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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="์ด๋ฆ(ํ์ผ์ ์ฅ์ฉ)") | |
with gr.Row(): | |
user_image_input = gr.Image(type="pil", label="์ ์ ์ฌ์ง(์ผ๊ตด์ถ์ถ)", width=512, height=512) | |
result_image_input = gr.Image(type="pil", label="๊ฒฐ๊ณผ๋ฌผ ์ฌ์ง", width=512, height=512) | |
swap_btn = gr.Button("Swap Faces") | |
output_image = gr.Image(label="ํฉ์ฑ ํ ์ฌ์ง", width=512, height=512) | |
swap_btn.click(fn=faceswapper, inputs=[user_image_input, result_image_input, name], outputs=output_image) | |
demo.launch(debug=True) |