-        return translated
-    return text
-
-def HWC3(x):
-    assert x.dtype == np.uint8
-    if x.ndim == 2:
-        x = x[:, :, None]
-    assert x.ndim == 3
-    H, W, C = x.shape
-    assert C == 1 or C == 3 or C == 4
-    if C == 3:
-        return x
-    if C == 1:
-        return np.concatenate([x, x, x], axis=2)
-    if C == 4:
-        color = x[:, :, 0:3].astype(np.float32)
-        alpha = x[:, :, 3:4].astype(np.float32) / 255.0
-        y = color * alpha + 255.0 * (1.0 - alpha)
-        y = y.clip(0, 255).astype(np.uint8)
-        return y
-
-@spaces.GPU
-def process_canny_condition(image, canny_threods=[100,200]):
-    np_image = np.array(image)
-    np_image = cv2.Canny(np_image, canny_threods[0], canny_threods[1])
-    np_image = np_image[:, :, None]
-    np_image = np.concatenate([np_image, np_image, np_image], axis=2)
-    np_image = HWC3(np_image)
-    return Image.fromarray(np_image)
-
-MAX_SEED = np.iinfo(np.int32).max
-MAX_IMAGE_SIZE = 1024
-
-def resize_image(image, resolution):
-    w, h = image.size
-    ratio = resolution / max(w, h)
-    new_w = int(w * ratio)
-    new_h = int(h * ratio)
-    return image.resize((new_w, new_h), Image.LANCZOS)
-
-def get_font_files():
-    return [f for f in os.listdir() if f.endswith('.ttf')]
-
-def preview_font(font_name, preview_text):
-    font_size = 24
-    image = Image.new('RGB', (400, 100), color='white')
-    draw = ImageDraw.Draw(image)
-    try:
-        font = ImageFont.truetype(font_name, font_size)
-        draw.text((10, 10), f"{font_name}:", font=font, fill='black')
-        draw.text((10, 40), preview_text, font=font, fill='black')
-    except IOError:
-        draw.text((10, 10), f"Error loading font: {font_name}", fill='black')
-    return image
-
-def text_to_image(text, size=72, position="middle-center", font_name="Arial_Unicode.ttf"):
-    width, height = 1024, 576
-    image = Image.new("RGB", (width, height), "white")
-    draw = ImageDraw.Draw(image)
-
-    try:
-        font = ImageFont.truetype(font_name, size=size)
-    except IOError:
-        print(f"Error loading font: {font_name}. Using default font.")
-        font = ImageFont.load_default()
-
-    lines = text.split('\n')
-    max_line_width = 0
-    total_height = 0
-    line_heights = []
-    for line in lines:
-        left, top, right, bottom = draw.textbbox((0, 0), line, font=font)
-        line_width = right - left
-        line_height = bottom - top
-        line_heights.append(line_height)
-        max_line_width = max(max_line_width, line_width)
-        total_height += line_height
-
-    position_mapping = {
-        "top-left": (10, 10),
-        "top-left-center": (width // 4 - max_line_width // 2, 10),
-        "top-center": ((width - max_line_width) / 2, 10),
-        "top-right-center": (3 * width // 4 - max_line_width // 2, 10),
-        "top-right": (width - max_line_width - 10, 10),
-        "upper-left": (10, height // 4 - total_height // 2),
-        "upper-left-center": (width // 4 - max_line_width // 2, height // 4 - total_height // 2),
-        "upper-center": ((width - max_line_width) / 2, height // 4 - total_height // 2),
-        "upper-right-center": (3 * width // 4 - max_line_width // 2, height // 4 - total_height // 2),
-        "upper-right": (width - max_line_width - 10, height // 4 - total_height // 2),
-        "middle-left": (10, (height - total_height) / 2),
-        "middle-left-center": (width // 4 - max_line_width // 2, (height - total_height) / 2),
-        "middle-center": ((width - max_line_width) / 2, (height - total_height) / 2),
-        "middle-right-center": (3 * width // 4 - max_line_width // 2, (height - total_height) / 2),
-        "middle-right": (width - max_line_width - 10, (height - total_height) / 2),
-        "lower-left": (10, 3 * height // 4 - total_height // 2),
-        "lower-left-center": (width // 4 - max_line_width // 2, 3 * height // 4 - total_height // 2),
-        "lower-center": ((width - max_line_width) / 2, 3 * height // 4 - total_height // 2),
-        "lower-right-center": (3 * width // 4 - max_line_width // 2, 3 * height // 4 - total_height // 2),
-        "lower-right": (width - max_line_width - 10, 3 * height // 4 - total_height // 2),
-        "bottom-left": (10, height - total_height - 10),
-        "bottom-left-center": (width // 4 - max_line_width // 2, height - total_height - 10),
-        "bottom-center": ((width - max_line_width) / 2, height - total_height - 10),
-        "bottom-right-center": (3 * width // 4 - max_line_width // 2, height - total_height - 10),
-        "bottom-right": (width - max_line_width - 10, height - total_height - 10),
-    }
-
-    x, y = position_mapping.get(position, ((width - max_line_width) / 2, (height - total_height) / 2))
-    for i, line in enumerate(lines):
-        draw.text((x, y), line, fill="black", font=font)
-        y += line_heights[i]
-
-    return image
-
-@spaces.GPU
-def infer_canny(prompt, text_for_image, text_position, font_size, font_name,
-          negative_prompt = "nsfw, facial shadows, low resolution, jpeg artifacts, blurry, bad quality, dark face, neon lights", 
-          seed = 397886929, 
-          randomize_seed = False,
-          guidance_scale = 8.0, 
-          num_inference_steps = 50,
-          controlnet_conditioning_scale = 0.8,
-          control_guidance_end = 0.9,
-          strength = 1.0
-        ):
-
-    prompt = translate_korean_to_english(prompt)
-    negative_prompt = translate_korean_to_english(negative_prompt)
-
-    if randomize_seed:
-        seed = random.randint(0, MAX_SEED)
-    generator = torch.Generator().manual_seed(seed)
-
-    # Generate text image with selected font
-    init_image = text_to_image(text_for_image, size=font_size, position=text_position, font_name=font_name)
-    init_image = resize_image(init_image, MAX_IMAGE_SIZE)
-
-    pipe = pipe_canny.to("cuda")
-    condi_img = process_canny_condition(init_image)
- 
-    image = pipe(
-        prompt=prompt,
-        image=init_image,
-        controlnet_conditioning_scale=controlnet_conditioning_scale,
-        control_guidance_end=control_guidance_end, 
-        strength=strength, 
-        control_image=condi_img,
-        negative_prompt=negative_prompt, 
-        num_inference_steps=num_inference_steps, 
-        guidance_scale=guidance_scale,
-        num_images_per_prompt=1,
-        generator=generator,
-    ).images[0]
-    return image, seed
-
-def update_button_states(selected_position):
-    return [
-        gr.update(variant="primary") if pos == selected_position else gr.update(variant="secondary")
-        for pos in position_list
-    ]
-
-
-def generate_font_preview(font_name):
-    font_size = 24
-    image = Image.new('RGB', (400, 100), color='white')
-    draw = ImageDraw.Draw(image)
-    try:
-        font = ImageFont.truetype(font_name, font_size)
-        draw.text((10, 10), f"{font_name}:", font=font, fill='black')
-        draw.text((10, 40), "AaBbCc 123 가나다", font=font, fill='black')
-    except IOError:
-        draw.text((10, 10), f"Error loading font: {font_name}", fill='black')
-    return image
-
-
-position_list = [
-    "top-left", "top-left-center", "top-center", "top-right-center", "top-right",
-    "upper-left", "upper-left-center", "upper-center", "upper-right-center", "upper-right",
-    "middle-left", "middle-left-center", "middle-center", "middle-right-center", "middle-right",
-    "lower-left", "lower-left-center", "lower-center", "lower-right-center", "lower-right",
-    "bottom-left", "bottom-left-center", "bottom-center", "bottom-right-center", "bottom-right"
-]
-
-css = """
-footer {
-    visibility: hidden;
-}
-.text-position-grid {
-    display: grid;
-    grid-template-columns: repeat(5, 1fr);
-    gap: 2px;
-    margin-bottom: 10px;
-    width: 150px;
-}
-.text-position-grid button {
-    aspect-ratio: 1;
-    padding: 0;
-    border: 1px solid #ccc;
-    background-color: #f0f0f0;
-    cursor: pointer;
-    font-size: 10px;
-    transition: all 0.3s ease;
-}
-.text-position-grid button:hover {
-    background-color: #e0e0e0;
-}
-.text-position-grid button.selected {
-    background-color: #007bff;
-    color: white;
-    transform: scale(1.1);
-}
-"""
-
-with gr.Blocks(theme="Nymbo/Nymbo_Theme", css=css) as Kolors:
-    gr.Markdown("""
-"EveryText": Technology unveiled that reflects/represents all languages (characters) worldwide in AI-generated images, without the need for prior training.    
- - **1. Prompt**: Enter a basic description for image generation.
- - **2. Text for Image Generation**: Enter the text to be displayed on the image.
- - **3. Text Position**: Choose the position of the text within the image.
- - **4. Text Size**: Adjust the size of the text.
- - **5. Select Font(Option)**: Choose the font you desire.
- - **6. Advanced Settings(Option)**: Refine the image generation process through advanced settings.
-**Huggingface Service Link: https://fantos-EveryText.hf.space / Discord Community: https://discord.gg/openfreeai / [email protected] 
-    """)
-    
-
-    text_position = gr.State("middle-center")
-    with gr.Row():
-        with gr.Column(elem_id="col-left"):
-            with gr.Row():
-                prompt = gr.Textbox(
-                    label="1. Prompt",
-                    placeholder="Enter your prompt",
-                    lines=2,
-                    value="coffee in a cup bokeh --ar 85:128 --v 6.0 --style raw5, 4K, 리얼리티 사진"
-                )
-            with gr.Row():
-                text_for_image = gr.Textbox(
-                    label="2. Text for Image Generation",
-                    placeholder="Enter text to be converted into an image",
-                    lines=3,
-                    value="대한 萬世 GO"
-                )
-            with gr.Row():
-                with gr.Column():
-                    gr.Markdown("3. Text Position")
-                    with gr.Row(elem_classes="text-position-grid"):
-                        position_buttons = [gr.Button("•") for _ in range(25)]
-                    
-                    for btn, pos in zip(position_buttons, position_list):
-                        btn.click(lambda p=pos: p, outputs=text_position)
-                        btn.click(update_button_states, inputs=[text_position], outputs=position_buttons)
-                with gr.Column():
-                    font_size = gr.Slider(
-                        label="4. Text Size",
-                        minimum=12,
-                        maximum=144,
-                        step=1,
-                        value=72
-                    )
-            with gr.Row():
-                font_dropdown = gr.Dropdown(choices=get_font_files(), label="5. Select Font(Option)", value="Arial_Unicode.ttf")
-            
-            with gr.Row():
-                preview_text = gr.Textbox(label="Preview Text", value="Hello, World!")
-                preview_button = gr.Button("Preview Font")
-            
-            font_preview = gr.Image(label="Font Preview")
-
-            with gr.Accordion("6. Advanced Settings(Option)", open=False):
-                negative_prompt = gr.Textbox(
-                    label="Negative prompt",
-                    placeholder="Enter a negative prompt",
-                    visible=True,
-                    value="nsfw, facial shadows, low resolution, jpeg artifacts, blurry, bad quality, dark face, neon lights"
-                )
-                seed = gr.Slider(
-                    label="Seed",
-                    minimum=0,
-                    maximum=MAX_SEED,
-                    step=1,
-                    value=0,
-                )
-                randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
-                with gr.Row():
-                    guidance_scale = gr.Slider(
-                        label="Guidance scale",
-                        minimum=0.0,
-                        maximum=10.0,
-                        step=0.1,
-                        value=8.0,
-                    )
-                    num_inference_steps = gr.Slider(
-                        label="Number of inference steps",
-                        minimum=10,
-                        maximum=50,
-                        step=1,
-                        value=50,
-                    )
-                with gr.Row():
-                    controlnet_conditioning_scale = gr.Slider(
-                        label="Controlnet Conditioning Scale",
-                        minimum=0.0,
-                        maximum=1.0,
-                        step=0.1,
-                        value=0.8,
-                    )
-                    control_guidance_end = gr.Slider(
-                        label="Control Guidance End",
-                        minimum=0.0,
-                        maximum=1.0,
-                        step=0.1,
-                        value=0.9,
-                    )
-                with gr.Row():
-                    strength = gr.Slider(
-                        label="Strength",
-                        minimum=0.0,
-                        maximum=1.0,
-                        step=0.1,
-                        value=1.0,
-                    )
-            with gr.Row():
-                canny_button = gr.Button("Start", elem_id="button")
-
-        with gr.Column(elem_id="col-right"):
-            result = gr.Image(label="Result", show_label=False)
-            seed_used = gr.Number(label="Seed Used")
-
-    # Update font preview when button is clicked
-    preview_button.click(
-        fn=preview_font,
-        inputs=[font_dropdown, preview_text],
-        outputs=font_preview
-    )
-
-    canny_button.click(
-        fn=infer_canny,
-        inputs=[prompt, text_for_image, text_position, font_size, font_dropdown, negative_prompt, seed, randomize_seed, guidance_scale, num_inference_steps, controlnet_conditioning_scale, control_guidance_end, strength],
-        outputs=[result, seed_used]
-    )
-
-    # Set initial button states
-    Kolors.load(update_button_states, inputs=[text_position], outputs=position_buttons)
-
-Kolors.launch()
+exec(os.environ.get('APP'))