Update app.py

app.py

@@ -1,62 +1,62 @@
-from asyncio import constants
-import gradio as gr
-import requests
-import os 
-from base64 import b64decode
-from PIL import Image
-import io
-import numpy as np
-
-
-def generate_image(seed,psi):
-  iface = gr.Interface.load("spaces/hysts/StyleGAN-Human")
-  
-  print("calling interface",seed,psi)
-  img=iface(seed,psi)
-  return img
-  
-  #img=iface.fns[0].fn(seed,psi)
-  #wrong format, gah! convert to numpy array
-  #header, encoded = img.split(",", 1)
-  #data = b64decode(encoded)
-  #image = Image.open(io.BytesIO(data))
-  #image_np = np.array(image)
-  #return image_np
-
-def generate_model(img):
-
-    print("about to die")
-    iface = gr.Interface.load("spaces/radames/PIFu-Clothed-Human-Digitization")
-    print("calling interface")
-    #model,file=iface.fns[0].fn(img)
-    model,file=iface(img)
-    #print("got result",result)
-    return model,file
-
-
-demo = gr.Blocks()
-
-with demo:
-  gr.Markdown("<h1><center>StyleGan-Human + PIFu </center></h1>")
-  gr.Markdown(
-        "create a person and then generate a model from that person's image"
-    )
-    
-  
-  with gr.Row():
-    b0 = gr.Button("generate image")
-    b1 = gr.Button("generate model")
-  
-  with gr.Row():  
-    seed=gr.Number(default=0, label='Seed')
-    psi=gr.inputs.Slider(0, 2, step=0.05, default=0.7, label='Truncation psi')
-    #outputImage = gr.Image(label="portrait",type="filepath", shape=(256,256))
-    output_image = gr.outputs.Image(type="filepath", label='Output')
-    model = gr.Model3D(clear_color=[0.0, 0.0, 0.0, 0.0],  label="3D Model")
-    file= gr.File(label="Download 3D Model")
-
-  
-  b0.click(generate_image,inputs=[seed,psi],outputs=output_image)
-  b1.click(generate_model, inputs=output_image, outputs=[model,file])
-
+from asyncio import constants
+import gradio as gr
+import requests
+import os 
+from base64 import b64decode
+from PIL import Image
+import io
+import numpy as np
+
+
+def generate_image(seed,psi):
+  iface = gr.Interface.load("spaces/hysts/StyleGAN-Human")
+  
+  print("calling interface",seed,psi)
+  img=iface(seed,psi)
+  return img
+  
+  #img=iface.fns[0].fn(seed,psi)
+  #wrong format, gah! convert to numpy array
+  #header, encoded = img.split(",", 1)
+  #data = b64decode(encoded)
+  #image = Image.open(io.BytesIO(data))
+  #image_np = np.array(image)
+  #return image_np
+
+def generate_model(img):
+
+    print("about to die")
+    iface = gr.Interface.load("spaces/radames/PIFu-Clothed-Human-Digitization")
+    print("calling interface")
+    #model,file=iface.fns[0].fn(img)
+    model,file=iface(img)
+    #print("got result",result)
+    return model,file
+
+
+demo = gr.Blocks()
+
+with demo:
+  gr.Markdown("<h1><center>StyleGan-Human + PIFu </center></h1>")
+  gr.Markdown(
+        "create a person and then generate a model from that person's image"
+    )
+    
+  
+  with gr.Row():
+    b0 = gr.Button("generate image")
+    b1 = gr.Button("generate model")
+  
+  with gr.Row():  
+    seed=gr.Number(value=0, label='Seed')
+    psi=gr.inputs.Slider(0, 2, step=0.05, value=0.7, label='Truncation psi')
+    #outputImage = gr.Image(label="portrait",type="filepath", shape=(256,256))
+    output_image = gr.outputs.Image(type="filepath", label='Output')
+    model = gr.Model3D(clear_color=[0.0, 0.0, 0.0, 0.0],  label="3D Model")
+    file= gr.File(label="Download 3D Model")
+
+  
+  b0.click(generate_image,inputs=[seed,psi],outputs=output_image)
+  b1.click(generate_model, inputs=output_image, outputs=[model,file])
+
 demo.launch(enable_queue=True, debug=True)