Update app.py

app.py

@@ -36,13 +36,9 @@ from e4e.models.psp import pSp
 from util import *
 from huggingface_hub import hf_hub_download
 
-os.makedirs('models', exist_ok=True)
-os.system("gdown https://drive.google.com/uc?id=1jtCg8HQ6RlTmLdnbT2PfW1FJ2AYkWqsK")
-os.system("cp e4e_ffhq_encode.pt models/e4e_ffhq_encode.pt")
-
 device= 'cpu'
-model_path = hf_hub_download(repo_id="akhaliq/JoJoGAN_e4e_ffhq_encode", filename="e4e_ffhq_encode.pt")
-ckpt = torch.load(model_path, map_location='cpu')
+model_path_e = hf_hub_download(repo_id="akhaliq/JoJoGAN_e4e_ffhq_encode", filename="e4e_ffhq_encode.pt")
+ckpt = torch.load(model_path_e, map_location='cpu')
 opts = ckpt['opts']
 opts['checkpoint_path'] = model_path
 opts= Namespace(**opts)
@@ -77,12 +73,12 @@ os.system("mv shape_predictor_68_face_landmarks.dat models/dlibshape_predictor_6
 
 device = 'cpu' 
 
-os.system("gdown https://drive.google.com/uc?id=1_cTsjqzD_X9DK3t3IZE53huKgnzj_btZ")
 
 latent_dim = 512
 
+model_path_s = hf_hub_download(repo_id="akhaliq/jojogan-stylegan2-ffhq-config-f", filename="stylegan2-ffhq-config-f.pt")
 original_generator = Generator(1024, latent_dim, 8, 2).to(device)
-ckpt = torch.load('stylegan2-ffhq-config-f.pt', map_location=lambda storage, loc: storage)
+ckpt = torch.load(model_path_s, map_location=lambda storage, loc: storage)
 original_generator.load_state_dict(ckpt["g_ema"], strict=False)
 mean_latent = original_generator.mean_latent(10000)