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Fffc / app.py

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output image 수정하기

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	import gradio as gr
	import cv2
	import numpy as np
	import insightface
	from insightface.app import FaceAnalysis
	import datetime
	import os
	from PIL import Image


	def faceswapper(user_image, result_image, username="test"):
	output_folder = 'outputs'

	# Convert PIL images to NumPy arrays for processing
	guest_img = np.array(user_image)
	result_img = np.array(result_image)

	# Convert RGB (PIL) to BGR (OpenCV)
	guest_img = guest_img[:, :, ::-1]
	result_img = result_img[:, :, ::-1]


	# Initialize the FaceAnalysis app
	app = FaceAnalysis(name='buffalo_l')
	app.prepare(ctx_id=0, det_size=(640, 640))

	# Initialize the face swapper model
	swapper = insightface.model_zoo.get_model('inswapper_128.onnx', download=False, download_zip=False)

	# Detect face in the guest image
	guest_faces = app.get(guest_img)
	guest_face = guest_faces[0]

	# Detect faces in the result image
	faces = app.get(result_img)

	# Perform face swapping
	for face in faces:
	result_img = swapper.get(result_img, face, guest_face, paste_back=True)

	# Save the result in the specified output folder
	if not os.path.exists(output_folder):
	os.makedirs(output_folder)
	current_time = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
	output_path = os.path.join(output_folder, f'{username}_swapped_face_{current_time}.jpg')
	cv2.imwrite(output_path, result_img)

	# Convert the final image from BGR to RGB before returning
	result_img = cv2.cvtColor(result_img, cv2.COLOR_BGR2RGB)


	# Convert back to PIL image
	result_img_pil = Image.fromarray(result_img)
	original_size = result_image.size
	result_img_pil = result_img_pil.resize(original_size, Image.Resampling.LANCZOS)

	return result_img_pil

	with gr.Blocks() as demo:
	with gr.Row():
	with gr.Column():
	name = gr.Textbox(label="이름(파일저장용)")
	with gr.Row():
	user_image_input = gr.Image(type="pil", label="유저사진(얼굴추출)", width=512, height=512)
	result_image_input = gr.Image(type="pil", label="결과물 사진", width=512, height=512)
	swap_btn = gr.Button("Swap Faces")
	output_image = gr.Image(label="합성 후 사진", width=512, height=512)
	swap_btn.click(fn=faceswapper, inputs=[user_image_input, result_image_input, name], outputs=output_image)

	demo.launch(debug=True)