app.py

import gradio as gr 
import yt_dlp
import os 
#import json
import numpy as np 
import cv2
import uuid
import moviepy
from moviepy.video.io.ffmpeg_tools import ffmpeg_extract_subclip
import moviepy.video.io.ImageSequenceClip
from moviepy.editor import *
from PIL import Image
os.system("yt-dlp -U")
uid=uuid.uuid4()
if not os.path.exists(f'{uid}'): os.makedirs(f'{uid}')
if not os.path.exists(f'{uid}-frames'): os.makedirs(f'{uid}-frames')
if not os.path.exists(f'{uid}-rembg'): os.makedirs(f'{uid}-rembg')
esr = gr.Interface.load("spaces/Omnibus/Real-ESRGAN-mod")
main_url= "https://omnibus-Deblur-Media.hf.space"
load_js = """
function(text_input, url_params) {
    console.log(text_input, url_params);
    const params = new URLSearchParams(window.location.search);
    url_params = Object.fromEntries(params);
    return [text_input, url_params]
}
"""
def load_video(vid):
    #os.system("yt-dlp -U")
    new_video_in = str(vid)
    capture = cv2.VideoCapture(new_video_in)
    fps = capture.get(cv2.CAP_PROP_FPS)
    msc = capture.get(cv2.CAP_PROP_POS_MSEC)
    frame_count = int(capture.get(cv2.CAP_PROP_FRAME_COUNT))
    msc = float(frame_count/fps)
    capture.release()
    vid_t = float(msc)
    hours = int(vid_t/360)
    minutes = int(vid_t/60)-(hours*360)
    seconds = vid_t-(minutes*60)-(hours*360)
    vid_len = f'{hours}:{minutes}:{seconds}'
    return frame_count, fps, vid_len, vid
def im_2_vid(images,fps):
    this_im=cv2.imread(images[0])
    height=this_im.shape[0]
    width= this_im.shape[1]
    size = (width, height)
    movie_clip = moviepy.video.io.ImageSequenceClip.ImageSequenceClip(images, fps)
    movie_clip.write_videofile(f'{uid}-rembg/bg_removed-{uid}.mp4')    
    return (f'{uid}-rembg/bg_removed-{uid}.mp4', f'{uid}-rembg/bg_removed-{uid}.mp4')
def predict(text, url_params):
    mod_url=""
    mod=gr.HTML("")
    out = None
    valid=gr.update(visible=False)
    mod_url = url_params.get('url')
    return ["" + text + "", mod_url]
def dl(inp,img):
    fps="Error"
    out = None
    out_file=[]
    if img == None and inp !="":
        try:
            inp_out=inp.replace("https://","")
            inp_out=inp_out.replace("/","_").replace(".","_").replace("=","_").replace("?","_")
            if "twitter" in inp:
                os.system(f'yt-dlp "{inp}" --extractor-arg "twitter:api=syndication" --trim-filenames 160 -o "{uid}/{inp_out}.mp4" -S res,mp4 --recode mp4')  
            else:
                os.system(f'yt-dlp "{inp}" --trim-filenames 160 -o "{uid}/{inp_out}.mp4" -S res,mp4 --recode mp4')  
                
            out = f"{uid}/{inp_out}.mp4"
            capture = cv2.VideoCapture(out)
            fps = capture.get(cv2.CAP_PROP_FPS)
            capture.release()
        except Exception as e:
            print(e)
            out = None
    elif img !=None and inp == "":
        capture = cv2.VideoCapture(img)
        fps = capture.get(cv2.CAP_PROP_FPS)
        capture.release()
        out = f"{img}"
    return out,out,out,out,fps
def trim_vid(vid,start_time,end_time):
    print (vid)
    start_hr=float(start_time.split(":",2)[0])*360
    start_min=int(start_time.split(":",2)[1])*60
    start_sec=int(start_time.split(":",2)[2])
    end_hr=int(end_time.split(":",2)[0])*360
    end_min=int(end_time.split(":",2)[1])*60
    end_sec=float(end_time.split(":",2)[2])
    start=start_hr+start_min+start_sec
    end=end_hr+end_min+end_sec
    clip = VideoFileClip(vid)
    mod_fps=clip.fps
    clip = clip.subclip(start, end)
    clip.write_videofile(f"{uid}-clip.mp4", fps=mod_fps)    
    #ffmpeg_extract_subclip(vid, start, end, targetname=f"{uid}-clip.mp4")
    out= f"{uid}-clip.mp4"
    capture = cv2.VideoCapture(out)    
    frame_count = int(capture.get(cv2.CAP_PROP_FRAME_COUNT))    
    capture.release()
    return out,frame_count


def video_clip(program,fps,qual,model_name,denoise_strength,face_enhance,outscale):
    _=None    
    fps=float(fps)
    new_video_in = str(f"{uid}-clip.mp4")
    capture = cv2.VideoCapture(new_video_in)
    frame_count = int(capture.get(cv2.CAP_PROP_FRAME_COUNT))
    fbox=[]
    out_box=[]
    cnt=0
    frame_count1= int(frame_count)
    for i in range(int(frame_count1)-1):
        capture.set(cv2.CAP_PROP_POS_FRAMES, i)
        ret, frame_f = capture.read(i)
        #frame_ff = cv2.cvtColor(frame_f, cv2.COLOR_BGR2RGB)
        cv2.imwrite(f'{uid}-frames/{i+1}.png',frame_f)
        fbox.append(f'{uid}-frames/{i+1}.png')
        mes=f'Working on {i+1} of {frame_count1}'
        yield _,_,mes
    yield _,_,"Frames Complete"
    if qual:
        mes = "Improving Quality"
        yield _,_,mes
    if qual:
        for i,img in enumerate(fbox):
            #print (img)
            out = os.path.abspath(img)
            out_url = f'{main_url}/file={out}'
            mes=f'Improving frame {i+1} of {frame_count}'
            yield _,_,mes
            out = esr(out_url, model_name, float(denoise_strength), face_enhance, int(outscale))
            #yield _,_,mes
            #cv2.imwrite(f'{img}',out)
            out_box.append(f'{out}')
            print (f'{main_url}/file={out}')
            #print (f'out::{out}')
        print (f'out_box::{out_box}')
        clip = ImageSequenceClip(out_box, fps = fps) 
    else:
        mes="Writing Video"
        clip = ImageSequenceClip(fbox, fps = fps) 
    yield _,_,"Writing Video"    
    videoclip = VideoFileClip(new_video_in)
    audioclip=videoclip.audio
    clip.audio=audioclip
    clip.write_videofile(f"{uid}/enhanced_vid.mp4")
    yield _,_,"Saving Video"    
    out = f"{uid}/enhanced_vid.mp4"
    yield out,out,"Video Complete"   

def gif_clip(program,fps,qual,model_name,denoise_strength,face_enhance,outscale):
    _=None    
    fps=float(fps)
    
    if program == 'imageio':
        print (f"NOT adjusting fps from: {fps} to: {fps*2}")
        fps=fps*2
    new_video_in = str(f"{uid}-clip.mp4")
    capture = cv2.VideoCapture(new_video_in)
    frame_count = int(capture.get(cv2.CAP_PROP_FRAME_COUNT))
    fbox=[]
    out_box=[]
    cnt=0
    frame_count1= int(frame_count)
    for i in range(int(frame_count1)-1):
        capture.set(cv2.CAP_PROP_POS_FRAMES, i)
        ret, frame_f = capture.read(i)
        cv2.imwrite(f'{uid}-frames/{i+1}.png',frame_f)
        fbox.append(f'{uid}-frames/{i+1}.png')
        mes=f'Working on {i+1} of {frame_count1}'
        yield _,_,mes
    yield _,_,"Frames Complete"
    if qual:
        mes = "Improving Quality"
        yield _,_,mes
    if qual:
        for i,img in enumerate(fbox):
            out = os.path.abspath(img)
            out_url = f'{main_url}/file={out}'
            mes=f'Improving frame {i+1} of {frame_count}'
            yield _,_,mes
            out = esr(out_url, model_name, float(denoise_strength), face_enhance, int(outscale))
            out_box.append(f'{out}')
            print (f'{main_url}/file={out}')
        clip = ImageSequenceClip(out_box, fps = fps) 
    else:
        clip = ImageSequenceClip(fbox, fps = fps) 
    yield _,_,"Writing GIF" 
    clip.to_gif(f"{uid}/clip_gif.gif",fps=fps, program=program) 
    #clip.speedx(2).to_gif(f"{uid}/clip_gif.gif",program=program)    
    out = f"{uid}/clip_gif.gif"
    yield out,out,"GIF Complete"   

def improve_img(inp,model_name,denoise_strength,face_enhance,outscale):
    _=None    
    yield _,"Reading image"
    
    #img=cv2.imread(inp)
    cv2.imwrite(f'{uid}-frames/tmp_im.png',cv2.cvtColor(inp, cv2.COLOR_BGR2RGB))
    out = os.path.abspath(f'{uid}-frames/tmp_im.png')
    out_url = f'{main_url}/file={out}'
    yield _,"Improving image"
    out = esr(out_url, model_name, float(denoise_strength), face_enhance, int(outscale))
    yield out,"Complete"   



def update_speed(inp,clip_speed,fps):
    if "-split.mp4" in inp:
        out_inp = f'{inp.split("-split.mp4",1)[0]}-split.mp4'
    else:
        out_inp = f'{inp.split(".mp4",1)[0]}-split.mp4'
    mod_fps=float(fps)*float(clip_speed)
    clip = VideoFileClip(inp)
    final = moviepy.video.fx.all.speedx(clip, factor=clip_speed)    
    final.write_videofile(f'{out_inp}', fps=mod_fps) 
    out = f'{out_inp}'
    return out,out,out
def echo_fn(inp):
    return inp 
def check_load(inp_url,outp_vid,hid_box,start_f,end_f):
    if outp_vid == None and inp_url !="":
        out_trim,in_vid,trim_count=trim_vid(hid_box,start_f,end_f)
    elif outp_vid !=None and inp_url == "":
        out_trim = None
        in_vid=outp_vid
        trim_count = ""
    return out_trim,in_vid,trim_count   
def run_samp(program,fps,qual,model_name,denoise_strength,face_enhance,outscale,frame_targ):
    _=None    
    #fps=float(fps)
    new_video_in = str(f"{uid}-clip.mp4")
    capture = cv2.VideoCapture(new_video_in)
    #frame_count1= int(frame_count)
    i=int(frame_targ)
    capture.set(cv2.CAP_PROP_POS_FRAMES, i)
    ret, frame_f = capture.read(i)
    #frame_ff = cv2.cvtColor(frame_f, cv2.COLOR_BGR2RGB)
    cv2.imwrite(f'{uid}-frames/{i}.png',frame_f)
    out = os.path.abspath(f'{uid}-frames/{i}.png')
    out_url = f'{main_url}/file={out}'
    yield _,"Creating Sample Frame","Creating Sample Frame"
    out = esr(out_url, model_name, float(denoise_strength), face_enhance, int(outscale))
    yield out,"Sample Frame Complete","Sample Frame Complete"         

def new_media(inp):
    if inp == "Image":
        im_box = gr.update(visible=True)
        vid_box = gr.update(visible=False)
        gif_row = gr.update(visible=False)
        vid_row = gr.update(visible=False)
        #qual = gr.update(value=True,interactive=False)
        return (im_box,vid_box,gif_row,vid_row)
    if inp == "Video":
        im_box = gr.update(visible=False)
        vid_box = gr.update(visible=True)
        gif_row = gr.update(visible=False)
        vid_row = gr.update(visible=True)
        #qual = gr.update(value=False,interactive=True)
        return (im_box,vid_box,gif_row,vid_row)
    if inp == "GIF":
        im_box = gr.update(visible=False)
        vid_box = gr.update(visible=True)
        gif_row = gr.update(visible=True)
        vid_row = gr.update(visible=False)            
        #qual = gr.update(value=False,interactive=True)
        return (im_box,vid_box,gif_row,vid_row)




    
css='''
#component-0{
background:repeating-radial-gradient(white, cornflowerblue);
}
.padded.svelte-90oupt{
background:cornflowerblue;
}
.dark .gr-box{
background:#344d74;!important;
opacity:1;!important;    
}
.p-2 {
background:#344d74;!important;
opacity:1;!important;
}
.gap-4 {
background:#6681ab;!important;
opacity:1;!important;
}
.dark .gr-padded{
background:#21314a;!important;
opacity:1;!important;
}
'''    
with gr.Blocks(css=css) as app:

    with gr.Row():
        gr.Column()
        with gr.Column():
            with gr.Group():
                choose_media = gr.Radio(label="Media Type",choices=["Image","Video","GIF"],value="Image")

                with gr.Accordion("Quality Options", open=False):
                    
                    with gr.Row():
                        model_name = gr.Dropdown(label="Real-ESRGAN Model",
                                                 choices=["RealESRGAN_x4plus", "RealESRNet_x4plus", "RealESRGAN_x4plus_anime_6B",
                                                          "RealESRGAN_x2plus", "realesr-general-x4v3"],
                                                 value="realesr-general-x4v3", show_label=True)
                        face_enhance = gr.Checkbox(label="Face Enhancement using GFPGAN",
                                                   value=False, show_label=True)
                        denoise_strength = gr.Slider(label="Denoise Strength",
                                                     minimum=0, maximum=1, step=0.1, value=0.5)
                        outscale = gr.Slider(label="Image Upscaling Factor",
                                             minimum=1, maximum=10, step=1, value=1, show_label=True)
  
            with gr.Box(visible=True) as im_box:
                with gr.Group():
                    inp_img_url=gr.Textbox(label="Image URL")
                    load_im_btn=gr.Button("Load URL")
                    inp_img=gr.Image(label = "Input Image")
                    with gr.Row():
                        proc_im_btn=gr.Button("Improve")
                        im_stat=gr.Textbox(label="Status")                    
                    outp_img=gr.Image(label="Enhanced Image")
            with gr.Box(visible=False) as vid_box:
                with gr.Group():
                    inp_url = gr.Textbox(label="Video URL")
                    go_btn = gr.Button("Run")
                    outp_vid=gr.Video(format="mp4")
                    with gr.Row():
                        frame_count=gr.Textbox(label="Frame Count",interactive = False)
                        fps=gr.Textbox(label="FPS",interactive = False)
                    outp_file=gr.Files()
                    clip_speed = gr.Slider(label="Speed", minimum=0.01, maximum=2, value=1, step=0.01)
                    speed_btn = gr.Button("Update Speed")
                    with gr.Row():
                        start_f = gr.Textbox(label = "Start", value = "0:00:00", placeholder = "0:00:23",interactive = True)
                        end_f = gr.Textbox(label = "End", value = "0:00:05", placeholder = "0:00:54",interactive = True)
                        trim_count = gr.Textbox(label="Trimmed Frames")
                    trim_btn=gr.Button("Trim")
                    out_trim=gr.Video(format="mp4")
                    hid_box = gr.Textbox(visible=False)
                    hid_fps = gr.Textbox(visible=False)

                    with gr.Row():
                        qual=gr.Checkbox(label="Improve Quality",value=False)
                    with gr.Accordion("Sample Frame",open=False):
                        with gr.Row():
                            frame_targ=gr.Number(label="Frame",value=1)
                            samp_btn=gr.Button("Get Sample")
                        samp_im = gr.Image(label="Sample Frame")  
                        

                    with gr.Column(visible=False) as gif_row:
                        with gr.Row():
                            choose_prog=gr.Radio(label="GIF Engine",choices=['imageio','ImageMagick','ffmpeg'], value = "imageio")
                        with gr.Row():
                            gif_btn = gr.Button("Make GIF")
                            gif_stat=gr.Textbox(label="Status")
                    with gr.Row(visible=False) as vid_row:
                        vid_btn = gr.Button("Make Video")
                        vid_stat=gr.Textbox(label="Status")
                    with gr.Row():
                        with gr.Column():
                            gif_show = gr.Video()
                        with gr.Column():
                            gif_file = gr.Files()   
        gr.Column()
    with gr.Row(visible=False):
        text_input=gr.Textbox()
        text_output=gr.Textbox()
        url_params=gr.JSON()

    def load_im_fn(inp):
        return inp
    
    load_im_btn.click(load_im_fn,inp_img_url,inp_img)
    proc_im_btn.click(improve_img,[inp_img,model_name,denoise_strength,face_enhance,outscale],[outp_img,im_stat])
    choose_media.change(new_media,choose_media,[im_box,vid_box,gif_row,vid_row])
    samp_btn.click(run_samp,[choose_prog,fps,qual,model_name,denoise_strength,face_enhance,outscale,frame_targ],[samp_im,gif_stat,vid_stat])    
    speed_btn.click(update_speed,[hid_box,clip_speed,hid_fps],[outp_vid,hid_box,outp_file])
    gif_btn.click(gif_clip,[choose_prog,fps,qual,model_name,denoise_strength,face_enhance,outscale],[gif_show,gif_file,gif_stat])
    vid_btn.click(video_clip,[choose_prog,fps,qual,model_name,denoise_strength,face_enhance,outscale],[gif_show,gif_file,vid_stat])
    
    trim_btn.click(trim_vid,[hid_box,start_f,end_f],[out_trim,trim_count])
    outp_vid.change(load_video,outp_vid,[frame_count,fps,end_f,hid_box]).then(trim_vid,[hid_box,start_f,end_f],[out_trim,trim_count])
    go_btn.click(dl,[inp_url,outp_vid],[outp_vid,outp_file,out_trim,hid_box,hid_fps])
    app.load(fn=predict, inputs=[text_input,url_params], outputs=[text_output,text_input],_js=load_js)
app.queue().launch(show_api=False)