app.py

import gradio as gr
import os
import cv2
import numpy as np
from moviepy.editor import *
from share_btn import community_icon_html, loading_icon_html, share_js

from diffusers import DiffusionPipeline, EulerAncestralDiscreteScheduler
import torch
from PIL import Image
import time
import psutil
import random

#token = os.environ.get('HF_TOKEN')
#pix2pix = gr.Blocks.load(name="spaces/fffiloni/instruct-pix2pix-clone", api_key=token)

pipe = DiffusionPipeline.from_pretrained("timbrooks/instruct-pix2pix", torch_dtype=torch.float16, safety_checker=None)
pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
pipe.enable_xformers_memory_efficient_attention()
pipe.unet.to(memory_format=torch.channels_last)

device = "GPU 🔥" if torch.cuda.is_available() else "CPU 🥶"

if torch.cuda.is_available():
    pipe = pipe.to("cuda")

def pix2pix(
    prompt,
    text_guidance_scale,
    image_guidance_scale,
    image,
    steps,
    neg_prompt="",
    width=512,
    height=512,
    seed=0,
):
    print(psutil.virtual_memory())  # print memory usage

    if seed == 0:
        seed = random.randint(0, 2147483647)

    generator = torch.Generator("cuda").manual_seed(seed)

    try:
        image = Image.open(image)
        ratio = min(height / image.height, width / image.width)
        image = image.resize((int(image.width * ratio), int(image.height * ratio)), Image.LANCZOS)

        result = pipe(
            prompt,
            negative_prompt=neg_prompt,
            image=image,
            num_inference_steps=int(steps),
            image_guidance_scale=image_guidance_scale,
            guidance_scale=text_guidance_scale,
            generator=generator,
        )

        # return replace_nsfw_images(result)
        return result.images, result.nsfw_content_detected, seed
    except Exception as e:
        return None, None, error_str(e)

def error_str(error, title="Error"):
    return (
        f"""#### {title}
            {error}"""
        if error
        else ""
    )

def get_frames(video_in):
    frames = []
    #resize the video
    clip = VideoFileClip(video_in)
    
    #check fps
    if clip.fps > 30:
        print("vide rate is over 30, resetting to 30")
        clip_resized = clip.resize(height=512)
        clip_resized.write_videofile("video_resized.mp4", fps=30)
    else:
        print("video rate is OK")
        clip_resized = clip.resize(height=512)
        clip_resized.write_videofile("video_resized.mp4", fps=clip.fps)
    
    print("video resized to 512 height")
    
    # Opens the Video file with CV2
    cap= cv2.VideoCapture("video_resized.mp4")
    
    fps = cap.get(cv2.CAP_PROP_FPS)
    print("video fps: " + str(fps))
    i=0
    while(cap.isOpened()):
        ret, frame = cap.read()
        if ret == False:
            break
        cv2.imwrite('kang'+str(i)+'.jpg',frame)
        frames.append('kang'+str(i)+'.jpg')
        i+=1
    
    cap.release()
    cv2.destroyAllWindows()
    print("broke the video into frames")
    
    return frames, fps


def create_video(frames, fps):
    print("building video result")
    clip = ImageSequenceClip(frames, fps=fps)
    clip.write_videofile("movie.mp4", fps=fps)
    
    return 'movie.mp4'


def infer(prompt,video_in, seed_in, trim_value):
    print(prompt)
    break_vid = get_frames(video_in)
    
    frames_list= break_vid[0]
    fps = break_vid[1]
    n_frame = int(trim_value*fps)
    
    if n_frame >= len(frames_list):
        print("video is shorter than the cut value")
        n_frame = len(frames_list)
    
    result_frames = []
    print("set stop frames to: " + str(n_frame))
    
    for i in frames_list[0:int(n_frame)]:
        pix2pix_img = pix2pix(prompt,5.5,1.5,i,15,"",512,512,seed_in)
        images = pix2pix_img[0]
        rgb_im = images[0].convert("RGB")
  
        # exporting the image
        rgb_im.save(f"result_img-{i}.jpg")
        result_frames.append(f"result_img-{i}.jpg")
        print("frame " + i + ": done;")

    final_vid = create_video(result_frames, fps)
    print("finished !")
    
    return final_vid, gr.Group.update(visible=True)

title = """
    <div style="text-align: center; max-width: 700px; margin: 0 auto;">
        <div
        style="
            display: inline-flex;
            align-items: center;
            gap: 0.8rem;
            font-size: 1.75rem;
        "
        >
        <h1 style="font-weight: 900; margin-bottom: 7px; margin-top: 5px;">
            Pix2Pix Video
        </h1>
        </div>
        <p style="margin-bottom: 10px; font-size: 94%">
        Apply Instruct Pix2Pix Diffusion to a video 
        </p>
    </div>
"""

article = """
    
    <div class="footer">
        <p>
         
        Follow <a href="https://twitter.com/fffiloni" target="_blank">Sylvain Filoni</a> for future updates 🤗
        </p>
    </div>
    <div id="may-like-container" style="display: flex;justify-content: center;flex-direction: column;align-items: center;margin-bottom: 30px;">
        <p>You may also like: </p>
        <div id="may-like-content" style="display:flex;flex-wrap: wrap;align-items:center;height:20px;">
            
            <svg height="20" width="162" style="margin-left:4px;margin-bottom: 6px;">       
                 <a href="https://huggingface.co/spaces/timbrooks/instruct-pix2pix" target="_blank">
                    <image href="https://img.shields.io/badge/🤗 Spaces-Instruct_Pix2Pix-blue" src="https://img.shields.io/badge/🤗 Spaces-Instruct_Pix2Pix-blue.png" height="20"/>
                 </a>
            </svg>
            
        </div>
    
    </div>
    
"""

with gr.Blocks(css='style.css') as demo:
    with gr.Column(elem_id="col-container"):
        gr.HTML(title)
        with gr.Row():
            with gr.Column():
                prompt = gr.Textbox(label="Prompt", placeholder="enter prompt", show_label=False, elem_id="prompt-in")
                video_inp = gr.Video(label="Video source", source="upload", type="filepath", include_audio=False, elem_id="input-vid")
                with gr.Row():
                    seed_inp = gr.Slider(label="Seed", minimum=0, maximum=2147483647, step=1, value=123456)
                    trim_in = gr.Slider(label="Cut video at (s)", minimun=1, maximum=3, step=1, value=1)
            with gr.Column():
                gr.HTML("""
                <a style="display:inline-block" href="https://huggingface.co/spaces/fffiloni/Pix2Pix-Video?duplicate=true"><img src="https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14" alt="Duplicate Space"></a> 
                work with longer videos / skip the queue: 
                """, elem_id="duplicate-container")
                video_out = gr.Video(label="Pix2pix video result", elem_id="video-output")
                submit_btn = gr.Button("Generate Pix2Pix video")

                with gr.Group(elem_id="share-btn-container", visible=False) as share_group:
                    community_icon = gr.HTML(community_icon_html)
                    loading_icon = gr.HTML(loading_icon_html)
                    share_button = gr.Button("Share to community", elem_id="share-btn")
        gr.HTML(article)
    
    inputs = [prompt,video_inp,seed_inp, trim_in]
    outputs = [video_out, share_group]
    
    submit_btn.click(infer, inputs, outputs)
    share_button.click(None, [], [], _js=share_js)

demo.launch().queue(max_size=12)