Fix

app.py

@@ -34,7 +34,7 @@ from util import *
 from huggingface_hub import hf_hub_download
 
 device= 'cpu'
-model_path_e = hf_hub_download(repo_id="akhaliq/JoJoGAN_e4e_ffhq_encode", filename="e4e_ffhq_encode.pt")
+model_path_e = hf_hub_download(repo_id="bankholdup/stylegan_petbreeder", filename="e4e_ffhq5_cat.pt")
 ckpt = torch.load(model_path_e, map_location='cpu')
 opts = ckpt['opts']
 opts['checkpoint_path'] = model_path_e
@@ -61,144 +61,21 @@ def projection(img, name, device='cuda'):
     return w_plus[0]
 
 
-
-
-device = 'cpu' 
-
-
-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(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)
-
-generatorjojo = deepcopy(original_generator)
-
-generatordisney = deepcopy(original_generator)
-
-generatorjinx = deepcopy(original_generator)
-
-generatorcaitlyn = deepcopy(original_generator)
-
-generatoryasuho = deepcopy(original_generator)
-
-generatorarcanemulti = deepcopy(original_generator)
-
-generatorart = deepcopy(original_generator)
-
-generatorspider = deepcopy(original_generator)
-
-generatorsketch = deepcopy(original_generator)
-
-
-transform = transforms.Compose(
-    [
-        transforms.Resize((1024, 1024)),
-        transforms.ToTensor(),
-        transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5)),
-    ]
-)
-
-
-
-
-modeljojo = hf_hub_download(repo_id="akhaliq/JoJoGAN-jojo", filename="jojo_preserve_color.pt")
-
-
-ckptjojo = torch.load(modeljojo, map_location=lambda storage, loc: storage)
-generatorjojo.load_state_dict(ckptjojo["g"], strict=False)
-
-
-modeldisney = hf_hub_download(repo_id="akhaliq/jojogan-disney", filename="disney_preserve_color.pt")
-
-ckptdisney = torch.load(modeldisney, map_location=lambda storage, loc: storage)
-generatordisney.load_state_dict(ckptdisney["g"], strict=False)
-
-
-modeljinx = hf_hub_download(repo_id="akhaliq/jojo-gan-jinx", filename="arcane_jinx_preserve_color.pt")
-
-ckptjinx = torch.load(modeljinx, map_location=lambda storage, loc: storage)
-generatorjinx.load_state_dict(ckptjinx["g"], strict=False)
-
-
-modelcaitlyn = hf_hub_download(repo_id="akhaliq/jojogan-arcane", filename="arcane_caitlyn_preserve_color.pt")
-
-ckptcaitlyn = torch.load(modelcaitlyn, map_location=lambda storage, loc: storage)
-generatorcaitlyn.load_state_dict(ckptcaitlyn["g"], strict=False)
-
-
-modelyasuho = hf_hub_download(repo_id="akhaliq/JoJoGAN-jojo", filename="jojo_yasuho_preserve_color.pt")
-
-ckptyasuho = torch.load(modelyasuho, map_location=lambda storage, loc: storage)
-generatoryasuho.load_state_dict(ckptyasuho["g"], strict=False)
-
-
-model_arcane_multi = hf_hub_download(repo_id="akhaliq/jojogan-arcane", filename="arcane_multi_preserve_color.pt")
-
-ckptarcanemulti = torch.load(model_arcane_multi, map_location=lambda storage, loc: storage)
-generatorarcanemulti.load_state_dict(ckptarcanemulti["g"], strict=False)
-
-
-modelart = hf_hub_download(repo_id="akhaliq/jojo-gan-art", filename="art.pt")
-
-ckptart = torch.load(modelart, map_location=lambda storage, loc: storage)
-generatorart.load_state_dict(ckptart["g"], strict=False)
-
-
-modelSpiderverse = hf_hub_download(repo_id="akhaliq/jojo-gan-spiderverse", filename="Spiderverse-face-500iters-8face.pt")
-
-ckptspider = torch.load(modelSpiderverse, map_location=lambda storage, loc: storage)
-generatorspider.load_state_dict(ckptspider["g"], strict=False)
-
-modelSketch = hf_hub_download(repo_id="akhaliq/jojogan-sketch", filename="sketch_multi.pt")
-
-ckptsketch = torch.load(modelSketch, map_location=lambda storage, loc: storage)
-generatorsketch.load_state_dict(ckptsketch["g"], strict=False)
-
 def inference(img, model):  
     img.save('out.jpg')  
     aligned_face = align_face('out.jpg')
         
-    my_w = projection(aligned_face, "test.pt", device).unsqueeze(0)
-    if model == 'JoJo':
-        with torch.no_grad():
-            my_sample = generatorjojo(my_w, input_is_latent=True)  
-    elif model == 'Disney':
-        with torch.no_grad():
-            my_sample = generatordisney(my_w, input_is_latent=True)
-    elif model == 'Jinx':
-        with torch.no_grad():
-            my_sample = generatorjinx(my_w, input_is_latent=True)
-    elif model == 'Caitlyn':
-        with torch.no_grad():
-            my_sample = generatorcaitlyn(my_w, input_is_latent=True)
-    elif model == 'Yasuho':
-        with torch.no_grad():
-            my_sample = generatoryasuho(my_w, input_is_latent=True)
-    elif model == 'Arcane Multi':
-        with torch.no_grad():
-            my_sample = generatorarcanemulti(my_w, input_is_latent=True)
-    elif model == 'Art':
-        with torch.no_grad():
-            my_sample = generatorart(my_w, input_is_latent=True)
-    elif model == 'Spider-Verse':
-        with torch.no_grad():
-            my_sample = generatorspider(my_w, input_is_latent=True)
-    else:
-        with torch.no_grad():
-            my_sample = generatorsketch(my_w, input_is_latent=True)
-            
+    my_w = projection(aligned_face, "test.pt", device).unsqueeze(0)           
     
-    npimage = my_sample[0].permute(1, 2, 0).detach().numpy()
+    npimage = my_w.permute(1, 2, 0).detach().numpy()
     imageio.imwrite('filename.jpeg', npimage)
     return 'filename.jpeg'
   
 title = "JoJoGAN"
 description = "Gradio Demo for JoJoGAN: One Shot Face Stylization. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below."
 
-article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2112.11641' target='_blank'>JoJoGAN: One Shot Face Stylization</a>| <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>"
-
-examples=[['mona.png','Jinx']]
-gr.Interface(inference, [gr.inputs.Image(type="pil"),gr.inputs.Dropdown(choices=['JoJo', 'Disney','Jinx','Caitlyn','Yasuho','Arcane Multi','Art','Spider-Verse','Sketch'], type="value", default='JoJo', label="Model")], gr.outputs.Image(type="file"),title=title,description=description,article=article,allow_flagging=False,examples=examples,allow_screenshot=False).launch()
+gr.Interface(inference, 
+[gr.inputs.Image(type="pil")], 
+gr.outputs.Image(type="file"),
+title=title,
+description=description).launch()