Update app.py

app.py

@@ -2,7 +2,7 @@ import os
 from PIL import Image
 import torch
 import gradio as gr
-os.system("pip install dlib")
+#os.system("pip install dlib")
 os.system("git clone https://github.com/mchong6/JoJoGAN.git")
 os.chdir("JoJoGAN")
 
@@ -29,9 +29,9 @@ os.makedirs('style_images', exist_ok=True)
 os.makedirs('style_images_aligned', exist_ok=True)
 os.makedirs('models', exist_ok=True)
 
-os.system("wget http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2")
-os.system("bzip2 -dk shape_predictor_68_face_landmarks.dat.bz2")
-os.system("mv shape_predictor_68_face_landmarks.dat models/dlibshape_predictor_68_face_landmarks.dat")
+#os.system("wget http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2")
+#os.system("bzip2 -dk shape_predictor_68_face_landmarks.dat.bz2")
+#os.system("mv shape_predictor_68_face_landmarks.dat models/dlibshape_predictor_68_face_landmarks.dat")
 
 
 device = 'cpu' 
@@ -44,7 +44,7 @@ latent_dim = 512
 
 # Load original generator
 original_generator = Generator(1024, latent_dim, 8, 2).to(device)
-ckpt = torch.load(os.path.join('models', 'stylegan2-ffhq-config-f.pt'), map_location=lambda storage, loc: storage)
+ckpt = torch.load('stylegan2-ffhq-config-f.pt', map_location=lambda storage, loc: storage)
 original_generator.load_state_dict(ckpt["g_ema"], strict=False)
 mean_latent = original_generator.mean_latent(10000)
 
@@ -60,21 +60,12 @@ transform = transforms.Compose(
 )
 
 plt.rcParams['figure.dpi'] = 150
-os.system("gdown https://drive.google.com/uc?id=1-7UlCppmiG4DKbhYDNbIZTc6mHy9JMWJ")
-os.system("mv e4e_ffhq_encode.pt models/e4e_ffhq_encode.pt")
 
 
 os.system("gdown https://drive.google.com/uc?id=1-8E0PFT37v5fZs-61oIrFbNpE28Unp2y")
-os.system("mv e4e_ffhq_encode.pt models/jojo.pt")
 
-def inference(img):
-    filepath = img
-    
-    name = strip_path_extension(filepath)+'.pt'
-    
-    aligned_face = align_face(filepath)
-    
-    my_w = e4e_projection(aligned_face, name, device).unsqueeze(0)
+def inference(img):    
+    my_w = e4e_projection(img, "test.pt", device).unsqueeze(0)
     
     
     plt.rcParams['figure.dpi'] = 150
@@ -83,7 +74,7 @@ def inference(img):
     preserve_color = False 
     
 
-    ckpt = torch.load(os.path.join('models', 'jojo.pt'), map_location=lambda storage, loc: storage)
+    ckpt = torch.load('jojo.pt', map_location=lambda storage, loc: storage)
     generator.load_state_dict(ckpt["g"], strict=False)
     
     with torch.no_grad():
@@ -98,4 +89,4 @@ title = "AnimeGANv2"
 description = "Gradio Demo for AnimeGanv2 Face Portrait. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please use a cropped portrait picture for best results similar to the examples below."
 article = "<p style='text-align: center'><a href='https://github.com/bryandlee/animegan2-pytorch' target='_blank'>Github Repo Pytorch</a></p> <center><img src='https://visitor-badge.glitch.me/badge?page_id=akhaliq_animegan' alt='visitor badge'></center> <p style='text-align: center'>samples from repo: <img src='https://user-images.githubusercontent.com/26464535/129888683-98bb6283-7bb8-4d1a-a04a-e795f5858dcf.gif' alt='animation'/> <img src='https://user-images.githubusercontent.com/26464535/137619176-59620b59-4e20-4d98-9559-a424f86b7f24.jpg' alt='animation'/><img src='https://user-images.githubusercontent.com/26464535/127134790-93595da2-4f8b-4aca-a9d7-98699c5e6914.jpg' alt='animation'/></p>"
 
-gr.Interface(inference, [gr.inputs.Image(type="filepath")], gr.outputs.Image(type="numpy"),title=title,description=description,article=article,enable_queue=True,allow_flagging=False).launch()
+gr.Interface(inference, [gr.inputs.Image(type="pil")], gr.outputs.Image(type="numpy"),title=title,description=description,article=article,enable_queue=True,allow_flagging=False).launch()