Update app.py

app.py

@@ -79,7 +79,7 @@ generatorjoker = deepcopy(original_generator)
 
 generatorvoldemort = deepcopy(original_generator)
 
-# generatorjinx = deepcopy(original_generator)
+generatorpushpa = deepcopy(original_generator)
 
 # generatorcaitlyn = deepcopy(original_generator)
 
@@ -106,25 +106,18 @@ transform = transforms.Compose(
 
 
 modeljoker = hf_hub_download(repo_id="Abhinowww/Capstone", filename="JokerEightHundredFalse.pt")
-
-
 ckptjoker = torch.load(modeljoker, map_location=lambda storage, loc: storage)
-# print(ckptjoker.keys())
-# generatorjoker.load_state_dict(ckptjoker["g"], strict=False)
 generatorjoker.load_state_dict(ckptjoker, strict=False)
 
 
 modelvoldemort = hf_hub_download(repo_id="Abhinowww/Capstone", filename="VoldemortEightHundredFalse.pt")
-
 ckptvoldemort = torch.load(modelvoldemort, map_location=lambda storage, loc: storage)
-# generatorvoldemort.load_state_dict(ckptvoldemort["g"], strict=False)
 generatorvoldemort.load_state_dict(ckptvoldemort, 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)
+modelpushpa = hf_hub_download(repo_id="Abhinowww/Capstone", filename="PushpaFourHundredFalse.pt")
+ckptpushpa = torch.load(modelpushpa, map_location=lambda storage, loc: storage)
+generatorpushpa.load_state_dict(ckptpushpa, strict=False)
 
 
 # modelcaitlyn = hf_hub_download(repo_id="akhaliq/jojogan-arcane", filename="arcane_caitlyn_preserve_color.pt")
@@ -172,9 +165,9 @@ def inference(img, model):
     elif model == 'Voldemort':
         with torch.no_grad():
             my_sample = generatorvoldemort(my_w, input_is_latent=True)
-    # elif model == 'Jinx':
-    #     with torch.no_grad():
-    #         my_sample = generatorjinx(my_w, input_is_latent=True)
+    elif model == 'Pushpa':
+        with torch.no_grad():
+            my_sample = generatorpushpa(my_w, input_is_latent=True)
     # elif model == 'Caitlyn':
     #     with torch.no_grad():
     #         my_sample = generatorcaitlyn(my_w, input_is_latent=True)
@@ -207,7 +200,7 @@ description = "Capstone Project. To use it, simply upload your image, or click o
 # examples=[['mona.png','Joker']]
 # 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="pil"),title=title,description=description,article=article,allow_flagging=False,examples=examples,allow_screenshot=False).launch()
 
-css_code='body{background-image:url("https://picsum.photos/seed/picsum/200/300");}'
+# css_code='body{background-image:url("https://picsum.photos/seed/picsum/200/300");}'
+# gr.Interface(lambda x:x, "textbox", "textbox", css=css_code).launch(debug=True)
 
-gr.Interface(lambda x:x, "textbox", "textbox", css=css_code).launch(debug=True)
-gr.Interface(inference, [gr.inputs.Image(type="pil"),gr.inputs.Dropdown(choices=['Joker', 'Voldemort'], type="value", default='Joker', label="Model")], gr.outputs.Image(type="pil"),title=title,description=description,allow_flagging=False,allow_screenshot=False).launch()
+gr.Interface(inference, [gr.inputs.Image(type="pil"),gr.inputs.Dropdown(choices=['Joker', 'Voldemort', 'Pushpa'], type="value", default='Joker', label="Model")], gr.outputs.Image(type="pil"),title=title,description=description,allow_flagging=False,allow_screenshot=False).launch()