Update app.py

app.py

@@ -108,14 +108,14 @@ async def generate_new_img(hex_code: str, prompt: str = Query(..., description="
                             Then from the initial image create a new image that will attract customers to put in an (ad template) 
                             Also, use this RGB color {hex_to_rgb(hex_code)} as a tone in the image while image is still recognized as it is original."""
             if device=="cpu":
-                controlnet = ControlNetModel.from_pretrained("lllyasviel/control_v11f1p_sd15_depth", torch_dtype=torch.float32, use_safetensors=True)
+                controlnet = ControlNetModel.from_pretrained("lllyasviel/control_v11f1p_sd15_depth", torch_dtype=torch.float32)
                 pipe = StableDiffusionControlNetImg2ImgPipeline.from_pretrained(
-                    "runwayml/stable-diffusion-v1-5", controlnet=controlnet, torch_dtype=torch.float32, use_safetensors=True
+                    "runwayml/stable-diffusion-v1-5", controlnet=controlnet, torch_dtype=torch.float32
                 ).to(device)
             else:
-                controlnet = ControlNetModel.from_pretrained("lllyasviel/control_v11f1p_sd15_depth", torch_dtype=torch.float16, use_safetensors=True)
+                controlnet = ControlNetModel.from_pretrained("lllyasviel/control_v11f1p_sd15_depth", torch_dtype=torch.float16)
                 pipe = StableDiffusionControlNetImg2ImgPipeline.from_pretrained(
-                    "runwayml/stable-diffusion-v1-5", controlnet=controlnet, torch_dtype=torch.float16, use_safetensors=True
+                    "runwayml/stable-diffusion-v1-5", controlnet=controlnet, torch_dtype=torch.float16
                 ).to(device)
                 pipe.enable_model_cpu_offload()
                 
@@ -132,6 +132,7 @@ async def generate_new_img(hex_code: str, prompt: str = Query(..., description="
             image = pipe(
                 ad_prompt, image=init_image
             ).images[0]
+            print(f"image type: {type(image)}")
             
             print("Image created")
             image_data = io.BytesIO()