Update app.py

app.py

@@ -24,8 +24,7 @@ import numpy as np
 from huggingface_hub import hf_hub_download
 
 def run(image, mode, sample_c=1.3,  num_samples=3, sample_step=100):
-    device = torch.device("cuda") #if torch.cuda.is_available() else torch.device("cpu")
- 
+    device = torch.device("cuda") if torch.cuda.is_available() else torch.device("cpu")
     parser, parser_up = create_argparser()
     
     args = parser.parse_args()
@@ -216,15 +215,14 @@ iface = gr.Interface(fn=run, inputs=[
     # gr.Image(image_mode="L", source="canvas", type="pil", shape=(256,256), invert_colors=False, tool="editor"),
     gr.inputs.Radio(label="Input Mode - The type of your input", choices=["mask", "sketch"],default="sketch"),
     gr.inputs.Slider(label="sample_c - The strength of classifier-free guidance",default=1.4, minimum=1.0, maximum=2.0),
-    gr.inputs.Slider(label="Number of samples - How many samples you wish to generate", default=2, step=1, minimum=1, maximum=8),
-    gr.inputs.Slider(label="Number of Steps - How many steps you want to use", default=100, step=10, minimum=10, maximum=1000),
+    gr.inputs.Slider(label="Number of samples - How many samples you wish to generate", default=4, step=1, minimum=1, maximum=16),
+    gr.inputs.Slider(label="Number of Steps - How many steps you want to use", default=100, step=10, minimum=50, maximum=1000),
     ], 
     outputs=[image],
     css=css,
     title="Generate images from sketches with PITI",
     description="<div>By uploading a sketch map or a semantic map and pressing submit, you can generate images based on your input. As the computing device is CPU, the running may be slow.</div>",
-    examples=[["1.png", "sketch", 1.3, 2, 100], ["2.png", "sketch", 1.3, 2, 100],["3.png", "sketch", 1.3, 2, 100],["4.png", "mask", 1.3, 2, 100],["5.png", "mask", 1.3, 2, 100],["6.png", "mask", 1.3, 2, 100]],
-    cache_examples=False)
-
+    examples=[["1.png", "sketch", 1.3, 4, 100], ["2.png", "sketch", 1.3, 4, 100],["3.png", "sketch", 1.3, 4, 100],["4.png", "mask", 1.3, 4, 100],["5.png", "mask", 1.3, 4, 100],["6.png", "mask", 1.3, 4, 100]])
+   
 iface.launch(enable_queue=True)
- 
+