import numpy as np import gradio as gr import roop.globals from roop.core import ( start, decode_execution_providers, suggest_max_memory, suggest_execution_threads, ) from roop.processors.frame.core import get_frame_processors_modules from roop.utilities import normalize_output_path import os from PIL import Image def swap_face(source_file, target_file, doFaceEnhancer): # Resize images to reduce processing load source_image = Image.fromarray(source_file) target_image = Image.fromarray(target_file) # Resize to a smaller dimension if necessary source_image.thumbnail((512, 512)) target_image.thumbnail((512, 512)) source_path = "input.jpg" target_path = "target.jpg" source_image.save(source_path, format="JPEG") target_image.save(target_path, format="JPEG") print("source_path: ", source_path) print("target_path: ", target_path) roop.globals.source_path = source_path roop.globals.target_path = target_path output_path = "output.jpg" roop.globals.output_path = normalize_output_path( roop.globals.source_path, roop.globals.target_path, output_path ) # Limit processing to what is necessary for CPU if doFaceEnhancer: roop.globals.frame_processors = ["face_swapper", "face_enhancer"] else: roop.globals.frame_processors = ["face_swapper"] # Optimize for CPU roop.globals.headless = True roop.globals.keep_fps = False # Disable to reduce processing roop.globals.keep_audio = False # Disable to reduce processing roop.globals.keep_frames = False roop.globals.many_faces = False roop.globals.video_encoder = "libx264" roop.globals.video_quality = 24 # Lower quality for faster processing roop.globals.max_memory = suggest_max_memory() # Use all available memory roop.globals.execution_providers = decode_execution_providers(["cpu"]) # Use CPU only roop.globals.execution_threads = suggest_execution_threads() # Utilize all CPU cores print( "start process", roop.globals.source_path, roop.globals.target_path, roop.globals.output_path, ) for frame_processor in get_frame_processors_modules(roop.globals.frame_processors): if not frame_processor.pre_check(): return start() return output_path html_section_2 = "

This model is running on CPU and might be slow.

" app = gr.Blocks() with app: gr.HTML(html_section_2) gr.Interface( fn=swap_face, inputs=[gr.Image(), gr.Image(), gr.Checkbox(label="Enhance", info="Face Enhancer")], outputs="image" ) app.launch()