Update app.py

app.py

@@ -146,6 +146,17 @@ def infer(use_custom_model, model_name, weight_name, custom_lora_weight, image_i
             variant="fp16"
         )
 
+    if preprocessor == "custom":
+        image = Image.open(image_in)
+        image = image.convert("RGB")
+        image = np.array(image)
+        image = Image.fromarray(image)
+
+        controlnet = ControlNetModel.from_pretrained(
+            "fffiloni/cn_malgras_second_002",
+            torch_dtype=torch.float16,
+        )
+
     pipe = StableDiffusionXLControlNetPipeline.from_pretrained(
         "stabilityai/stable-diffusion-xl-base-1.0",
         controlnet=controlnet,
@@ -329,7 +340,7 @@ with gr.Blocks(css=css) as demo:
 
             with gr.Column():
                 with gr.Group():
-                    preprocessor = gr.Dropdown(label="Preprocessor", choices=["canny", "lineart"], value="canny", interactive=True, info="For the moment, only canny is available")  
+                    preprocessor = gr.Dropdown(label="Preprocessor", choices=["canny", "lineart", "custom"], value="canny", interactive=True, info="For the moment, only canny is available")  
                     controlnet_conditioning_scale = gr.Slider(label="Controlnet conditioning Scale", minimum=0.1, maximum=1.0, step=0.01, value=0.5)
                 with gr.Group():
                     seed = gr.Slider(