Create app.py

app.py

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+from __future__ import annotations
+import os
+import random
+import uuid
+import gradio as gr
+import spaces
+import numpy as np
+from diffusers import PixArtAlphaPipeline, LCMScheduler
+import torch
+from typing import Tuple
+from datetime import datetime
+
+# Description for the app
+DESCRIPTION = """ 
+# Instant Image
+### Super fast text to Image Generator.
+### <span style='color: red;'>You may change the steps from 4 to 8, if you didn't get satisfied results.
+### First Image processing takes time then images generate faster.
+### Must Try -> Instant Video https://huggingface.co/spaces/KingNish/Instant-Video
+"""
+if not torch.cuda.is_available():
+    DESCRIPTION += "\n<p>Running on CPU 🥶 This demo does not work on CPU.</p>"
+
+# Configuration and constants
+MAX_SEED = np.iinfo(np.int32).max
+CACHE_EXAMPLES = torch.cuda.is_available() and os.getenv("CACHE_EXAMPLES", "1") == "1"
+MAX_IMAGE_SIZE = int(os.getenv("MAX_IMAGE_SIZE", "4192"))
+USE_TORCH_COMPILE = os.getenv("USE_TORCH_COMPILE", "0") == "1"
+ENABLE_CPU_OFFLOAD = os.getenv("ENABLE_CPU_OFFLOAD", "0") == "1"
+PORT = int(os.getenv("DEMO_PORT", "15432"))
+device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
+
+# Define color-based attributes
+color_attributes = {
+    "Purple": {"verbs": ["assist", "befriend", "care", "collaborate", "connect", "embrace", "empower", "encourage", "foster", "give", "help", "nourish", "nurture", "promote", "protect", "provide", "serve", "share", "shepherd", "steward", "tend", "uplift", "value", "welcome"], "adjectives": ["caring", "encouraging", "attentive", "compassionate", "empathetic", "generous", "hospitable", "nurturing", "protective", "selfless", "supportive", "welcoming"]},
+    "Green": {"verbs": ["analyze", "discover", "examine", "expand", "explore", "extend", "inquire", "journey", "launch", "move", "pioneer", "pursue", "question", "reach", "search", "uncover", "venture", "wonder"], "adjectives": ["adventurous", "curious", "discerning", "examining", "experiential", "exploratory", "inquisitive", "investigative", "intrepid", "philosophical"]},
+    "Maroon": {"verbs": ["accomplish", "achieve", "build", "challenge", "commit", "compete", "contend", "dedicate", "defend", "devote", "drive", "endeavor", "entrust", "endure", "fight", "grapple", "grow", "improve", "increase", "overcome", "persevere", "persist", "press on", "pursue", "resolve"], "adjectives": ["competitive", "determined", "gritty", "industrious", "persevering", "relentless", "resilient", "tenacious", "tough", "unwavering"]},
+    "Orange": {"verbs": ["compose", "conceptualize", "conceive", "craft", "create", "design", "dream", "envision", "express", "fashion", "form", "imagine", "interpret", "make", "originate", "paint", "perform", "portray", "realize", "shape"], "adjectives": ["artistic", "conceptual", "creative", "eclectic", "expressive", "imaginative", "interpretive", "novel", "original", "whimsical"]},
+    "Yellow": {"verbs": ["accelerate", "advance", "change", "conceive", "create", "engineer", "envision", "experiment", "dream", "ignite", "illuminate", "imagine", "innovate", "inspire", "invent", "pioneer", "progress", "shape", "spark", "solve", "transform", "unleash", "unlock"], "adjectives": ["advanced", "analytical", "brilliant", "experimental", "forward-thinking", "innovative", "intelligent", "inventive", "leading-edge", "visionary"]},
+    "Red": {"verbs": ["animate", "amuse", "captivate", "cheer", "delight", "encourage", "energize", "engage", "enjoy", "enliven", "entertain", "excite", "express", "inspire", "joke", "motivate", "play", "stir", "uplift"], "adjectives": ["dynamic", "energetic", "engaging", "entertaining", "enthusiastic", "exciting", "fun", "lively", "magnetic", "playful", "humorous"]},
+    "Blue": {"verbs": ["accomplish", "achieve", "affect", "assert", "cause", "command", "determine", "direct", "dominate", "drive", "empower", "establish", "guide", "impact", "impress", "influence", "inspire", "lead", "outpace", "outshine", "realize", "shape", "succeed", "transform", "win"], "adjectives": ["accomplished", "assertive", "confident", "decisive", "elite", "influential", "powerful", "prominent", "proven", "strong"]},
+    "Pink": {"verbs": ["arise", "aspire", "detail", "dream", "elevate", "enchant", "enrich", "envision", "exceed", "excel", "experience", "improve", "idealize", "imagine", "inspire", "perfect", "poise", "polish", "prepare", "refine", "uplift"], "adjectives": ["aesthetic", "charming", "classic", "dignified", "idealistic", "meticulous", "poised", "polished", "refined", "sophisticated", "elegant"]},
+    "Silver": {"verbs": ["activate", "campaign", "challenge", "commit", "confront", "dare", "defy", "disrupt", "drive", "excite", "face", "ignite", "incite", "influence", "inspire", "inspirit", "motivate", "move", "push", "rebel", "reimagine", "revolutionize", "rise", "spark", "stir", "fight", "free"], "adjectives": ["bold", "daring", "fearless", "independent", "non-conformist", "radical", "rebellious", "resolute", "unconventional", "valiant"]},
+    "Beige": {"verbs": ["dedicate", "humble", "collaborate", "empower", "inspire", "empassion", "transform"], "adjectives": ["dedicated", "collaborative", "consistent", "empowering", "enterprising", "humble", "inspiring", "passionate", "proud", "traditional", "transformative"]},
+}
+
+# Image styles for Gradio interface
+style_list = [
+    {"name": "(No style)", "prompt": "{prompt}", "negative_prompt": ""},
+    {"name": "Cinematic", "prompt": "cinematic still {prompt} . emotional, harmonious, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy", "negative_prompt": "anime, cartoon, graphic, text, painting, crayon, graphite, abstract, glitch, deformed, mutated, ugly, disfigured"},
+    {"name": "Realistic", "prompt": "Photorealistic {prompt} . Ulta-realistic, professional, 4k, highly detailed", "negative_prompt": "drawing, painting, crayon, sketch, graphite, impressionist, noisy, blurry, soft, deformed, ugly, disfigured"},
+    {"name": "Anime", "prompt": "anime artwork {prompt} . anime style, key visual, vibrant, studio anime,  highly detailed", "negative_prompt": "photo, deformed, black and white, realism, disfigured, low contrast"},
+    {"name": "Digital Art", "prompt": "concept art {prompt} . digital artwork, illustrative, painterly, matte painting, highly detailed", "negative_prompt": "photo, photorealistic, realism, ugly"},
+    {"name": "Pixel art", "prompt": "pixel-art {prompt} . low-res, blocky, pixel art style, 8-bit graphics", "negative_prompt": "sloppy, messy, blurry, noisy, highly detailed, ultra textured, photo, realistic"},
+    {"name": "Fantasy art", "prompt": "ethereal fantasy concept art of {prompt} . magnificent, celestial, ethereal, painterly, epic, majestic, magical, fantasy art, cover art, dreamy", "negative_prompt": "photographic, realistic, realism, 35mm film, dslr, cropped, frame, text, deformed, glitch, noise, noisy, off-center, deformed, cross-eyed, closed eyes, bad anatomy, ugly, disfigured, sloppy, duplicate, mutated, black and white"},
+    {"name": "3D Model", "prompt": "professional 3d model {prompt} . octane render, highly detailed, volumetric, dramatic lighting", "negative_prompt": "ugly, deformed, noisy, low poly, blurry, painting"},
+]
+
+# Create dictionary of styles
+styles = {k["name"]: (k["prompt"], k["negative_prompt"]) for k in style_list}
+STYLE_NAMES = list(styles.keys())
+DEFAULT_STYLE_NAME = "(No style)"
+NUM_IMAGES_PER_PROMPT = 1
+
+# Function to apply style and modify prompt based on selected colors
+def apply_style(style_name: str, positive: str, color_selections: dict) -> Tuple[str, str]:
+    p, n = styles.get(style_name, styles[DEFAULT_STYLE_NAME])
+    color_prompt = ""
+    
+    # Aggregate verbs and adjectives from selected colors based on their ratios
+    for color, attributes in color_selections.items():
+        if attributes["selected"]:
+            verbs = random.sample(color_attributes[color]["verbs"], min(3, len(color_attributes[color]["verbs"])))
+            adjectives = random.sample(color_attributes[color]["adjectives"], min(3, len(color_attributes[color]["adjectives"])))
+            color_prompt += " ".join(verbs) + " " + " ".join(adjectives) + " "
+    
+    # Form the final prompt
+    final_prompt = p.replace("{prompt}", positive + " " + color_prompt.strip())
+    return final_prompt, n
+
+# Check if CUDA is available and set up the pipeline
+if torch.cuda.is_available():
+    pipe = PixArtAlphaPipeline.from_pretrained(
+        "PixArt-alpha/PixArt-LCM-XL-2-1024-MS",
+        torch_dtype=torch.float16,
+        use_safetensors=True,
+    )
+    if os.getenv('CONSISTENCY_DECODER', False):
+        print("Using DALL-E 3 Consistency Decoder")
+        pipe.vae = ConsistencyDecoderVAE.from_pretrained("openai/consistency-decoder", torch_dtype=torch.float16)
+    if ENABLE_CPU_OFFLOAD:
+        pipe.enable_model_cpu_offload()
+    else:
+        pipe.to(device)
+        print("Loaded on Device!")
+    if USE_TORCH_COMPILE:
+        pipe.transformer = torch.compile(pipe.transformer, mode="reduce-overhead", fullgraph=True)
+        print("Model Compiled!")
+
+# Function to save image
+def save_image(img):
+    unique_name = str(uuid.uuid4()) + ".png"
+    img.save(unique_name)
+    return unique_name
+
+# Function to randomize seed if needed
+def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
+    if randomize_seed:
+        seed = random.randint(0, MAX_SEED)
+    return seed
+
+# Main function to generate images based on user inputs
+@spaces.GPU(duration=30)
+def generate(
+    prompt: str,
+    negative_prompt: str = "",
+    style: str = DEFAULT_STYLE_NAME,
+    use_negative_prompt: bool = False,
+    seed: int = 0,
+    width: int = 1024,
+    height: int = 1024,
+    inference_steps: int = 4,
+    randomize_seed: bool = False,
+    use_resolution_binning: bool = True,
+    **color_ratios  # Collect color ratios dynamically
+):
+    seed = int(randomize_seed_fn(seed, randomize_seed))
+    generator = torch.Generator().manual_seed(seed)
+    
+    if not use_negative_prompt:
+        negative_prompt = None  # type: ignore
+    
+    # Process color selections and their ratios
+    color_selections = {color: {"selected": color_ratios.get(f"{color.lower()}_selected", False), "ratio": color_ratios.get(f"{color.lower()}_ratio", 0)} for color in color_attributes}
+    
+    # Apply style and modify prompt based on color selections
+    prompt, negative_prompt = apply_style(style, prompt, color_selections)
+    
+    # Generate images
+    try:
+        images = pipe(
+            prompt=prompt,
+            negative_prompt=negative_prompt,
+            width=width,
+            height=height,
+            guidance_scale=0,
+            num_inference_steps=inference_steps,
+            generator=generator,
+            num_images_per_prompt=NUM_IMAGES_PER_PROMPT,
+            use_resolution_binning=use_resolution_binning,
+            output_type="pil",
+        ).images
+    except Exception as e:
+        print(f"Error during image generation: {e}")
+        return [], seed
+    
+    image_paths = [save_image(img) for img in images]
+    print(image_paths)
+    return image_paths, seed
+
+# Example prompts
+examples = [
+    "A Monkey with a happy face in the Sahara desert.",
+    "Eiffel Tower was Made up of ICE.",
+    "Color photo of a corgi made of transparent glass, standing on the riverside in Yosemite National Park.",
+    "A close-up photo of a woman. She wore a blue coat with a gray dress underneath and has blue eyes.",
+    "A litter of golden retriever puppies playing in the snow. Their heads pop out of the snow, covered in.",
+    "an astronaut sitting in a diner, eating fries, cinematic, analog film",
+]
+
+# Set up the Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown(DESCRIPTION)
+    with gr.Row(equal_height=False):
+        with gr.Group():
+            with gr.Row():
+                prompt = gr.Text(
+                    label="Prompt",
+                    show_label=False,
+                    max_lines=1,
+                    placeholder="Enter your prompt",
+                    container=False,
+                )
+                run_button = gr.Button("Run", scale=0)
+            result = gr.Gallery(label="Result", columns=NUM_IMAGES_PER_PROMPT, show_label=False)
+    
+    # Color selection and ratio configuration in the UI
+    with gr.Accordion("Color Influences", open=False):
+        with gr.Group():
+            color_checkboxes = {}
+            color_sliders = {}
+            for color in color_attributes:
+                with gr.Row():
+                    color_checkboxes[color] = gr.Checkbox(label=f"{color} Selected", value=False)
+                    color_sliders[color] = gr.Slider(label=f"{color} Influence Ratio", minimum=0, maximum=1, step=0.01, value=0.0)
+    
+    with gr.Accordion("Advanced options", open=False):
+        with gr.Group():
+            with gr.Row():
+                use_negative_prompt = gr.Checkbox(label="Use negative prompt", value=False, visible=True)
+                negative_prompt = gr.Text(
+                    label="Negative prompt",
+                    max_lines=1,
+                    placeholder="Enter a negative prompt",
+                    visible=True,
+                )
+            style_selection = gr.Radio(
+                choices=STYLE_NAMES,
+                value=DEFAULT_STYLE_NAME,
+                label="Image Style",
+                show_label=True,
+                container=True,
+                interactive=True,
+            )
+            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(visible=True):
+                width = gr.Slider(
+                    label="Width",
+                    minimum=256,
+                    maximum=MAX_IMAGE_SIZE,
+                    step=32,
+                    value=1024,
+                )
+                height = gr.Slider(
+                    label="Height",
+                    minimum=256,
+                    maximum=MAX_IMAGE_SIZE,
+                    step=32,
+                    value=1024,
+                )
+        with gr.Row():
+            inference_steps = gr.Slider(
+                label="Steps",
+                minimum=4,
+                maximum=20,
+                step=1,
+                value=4,
+            )
+
+    gr.Examples(
+        examples=examples,
+        inputs=prompt,
+        outputs=[result, seed],
+        fn=generate,
+        cache_examples=CACHE_EXAMPLES,
+    )
+
+    # Dynamic updates based on user interactions
+    use_negative_prompt.change(
+        fn=lambda x: gr.update(visible=x),
+        inputs=use_negative_prompt,
+        outputs=negative_prompt,
+        api_name=False,
+    )
+
+    gr.on(
+        triggers=[
+            prompt.submit,
+            negative_prompt.submit,
+            run_button.click,
+        ],
+        fn=generate,
+        inputs=[
+            prompt,
+            negative_prompt,
+            style_selection,
+            use_negative_prompt,
+            seed,
+            width,
+            height,
+            inference_steps,
+            randomize_seed,
+            *[color_checkboxes[color] for color in color_attributes],
+            *[color_sliders[color] for color in color_attributes]
+        ],
+        outputs=[result, seed],
+        api_name="run",
+    )
+
+# Launch the Gradio app
+if __name__ == "__main__":
+    demo.queue(max_size=20).launch()
+    # Uncomment the next line to launch the server with specific options
+    # demo.queue(max_size=20).launch(server_name="0.0.0.0", server_port=11900, debug=True)