Update app.py

app.py

@@ -3,7 +3,7 @@ from PIL import Image
 import torch
 import gradio as gr
 
-
+os.system("pip install dlib")
 import torch
 torch.backends.cudnn.benchmark = True
 from torchvision import transforms, utils
@@ -28,9 +28,9 @@ 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' 
@@ -66,7 +66,9 @@ plt.rcParams['figure.dpi'] = 150
 os.system("gdown https://drive.google.com/uc?id=1-8E0PFT37v5fZs-61oIrFbNpE28Unp2y")
 
 def inference(img):    
-    my_w = e4e_projection(img, "test.pt", device).unsqueeze(0)
+    aligned_face = align_face(img)
+
+    my_w = e4e_projection(aligned_face, "test.pt", device).unsqueeze(0)
     
     
     plt.rcParams['figure.dpi'] = 150
@@ -93,4 +95,4 @@ description = "Gradio Demo for JoJoGAN: One Shot Face Stylization. To use it, si
 article = "<p style='text-align: center'><a href='https://github.com/mchong6/JoJoGAN' target='_blank'>Github Repo Pytorch</a></p> <center><img src='https://visitor-badge.glitch.me/badge?page_id=akhaliq_jojogan' alt='visitor badge'></center> <p style='text-align: center'>samples from repo: <img src='https://raw.githubusercontent.com/mchong6/JoJoGAN/main/teaser.jpg' alt='animation'/></p>"
 
 examples=[['iu.jpeg']]
-gr.Interface(inference, [gr.inputs.Image(type="pil",shape=(512,512))], gr.outputs.Image(type="file"),title=title,description=description,article=article,enable_queue=True,allow_flagging=False,examples=examples).launch()
+gr.Interface(inference, [gr.inputs.Image(type="filepath",shape=(512,512))], gr.outputs.Image(type="file"),title=title,description=description,article=article,enable_queue=True,allow_flagging=False,examples=examples).launch()