| import roop.globals |
| import cv2 |
| import numpy as np |
| import onnx |
| import onnxruntime |
|
|
| from roop.typing import Face, Frame |
| from roop.utilities import resolve_relative_path |
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|
| class FaceSwapInsightFace(): |
| plugin_options:dict = None |
| model_swap_insightface = None |
|
|
| processorname = 'faceswap' |
| type = 'swap' |
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|
| def Initialize(self, plugin_options:dict): |
| if self.plugin_options is not None: |
| if self.plugin_options["devicename"] != plugin_options["devicename"]: |
| self.Release() |
|
|
| self.plugin_options = plugin_options |
| if self.model_swap_insightface is None: |
| model_path = resolve_relative_path('../models/inswapper_128.onnx') |
| graph = onnx.load(model_path).graph |
| self.emap = onnx.numpy_helper.to_array(graph.initializer[-1]) |
| self.devicename = self.plugin_options["devicename"].replace('mps', 'cpu') |
| self.input_mean = 0.0 |
| self.input_std = 255.0 |
| |
| sess_options = onnxruntime.SessionOptions() |
| sess_options.enable_cpu_mem_arena = False |
| self.model_swap_insightface = onnxruntime.InferenceSession(model_path, sess_options, providers=roop.globals.execution_providers) |
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| |
| def Run(self, source_face: Face, target_face: Face, temp_frame: Frame) -> Frame: |
| blob = cv2.dnn.blobFromImage(temp_frame, 1.0 / self.input_std, (128, 128), |
| (self.input_mean, self.input_mean, self.input_mean), swapRB=True) |
| latent = source_face.normed_embedding.reshape((1,-1)) |
| latent = np.dot(latent, self.emap) |
| latent /= np.linalg.norm(latent) |
| io_binding = self.model_swap_insightface.io_binding() |
| io_binding.bind_cpu_input("target", blob) |
| io_binding.bind_cpu_input("source", latent) |
| io_binding.bind_output("output", self.devicename) |
| self.model_swap_insightface.run_with_iobinding(io_binding) |
| ort_outs = io_binding.copy_outputs_to_cpu()[0] |
| img_fake = ort_outs.transpose((0,2,3,1))[0] |
| return np.clip(255 * img_fake, 0, 255).astype(np.uint8)[:,:,::-1] |
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| img_fake, M = self.model_swap_insightface.get(temp_frame, target_face, source_face, paste_back=False) |
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| def Release(self): |
| del self.model_swap_insightface |
| self.model_swap_insightface = None |
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