test_wholeimage_swapsingle.py 2.5 KB

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  1. import cv2
  2. import torch
  3. import fractions
  4. import numpy as np
  5. from PIL import Image
  6. import torch.nn.functional as F
  7. from torchvision import transforms
  8. from models.models import create_model
  9. from options.test_options import TestOptions
  10. from insightface_func.face_detect_crop_single import Face_detect_crop
  11. from util.reverse2original import reverse2wholeimage
  12. import os
  13. from util.add_watermark import watermark_image
  14. def lcm(a, b): return abs(a * b) / fractions.gcd(a, b) if a and b else 0
  15. transformer_Arcface = transforms.Compose([
  16. transforms.ToTensor(),
  17. transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
  18. ])
  19. def _totensor(array):
  20. tensor = torch.from_numpy(array)
  21. img = tensor.transpose(0, 1).transpose(0, 2).contiguous()
  22. return img.float().div(255)
  23. if __name__ == '__main__':
  24. opt = TestOptions().parse()
  25. start_epoch, epoch_iter = 1, 0
  26. crop_size = 224
  27. torch.nn.Module.dump_patches = True
  28. logoclass = watermark_image('./simswaplogo/simswaplogo.png')
  29. model = create_model(opt)
  30. model.eval()
  31. app = Face_detect_crop(name='antelope', root='./insightface_func/models')
  32. app.prepare(ctx_id= 0, det_thresh=0.6, det_size=(640,640))
  33. pic_a = opt.pic_a_path
  34. img_a_whole = cv2.imread(pic_a)
  35. img_a_align_crop, _ = app.get(img_a_whole,crop_size)
  36. img_a_align_crop_pil = Image.fromarray(cv2.cvtColor(img_a_align_crop[0],cv2.COLOR_BGR2RGB))
  37. img_a = transformer_Arcface(img_a_align_crop_pil)
  38. img_id = img_a.view(-1, img_a.shape[0], img_a.shape[1], img_a.shape[2])
  39. # convert numpy to tensor
  40. img_id = img_id.cuda()
  41. #create latent id
  42. img_id_downsample = F.interpolate(img_id, scale_factor=0.5)
  43. latend_id = model.netArc(img_id_downsample)
  44. latend_id = F.normalize(latend_id, p=2, dim=1)
  45. ############## Forward Pass ######################
  46. pic_b = opt.pic_b_path
  47. img_b_whole = cv2.imread(pic_b)
  48. img_b_align_crop_list, b_mat_list = app.get(img_b_whole,crop_size)
  49. # detect_results = None
  50. swap_result_list = []
  51. for b_align_crop in img_b_align_crop_list:
  52. b_align_crop_tenor = _totensor(cv2.cvtColor(b_align_crop,cv2.COLOR_BGR2RGB))[None,...].cuda()
  53. swap_result = model(None, b_align_crop_tenor, latend_id, None, True)[0]
  54. swap_result_list.append(swap_result)
  55. reverse2wholeimage(swap_result_list, b_mat_list, crop_size, img_b_whole, logoclass, os.path.join(opt.output_path, 'result_whole_swapsingle.jpg'), opt.no_simswaplogo)
  56. print(' ')
  57. print('************ Done ! ************')