Update app.py

app.py

@@ -8,6 +8,8 @@ from accelerate import Accelerator
 
 accelerator = Accelerator()
 models =[
+    "prompthero/midjourney-v4-diffusion",
+    "nitrosocke/classic-anim-diffusion",
     "stablediffusionapi/disney-pixal-cartoon",
     "stablediffusionapi/edge-of-realism",
     "sd-dreambooth-library/original-character-cyclps",
@@ -46,7 +48,6 @@ models =[
     "digiplay/AIGEN_v1.4_diffusers",
     "stablediffusionapi/dreamshaper-v6",
     "axolotron/ice-cream-animals",
-    "FFusion/FFXL400",
     "TheLastBen/froggy-style-v21-768",
     "FloydianSound/Nixeu_Diffusion_v1-5",
     "digiplay/PotoPhotoRealism_v1",
@@ -55,15 +56,9 @@ models =[
 def plex(prompt,modil):
     pipe = accelerator.prepare(AutoPipelineForText2Image.from_pretrained(""+modil+"", torch_dtype=torch.float32))
     pipe = accelerator.prepare(pipe.to("cpu"))
-    # prompt = "A fantasy landscape, Cinematic lighting"
-    # negative_prompt = "low quality, bad quality"
-
-    #rmage = load_image(goof)
-    #original_image = rmage.convert("RGB")
-    #original_image.thumbnail((512, 512))
-
-    image = pipe(prompt=prompt, num_inference_steps=5).images[0]
+    image = pipe(prompt=prompt, num_inference_steps=10).images[0]
     return image
 
-iface = gr.Interface(fn=plex,inputs=[gr.Textbox(label="Prompt"), gr.Dropdown(choices=models, type="value", value=models[random.randint(1, len(models))])],outputs=gr.Image(),title="AutoPipelineForText2Image_SD_Multi",description="AutoPipelineForText2Image_SD_Multi")
-iface.launch()
+iface = gr.Interface(fn=plex,outputs=gr.Image(label="Generated Output Image"),inputs=[gr.Dropdown(choices=models, type="value", value=models[random.randint(1, len(models)), gr.Textbox(label="Prompt"), gr.Textbox(label="negative_prompt", value="low quality, bad quality")])], title="AutoPipelineForText2Image_SD_Multi",description="AutoPipelineForText2Image_SD_Multi")
+iface.queue(max_size=1)
+iface.launch(max_threads=1)