test gradio

app.py

@@ -16,22 +16,22 @@ login(token=token)
 
 
 pipeline = AutoPipelineForText2Image.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16).to("cuda")
-pipeline.load_ip_adapter("h94/IP-Adapter", subfolder="sdxl_models", weight_name="ip-adapter_sdxl.bin")
 
 
 
 @spaces.GPU
-def generate_image(prompt, reference_image, controlnet_conditioning_scale):
-    style_image = Image.open(reference_image)
+def generate_image(prompt, reference_images, controlnet_conditioning_scale):
+    pipeline.load_ip_adapter(["h94/IP-Adapter"]*len(reference_images), subfolder="sdxl_models", weight_name="ip-adapter_sdxl.bin")
+    style_images = [Image.open(reference_image) for reference_image in reference_images]
     # reference_image.resize((512, 512))
     scale = {
-        "up": {"block_0": [0.0, controlnet_conditioning_scale, 0.0]},
+        "up": {"block_0": [0.0, controlnet_conditioning_scale/len(reference_images), 0.0]},
     }
-    pipeline.set_ip_adapter_scale(scale)
+    pipeline.set_ip_adapter_scale([scale]*len(reference_images))
 
     image = pipeline(
         prompt=prompt,
-        ip_adapter_image=style_image,
+        ip_adapter_image=style_images,
         negative_prompt="",
         guidance_scale=5,
         num_inference_steps=30,
@@ -44,7 +44,7 @@ interface = gr.Interface(
     fn=generate_image,
     inputs=[
         gr.Textbox(label="Prompt"),
-        gr.Image( type= "filepath",label="Reference Image (Style)"),
+        gr.inputs.File(file_count="multiple"),
         gr.Slider(label="Control Net Conditioning Scale", minimum=0, maximum=1.0, step=0.1, value=0.6),
     ],
     outputs="image",