Update app.py

app.py

@@ -49,7 +49,6 @@ models =[
     "wavymulder/modelshoot",
     "prompthero/openjourney-lora",
     "Fictiverse/Stable_Diffusion_VoxelArt_Model",
-    "nousr/robo-diffusion-2-base",
     "darkstorm2150/Protogen_v2.2_Official_Release",
     "hassanblend/HassanBlend1.5.1.2",
     "hassanblend/hassanblend1.4",
@@ -71,7 +70,6 @@ models =[
     "lckidwell/album-cover-style",
     "axolotron/ice-cream-animals",
     "perion/ai-avatar",
-    "FFusion/FFXL400",
     "digiplay/GhostMix",
     "ThePioneer/MISA",
     "TheLastBen/froggy-style-v21-768",
@@ -118,14 +116,14 @@ sdulers =[
 generator = torch.Generator(device="cpu").manual_seed(random.randint(0, MAX_SEED))
 
 def plex(mput, prompt, neg_prompt, stips, modal_id, dula, blip, blop):
+    apol = []
     modal_id = ""+modal_id+""
     dula=""+dula+"" ## shedulers todo
-    pope = accelerator.prepare(StableDiffusionPipeline.from_pretrained(modal_id, use_safetensors=True,torch_dtype=torch.float32))
+    pope = accelerator.prepare(StableDiffusionPipeline.from_pretrained(modal_id, use_safetensors=True,torch_dtype=torch.float32, safety_checker=None))
     pope.unet.to(memory_format=torch.channels_last)
     pope = accelerator.prepare(pope.to("cpu"))
-    pipe = accelerator.prepare(StableDiffusionControlNetPipeline.from_pretrained(modal_id, use_safetensors=True,controlnet=controlnet,torch_dtype=torch.float32))
-    pipe.unet.to(memory_format=torch.channels_last)
-    pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
+    pipe = accelerator.prepare(StableDiffusionControlNetPipeline.from_pretrained(modal_id, use_safetensors=True,controlnet=controlnet,torch_dtype=torch.float32,safety_checker=None))
+    pipe.scheduler = dula.from_config(pipe.scheduler.config)
     pipe = accelerator.prepare(pipe.to("cpu"))
     
     tilage = pope(prompt,num_inference_steps=5,height=512,width=512,generator=generator).images[0]
@@ -146,9 +144,13 @@ def plex(mput, prompt, neg_prompt, stips, modal_id, dula, blip, blop):
     openpose_image = openpose(mput)
     openpose_image.save('./fin.png','PNG')
     images = [openpose_image, canny_image]
+    apol.append(openpose_image)
+    apol.append(canny_image)
+    apol.append(tilage)
+    imoge = pipe([prompt] *2,images,num_inference_steps=stips,negative_prompt=[neg_prompt] *2,controlnet_conditioning_scale=[blip, blop],height=512,width=512,generator=generator).images
+    for i, imge in enumerate(imoge["images"]):
+        apol.append(imge)
+    return apol
 
-    image = pipe(prompt,images,num_inference_steps=stips,negative_prompt=neg_prompt,controlnet_conditioning_scale=[blip, blop],height=512,width=512,generator=generator).images[0]
-    return image
-
-iface = gr.Interface(fn=plex,inputs=[gr.Image(type="pil"), gr.Textbox(label="prompt"), gr.Textbox(label="neg_prompt", value="monochrome, lowres, bad anatomy, worst quality, low quality"), gr.Slider(label="infer_steps", value=20, minimum=1, step=1, maximum=100), gr.Dropdown(choices=models, value=models[0], type="value", label="select a model"), gr.Dropdown(choices=sdulers, value=sdulers[0], type="value", label="schedulrs"), gr.Slider(label="condition_scale_canny", value=0.5, minimum=0.1, step=0.1, maximum=1), gr.Slider(label="condition_scale_pose", value=0.5, minimum=0.1, step=0.1, maximum=1)], outputs=gr.Image(), title="Img2Img Guided Multi-Conditioned Canny/Pose Controlnet Selectable StableDiffusion Model Demo", description="by JoPmt.")
+iface = gr.Interface(fn=plex,inputs=[gr.Image(type="filepath"), gr.Textbox(label="prompt"), gr.Textbox(label="neg_prompt", value="monochrome, lowres, bad anatomy, worst quality, low quality"), gr.Slider(label="infer_steps", value=5, minimum=1, step=1, maximum=5), gr.Dropdown(choices=models, value=models[0], type="value", label="select a model"), gr.Dropdown(choices=sdulers, value=sdulers[0], type="value", label="schedulrs"), gr.Slider(label="condition_scale_canny", value=0.5, minimum=0.1, step=0.1, maximum=1), gr.Slider(label="condition_scale_pose", value=0.5, minimum=0.1, step=0.1, maximum=1)], outputs=gr.Gallery(columns=2), title="Img2Img Guided Multi-Conditioned Canny/Pose Controlnet Selectable StableDiffusion Model Demo", description="by JoPmt.")
 iface.launch()