gradio_text2image.py

from paddlemix.appflow import Appflow
from ppdiffusers.utils import load_image
import paddle
import imageio

from PIL import Image
import gradio as gr
import traceback

# upscaling
def ups_fun(low_res_img, prompt):
    low_res_img = Image.fromarray(low_res_img.astype('uint8')).convert('RGB')
    app = Appflow(app='image2image_text_guided_upscaling',models=['stabilityai/stable-diffusion-x4-upscaler'])
    image = app(prompt=prompt,image=low_res_img)['result']
    return image

# text_guided_generation
def tge_fun(image, prompt_pos, prompt_neg):
    image = Image.fromarray(image.astype('uint8')).convert('RGB')
    app = Appflow(app='image2image_text_guided_generation',models=['Linaqruf/anything-v3.0'])
    image = app(prompt=prompt_pos,negative_prompt=prompt_neg,image=image)['result']
    return image

# video_generation
def vge_fun(prompt):
    app = Appflow(app='text_to_video_generation',models=['damo-vilab/text-to-video-ms-1.7b'])
    video_frames = app(prompt=prompt,num_inference_steps=25)['result']
    imageio.mimsave("gen_video.gif", video_frames, duration=8)
    return "gen_video.gif"

with gr.Blocks() as demo:
    gr.Markdown("# Appflow应用：text2image")
    with gr.Tab("文本引导的图像放大"):
        with gr.Row():
            ups_image_in = gr.Image(label = "输入图片")
            ups_image_out = gr.Image(label = "输出图片")
        ups_text_in = gr.Text(label = "Prompt")
        ups_button = gr.Button()
        ups_button.click(fn=ups_fun, inputs = [ups_image_in, ups_text_in], outputs = [ups_image_out])
    with gr.Tab("文本引导的图像变换"):
        with gr.Row():
            tge_image_in = gr.Image(label = "输入图片")
            tge_image_out = gr.Image(label = "输出图片")
        tge_text_pos_in = gr.Text(label = "Positive Prompt")
        tge_text_neg_in = gr.Text(label = "Negative Prompt")
        tge_button = gr.Button()
        tge_button.click(fn=tge_fun, inputs = [tge_image_in, tge_text_pos_in, tge_text_neg_in], outputs = [tge_image_out])
    with gr.Tab("文本条件的视频生成"):
        vge_text_in = gr.Text(label = "Prompt")
        vge_video_out = gr.Video(label = "输出视频")
        vge_button = gr.Button()
        vge_button.click(fn=vge_fun, inputs = [vge_text_in], outputs = [vge_video_out])

demo.launch()