Update app.py

app.py

@@ -24,10 +24,10 @@ pipe.to(device)
 
 gallery = gr.Gallery(label="Generated images", show_label=False, elem_id="gallery").style(grid=[1], height="auto")
 
-def infer(prompt): 
-    
+def infer(prompt, guide, steps, seed, img_w, img_h): 
+    generator = torch.Generator('cpu').manual_seed(seed)
     #image = pipe(prompt, init_image=init_image)["sample"][0]
-    images_list = pipe([prompt] * 1, guidance_scale=7.5, num_inference_steps=25, height=512, width=512)    #TODO
+    images_list = pipe([prompt] * 1, guidance_scale=guide, num_inference_steps=steps, width=img_w, height=img_h)    #TODO
     images = []
     for i, image in enumerate(images_list["images"]):
         images.append(image)
@@ -39,4 +39,9 @@ print("okay")
 title="Marco Generation"
 description="Use 'mkmk woman' to get Marco pics. <br />Warning: Slow process... about 10 min inference time." 
 
-gr.Interface(fn=infer, inputs="text", outputs=gallery,title=title,description=description).queue(max_size=10).launch(enable_queue=True)
+gr.Interface(fn=infer, inputs=["text",
+    gr.Slider(2, 15, value = 7, label = 'Guidence Scale'),
+    gr.Slider(10, 50, value = 25, step = 1, label = 'Number of Iterations'),
+    gr.Slider(label = "Seed", minimum = 0, maximum = 2147483647, step = 1, randomize = True),
+    gr.Slider(label='Width', minimum = 512, maximum = 768, step = 256, value = 512),
+    gr.Slider(label='Height', minimum = 512, maximum = 768, step = 256, value = 512)], outputs=gallery,title=title,description=description).queue(max_size=100).launch(enable_queue=True)