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import gradio as gr
import insightface
from insightface.app import FaceAnalysis
wellcomingMessage = """"""
assert insightface.__version__>='0.7'
value = 0
app = FaceAnalysis(name='buffalo_l')
app.prepare(ctx_id=0, det_size=(640, 640))
swapper = insightface.model_zoo.get_model('inswapper_128.onnx', download=True, download_zip=True)
def swap_faces(faceSource, sourceFaceId, faceDestination, destFaceId):
faces = app.get(faceSource)
faces = sorted(faces, key = lambda x : x.bbox[0])
if len(faces) < sourceFaceId or sourceFaceId < 1:
raise gr.Error(f"Source image only contains {len(faces)} faces, but you requested face {sourceFaceId}")
source_face = faces[sourceFaceId-1]
res_faces = app.get(faceDestination)
res_faces = sorted(res_faces, key = lambda x : x.bbox[0])
if len(res_faces) < destFaceId or destFaceId < 1:
raise gr.Error(f"Destination image only contains {len(res_faces)} faces, but you requested face {destFaceId}")
res_face = res_faces[destFaceId-1]
result = swapper.get(faceDestination, res_face, source_face, paste_back=True)
global value
value = value + 1
print(f"processed: {value}...")
# for face in faces:
# res = swapper.get(res, face, source_face, paste_back=True)
# cv2.imwrite("./t1_swapped.jpg", res)
return result
gr.Interface(swap_faces,
[
gr.Image(type="filepath", label="Input Image", sources=["upload", "clipboard"]),
gr.Number(precision=0, value=1, info='face position (from left, starting at 1)'),
gr.Image(sources=["clipboard", "upload"]),
gr.Number(precision=0, value=1, info='face position (from left, starting at 1)')
],
gr.Image(),
description=wellcomingMessage,
examples=[],
).launch() |