app.py

import gradio as gr
import subprocess as sp
import os
import uuid
import time
import shutil
from moviepy.editor import *
import cloudinary
import cloudinary.uploader

cloudinary.config( 
  cloud_name = "dlnrrexav", 
  api_key = "726116746471429", 
  api_secret = "TxV4FYkWvTmmskfi8dwedwYLOd0" 
)

def resize_video(file, export, duration, fps, width):
    # loading video dsa gfg intro video  
    clip = VideoFileClip(file)  
        
    # getting only first 5 seconds 
    if(clip.duration> 6):
        clip = clip.subclip(0, duration)
        # new clip with new duration 
        new_clip = clip.set_duration(duration) 
    else:
        new_clip = clip 

    w_old = new_clip.w
    h_old = new_clip.h
    
    if w_old > h_old:
        w = int(width)
        h = int(width * h_old / w_old)
    else:
        h = int(width)
        w = int(h * w_old / h_old)

    if(h % 2 != 0): h += 1
    
    if(w % 2 != 0): w += 1

    new_clip = new_clip.resize((w,h))

    new_clip.write_videofile(export, fps=fps, audio_codec='aac')

os.makedirs("./output", exist_ok=True)

def run(*args):
    source, target, unique_id, *rest_args = args

    print('target', target)

    new_target = './resize-vid.mp4'
    resize_video(file=target, export=new_target, duration=5, fps=12, width=800)
    target = new_target

    print('target', target)
    
    if not os.path.exists(source):
        return "Source file does not exist"
    if not os.path.exists(target):
        return "Target file does not exist"
    remove_old_directories("./output", num_minutes=60)
    filename = os.path.basename(target)
    os.makedirs(f"./output/{unique_id}",exist_ok=True)
    output = f"./output/{unique_id}/{filename}"
    frame_processor = rest_args[0]
    selected_frame_processors = ' '.join(frame_processor)

    face_analyser_direction = rest_args[1]
    face_recognition = rest_args[2]
    face_analyser_gender = rest_args[3]

    cmd = (
        f"python run.py --execution-providers cpu -s {source} -t {target} -o {output} "
        #f"python run.py --execution-providers cuda -s {source} -t {target} -o {output} "
        f"--frame-processors {selected_frame_processors} "
        f"--face-analyser-direction {face_analyser_direction} "
    )
    if face_recognition != 'none':
        cmd += f"--face-recognition {face_recognition} "
    if face_analyser_gender != 'none':
        cmd += f"--face-analyser-gender {face_analyser_gender} "

    if len(rest_args) > 4:
        skip_audio = rest_args[4]
        keep_fps = rest_args[5]
        keep_temp = rest_args[6]
        if skip_audio:
            cmd += "--skip-audio "
        if keep_fps:
            cmd += "--keep-fps "
        if keep_temp:
            cmd += "--keep-temp "

    try:
        print("Started...", cmd)
        start_time = time.time()
        output_text = sp.run(cmd, shell=True, capture_output=True, text=True).stdout
        end_time = time.time()
        print('time', end_time - start_time)
        print(output_text)
        #cloudinary.uploader.upload(output, resource_type = "video")
        return output
    except Exception as e:
        return f"An error occurred: {str(e)}"

def clear_output(unique_id):
    try:
        output_path = f"./output/{unique_id}"
        if os.path.exists(output_path):
            print("Trying to delete ")
            for filename in os.listdir(output_path):
                file_path = os.path.join(output_path, filename)
                if os.path.isfile(file_path):
                    os.remove(file_path)
                    print(f"Output files in {output_path} are deleted")
                    return "Output files for unique_id deleted"
                else:
                    print(f"Output files in {output_path} does not exist")
                    return "Output directory for (output_path} does not exist"
    except Exception as e:
        return f"An error occurred: {str(e)}"

def remove_old_directories(directory, num_minutes=60):
    now = time.time()

    for r, d, f in os.walk(directory):
        for dir_name in d:
            dir_path = os.path.join(r, dir_name)
            timestamp = os.path.getmtime(dir_path)
            age_minutes = (now - timestamp) / 60 # Convert to minutes
            
            if age_minutes >= num_minutes:
                try:
                    print("Removing", dir_path)
                    shutil.rmtree(dir_path)
                    print("Directory removed:", dir_path)
                except Exception as e:
                    print(e)
                    pass

def get_theme() -> gr.Theme:
    return gr.themes.Soft(
        primary_hue = gr.themes.colors.teal,
        secondary_hue = gr.themes.colors.gray,
        font = gr.themes.GoogleFont('Inter')
    ).set(
        background_fill_primary = '*neutral_50',
        block_label_text_size = '*text_sm',
        block_title_text_size = '*text_sm'
    )

with gr.Blocks(theme=get_theme(),api_name=False, api_open=False, show_api=False) as ui:

    gr.Markdown("""
    # Video Face Swap
    by [Tony Assi](https://www.tonyassi.com/)

    Videos get downsampled to 800 pixels (on the longest side), 5 second duration, and 12 fps. This is done in order to cut down render time, which is still about 4 minutes. Please ❤️ this Space.
    
    <a href="mailto: [email protected]">Email me</a> for access to your own High Def Video Face Swap app so you don't have to wait in line. Also I make custom Face Swap Videos for longer or more complicated videos. [email protected] 

    ---
    
    **Reference Mode** Looks at the first frame of the video to choose the face to face swap. Use the Face Analyzer Direction to decide which face.
    
    **Many Faces Mode** Will face swap all faces. Use this mode with the Gender Analyzer to pick gender.
    
    """)
    

    frame_processor_checkbox = gr.CheckboxGroup(
            choices = ['face_swapper', 'face_enhancer', 'frame_enhancer'],
            label = 'FRAME PROCESSORS',
            value = ['face_swapper'],  # Default value
            visible = False
    )

    face_analyser_age_dropdown = gr.Dropdown(
        label = 'FACE RECOGNITION',
        choices = ['none'] + ['reference', 'many'],
        value = 'reference',
        visible = True
    )
    
    face_analyser_direction_dropdown = gr.Dropdown(
        label = 'FACE ANALYSER DIRECTION (FOR REFERENCE MODE)',
        choices = ['left-right', 'right-left', 'top-bottom', 'bottom-top', 'small-large', 'large-small'],
        value = 'left-right',
        visible = True
    )
    
    face_analyser_gender_dropdown = gr.Dropdown(
        label = 'FACE ANALYSER GENDER',
        choices = ['none'] + ['male', 'female'],
        value = 'none'
    )
    
    unique_id = gr.Textbox(value=str(uuid.uuid4()), visible=False)

    source_image_video = gr.Image(type="filepath", label="SOURCE IMAGE")

    target_video = gr.Video(label="TARGET VIDEO")

    skip_audio = gr.Checkbox(label="SKIP AUDIO", visible = False)
    keep_fps = gr.Checkbox(label="KEEP FPS", value=True, visible = False)
    keep_temp = gr.Checkbox(label="KEEP TEMP", visible = False)

    video_button = gr.Button("START")
    clear_video_button = gr.ClearButton(value="CLEAR")
    video_output = gr.Video(label="OUTPUT")
    clear_video_button.add(video_output)
    video_button.click(
        run,
        inputs=[source_image_video, target_video, unique_id, frame_processor_checkbox, face_analyser_direction_dropdown, face_analyser_age_dropdown, face_analyser_gender_dropdown, skip_audio, keep_fps, keep_temp],
        outputs=video_output
    )
    clear_video_button.click(fn=clear_output, inputs=unique_id)

 
    gr.Examples(examples=[['bella1.jpg','./wiz-ex1.mp4', unique_id.value, frame_processor_checkbox.value, face_analyser_direction_dropdown.value, face_analyser_age_dropdown.value, face_analyser_gender_dropdown.value, skip_audio.value, keep_fps.value, keep_temp.value]], 
                inputs=[source_image_video, target_video, unique_id, frame_processor_checkbox, face_analyser_direction_dropdown, face_analyser_age_dropdown, face_analyser_gender_dropdown, skip_audio, keep_fps, keep_temp],
                outputs=video_output,
                fn=run,
                cache_examples=True
               )
               
                
            

ui.launch(debug=True)