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import os |
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import time |
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import numpy as np |
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import numexpr as ne |
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from multiprocessing.dummy import Process, Queue |
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from face_detect.face_align_68 import face_alignment_landmark |
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from face_detect.face_detect import FaceDetect |
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from face_lib.face_swap import HifiFace |
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from face_restore.gfpgan_onnx_api import GFPGAN |
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from face_restore.xseg_onnx_api import XSEG |
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TRACKING_THRESHOLD = 0.15 |
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def cosine_vectorized_v3(array1, array2): |
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sumyy = np.einsum('ij,ij->i', array2, array2) |
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sumxx = np.einsum('ij,ij->i', array1, array1)[:, None] |
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sumxy = array1.dot(array2.T) |
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sqrt_sumxx = ne.evaluate('sqrt(sumxx)') |
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sqrt_sumyy = ne.evaluate('sqrt(sumyy)') |
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return ne.evaluate('(sumxy/sqrt_sumxx)/sqrt_sumyy') |
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class Consumer0Base(Process): |
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def __init__(self, opt, frame_queue_in, feature_dst_list=None, queue_list=None, block=True, fps_counter=False): |
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super().__init__() |
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self.queue_list = queue_list |
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self.fps_counter = fps_counter |
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self.block = block |
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self.pid = os.getpid() |
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self.opt = opt |
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self.frame_queue_in = frame_queue_in |
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self.feature_dst_list = feature_dst_list |
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self.crop_size = self.opt.input_size |
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self.scrfd_detector = FaceDetect(mode='scrfd_500m', tracking_thres=TRACKING_THRESHOLD) |
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self.face_alignment = face_alignment_landmark(lm_type=68) |
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print('init consumer {}, pid is {}.'.format(self.__class__.__name__, self.pid)) |
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class Consumer1BaseONNX(Process): |
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def __init__(self, opt, feature_list, queue_list: list, block=True, fps_counter=False,provider='gpu', load_xseg=True, xseg_flag=False): |
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super().__init__() |
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self.queue_list = queue_list |
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self.fps_counter = fps_counter |
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self.block = block |
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self.pid = os.getpid() |
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self.opt = opt |
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self.feature_list = feature_list |
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self.crop_size = self.opt.input_size |
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self.xseg_flag = xseg_flag |
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print("model_name:", self.opt.model_name) |
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self.hf = HifiFace(model_name='er8_bs1', provider=provider) |
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if load_xseg: |
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self.xseg = XSEG(model_type='xseg_0611', provider=provider) |
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def switch_xseg(self): |
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self.xseg_flag = not self.xseg_flag |
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def predict(self, src_face_image, dst_face_latent): |
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mask_out, swap_face_out = self.hf.forward(src_face_image, dst_face_latent) |
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if self.xseg_flag: |
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mask_out = self.xseg.forward(swap_face_out)[None,None] |
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return [mask_out, swap_face_out] |
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class Consumer2Base(Process): |
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def __init__(self, queue_list: list, frame_queue_out, block=True, fps_counter=False): |
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super().__init__() |
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self.queue_list = queue_list |
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self.fps_counter = fps_counter |
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self.block = block |
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self.pid = os.getpid() |
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self.frame_queue_out = frame_queue_out |
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print('init consumer {}, pid is {}.'.format(self.__class__.__name__, self.pid)) |
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def run(self): |
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counter = 0 |
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start_time = time.time() |
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while True: |
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something_in = self.queue_list[0].get() |
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if something_in is None: |
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print('subprocess {} exit !'.format(self.pid)) |
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break |
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self.forward_func(something_in) |
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if self.fps_counter: |
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counter += 1 |
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if (time.time() - start_time) > 4: |
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print("Consumer2 FPS: {}".format(counter / (time.time() - start_time))) |
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counter = 0 |
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start_time = time.time() |
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print('c2 stop') |
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class Consumer3Base(Process): |
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def __init__(self, queue_list, block=True, fps_counter=False, provider='gpu'): |
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super().__init__() |
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self.queue_list = queue_list |
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self.fps_counter = fps_counter |
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self.block = block |
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self.pid = os.getpid() |
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self.gfp = GFPGAN(model_type='GFPGANv1.4', provider=provider) |
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print('init consumer {}, pid is {}.'.format(self.__class__.__name__, self.pid)) |
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def run(self): |
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counter = 0 |
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start_time = time.time() |
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while True: |
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something_in = self.queue_list[0].get() |
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if something_in is None: |
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print('subprocess {} exit !'.format(self.pid)) |
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self.queue_list[1].put(None) |
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break |
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self.forward_func(something_in) |
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if self.fps_counter: |
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counter += 1 |
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if (time.time() - start_time) > 4: |
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print("Consumer3 FPS: {}".format(counter / (time.time() - start_time))) |
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counter = 0 |
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start_time = time.time() |
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print('c3 stop') |
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