Update README.md

README.md

@@ -62,11 +62,11 @@ controlnet = FluxMultiControlNetModel([controlnet_union]) # we always recommend
 pipe = FluxControlNetPipeline.from_pretrained(base_model, controlnet=controlnet, torch_dtype=torch.bfloat16)
 pipe.to("cuda")
 
-prompt = 'a young girl'
-control_image_depth = load_image("https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Union/resolve/main/images/depth.jpg")
+prompt = 'A bohemian-style female travel blogger with sun-kissed skin and messy beach waves.'
+control_image_depth = load_image("https://huggingface.co/Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro/resolve/main/assets/depth.jpg")
 control_mode_depth = 2
 
-control_image_canny = load_image("https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Union/resolve/main/images/canny.jpg")
+control_image_canny = load_image("https://huggingface.co/Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro/resolve/main/assets/canny.jpg")
 control_mode_canny = 0
 
 width, height = control_image.size
@@ -77,7 +77,7 @@ image = pipe(
     control_mode=[control_mode_depth, control_mode_canny],
     width=width,
     height=height,
-    controlnet_conditioning_scale=[0.5, 0.5],
+    controlnet_conditioning_scale=[0.2, 0.4],
     num_inference_steps=24, 
     guidance_scale=3.5,
     generator=torch.manual_seed(42),
@@ -86,6 +86,8 @@ image = pipe(
 
 We also support loading multiple ControlNets as before, you can load as
 ```python
+from diffusers import FluxControlNetModel, FluxMultiControlNetModel
+
 controlnet_model_union = './Shakker-Labs/FLUX.1-dev-Controlnet-Union'
 controlnet_union = FluxControlNetModel.from_pretrained(controlnet_model_union, torch_dtype=torch.bfloat16)