Upload run_faceswap.py

run_faceswap.py

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+
+import os
+import torch
+from types import SimpleNamespace
+from SimSwap.models.models import create_model
+from PIL import Image
+from torchvision import transforms
+
+def run_faceswap(image_path_A, image_path_B, output_path):
+    opt = SimpleNamespace()
+    opt.name = "people"
+    opt.checkpoints_dir = "./checkpoints"
+    opt.gpu_ids = []
+    opt.isTrain = False
+    opt.resize_or_crop = 'none'
+    opt.crop_size = 224
+    opt.which_epoch = "latest"
+
+    # Añadir atributos requeridos para netG
+    opt.input_nc = 3
+    opt.output_nc = 3
+    opt.ngf = 64
+    opt.netG = 'unet_128'
+
+    model = create_model(opt)
+    model.eval()
+
+    transform = transforms.Compose([
+        transforms.Resize((224, 224)),
+        transforms.ToTensor()
+    ])
+
+    img_A = Image.open(image_path_A).convert("RGB")
+    img_B = Image.open(image_path_B).convert("RGB")
+
+    tensor_A = transform(img_A).unsqueeze(0)
+    tensor_B = transform(img_B).unsqueeze(0)
+
+    with torch.no_grad():
+        output = model(tensor_A, tensor_B)
+
+    output_img = transforms.ToPILImage()(output.squeeze(0))
+    output_img.save(output_path)