app.py

# Copyright (2024) Bytedance Ltd. and/or its affiliates 
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.

from __future__ import annotations
import os
import random
import uuid

import gradio as gr
import numpy as np

from loguru import logger
from caller import (
    SeedT2ICaller,
    SeedEditCaller
)
from PIL import Image

help_text = """
## How to use this Demo
Step 1. Type in the caption/instruction text box, and click "Generate" to generate an initial image using Seed-T2I.

Step 2. Type in the caption/instruction text box, and click "Edit" to edit the current image using Seed-Edit.

This is a demo with limited QPS and a simple interface.
For a better experience, please use [Doubao](https://www.doubao.com/chat/)/[Dreamina](https://dreamina.capcut.com/ai-tool/image/generate) APP.

- The current demo does not support multi-round editing, which may lead to overexposure with multiple rounds of upload and download edits.
- Higher-quality input images will produce higher-quality edited results. For low-quality images, unwanted changes, e.g. facial id, may occur.

<font size=2>Note: This demo is governed by the license of CC BY-NC \
We strongly advise users not to knowingly generate or allow others to knowingly generate harmful content, \
including hate speech, violence, pornography, deception, etc. \
(注：本演示受CC BY-NC的许可协议限制。我们强烈建议，用户不应传播及不应允许他人传播以下内容，\
包括但不限于仇恨言论、暴力、色情、欺诈相关的有害信息。)
"""

example_instructions = [
    "Make it a picasso painting",
    "close its eye",
    "convert to a bronze statue",
    "make it wearing a hat",
    "make it wearing a PhD suit",
    "Turn it into an anime.",
    "have it look like a graphic novel",
    "make it gain weight",
    "what would he look like bald?",
    "Have it smile",
    "Put in a cocktail party.",
    "move to the beach.",
    "add dramatic lighting",
    "Convert to black and white",
    "What if it were snowing?",
    "Give a leather jacket",
    "Turn into a cyborg!",
]

def main():
    resolution = 1024
    cfg = {"resolution": resolution}
    model_t2i = SeedT2ICaller(cfg)
    
    cfg_edit = {}
    model_edit = SeedEditCaller(cfg_edit)
    logger.info("All models loaded")
    

    def load_example():
        example_image = Image.open(f"uni_test/test.jpg").convert("RGB")
        example_instruction = random.choice(example_instructions)
        edited_image, example_instruction = generate(example_image, 
                                                     example_instruction, 
                                                     cfg_scale=0.5)
        return example_image, example_instruction, edited_image

    def generate_t2i(instruction: str, cfg_scale: float = 0.5):
        if not instruction:
            return None, ""

        logger.info("Generate images ...")
        # Call model and capture the status
        gen_image, success = model_t2i.generate(instruction, batch_size=1, cfg_scale=cfg_scale)
        if not success or gen_image is None:
            logger.error("Image generation failed or returned None. please retry")
            return None, instruction
        return gen_image, instruction

    def generate(input_image: Image.Image, instruction: str = None, cfg_scale: float = 0.5):
        logger.info("Generating images ...")
        if not instruction or input_image is None:
            return input_image, ""

        logger.info("Running diffusion models ...")
        edited_image, success = model_edit.edit(input_image, instruction, batch_size=1, cfg_scale=cfg_scale)
        if not success or edited_image is None:
            logger.error("Image editting failed or returned None.")
            return None, instruction
            
        return edited_image, instruction 

    def reset():
        return None, None, ""

    with gr.Blocks(css="footer {visibility: hidden}") as demo:
        with gr.Row():
            with gr.Column(scale=1, min_width=100):
                generate_button = gr.Button("Generate")
            with gr.Column(scale=1, min_width=100):
                edit_button = gr.Button("Edit")
            with gr.Column(scale=1, min_width=100):
                load_button = gr.Button("Load Example")
            with gr.Column(scale=1, min_width=100):
                reset_button = gr.Button("Reset")
                
        with gr.Row():
            with gr.Column(scale=3):
                instruction = gr.Textbox(lines=1, label="Caption/Edit Instruction", interactive=True, value=None) 
            with gr.Column(scale=1):
                cfg_scale = gr.Slider(value=0.5, minimum=0.0, maximum=1.0, step=0.1, label="Edit/Text Strength (CFG)", interactive=True)
                
        with gr.Row():
            input_image = gr.Image(label="Input Image", type="pil", interactive=True, 
                                    height=resolution, width=resolution)
            edited_image = gr.Image(label="Edited Image", type="pil", interactive=False, 
                                    height=resolution, width=resolution)

        gr.Markdown(help_text)
        
        load_button.click(
            fn=load_example,
            inputs=[],
            outputs=[input_image, instruction, edited_image]
        )
        generate_button.click(
            fn=generate_t2i,
            inputs=[instruction, cfg_scale],
            outputs=[input_image, instruction]
        )
        edit_button.click(
            fn=generate,
            inputs=[input_image, instruction, cfg_scale],
            outputs=[edited_image, instruction]
        )
        reset_button.click(
            fn=reset,
            inputs=[],
            outputs=[input_image, edited_image, instruction]
        )

    # demo.launch(server_name="0.0.0.0", server_port=8024)
    demo.queue().launch(share=False)

if __name__ == "__main__":
    main()