update input

app.py

@@ -63,7 +63,8 @@ MAX_IMAGE_SIZE = 512
 @spaces.GPU #[uncomment to use ZeroGPU]
 def infer(
     prompt,
-    raw_images,
+    ref1,
+    ref2,
     seed,
     randomize_seed,
     width,
@@ -109,16 +110,11 @@ with gr.Blocks(css=css) as demo:
         gr.Markdown("# Text-to-Image Gradio Template")
 
         with gr.Row():
-            prompt = gr.Text(
-                label="Prompt",
-                show_label=False,
-                max_lines=1,
-                placeholder="Enter your prompt",
-                container=False,
-            )
+            prompt = gr.Text(label="Prompt", show_label=False, max_lines=1,
+                             placeholder="Enter your prompt", container=False)
             run_button = gr.Button("Run", scale=0, variant="primary")
 
-        # 新增：两张输入图片
+        # 两张输入图片，其中 ref2 可为空
         with gr.Row():
             ref1 = gr.Image(label="Input Image 1", type="pil")
             ref2 = gr.Image(label="Input Image 2", type="pil")
@@ -126,68 +122,54 @@ with gr.Blocks(css=css) as demo:
         result = gr.Image(label="Result", show_label=False)
 
         with gr.Accordion("Advanced Settings", open=False):
-            seed = gr.Slider(
-                label="Seed",
-                minimum=0,
-                maximum=MAX_SEED,
-                step=1,
-                value=0,
-            )
+            seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=0)
             randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
-
             with gr.Row():
-                width = gr.Slider(
-                    label="Width",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=1024,
-                )
-                height = gr.Slider(
-                    label="Height",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=1024,
-                )
-
+                width = gr.Slider(label="Width", minimum=256, maximum=MAX_IMAGE_SIZE, step=32, value=1024)
+                height = gr.Slider(label="Height", minimum=256, maximum=MAX_IMAGE_SIZE, step=32, value=1024)
             with gr.Row():
-                guidance_scale = gr.Slider(
-                    label="Guidance scale",
-                    minimum=0.0,
-                    maximum=10.0,
-                    step=0.1,
-                    value=0.0,
-                )
-                num_inference_steps = gr.Slider(
-                    label="Number of inference steps",
-                    minimum=1,
-                    maximum=50,
-                    step=1,
-                    value=2,
-                )
-
-        # 如果 examples 只包含文本 prompt，保持如下即可
+                guidance_scale = gr.Slider(label="Guidance scale", minimum=0.0, maximum=10.0, step=0.1, value=0.0)
+                num_inference_steps = gr.Slider(label="Number of inference steps", minimum=1, maximum=50, step=1, value=2)
+
         examples = [
             ["a cute corgi in a wizard hat"],
             ["a watercolor painting of yosemite valley at sunrise"],
         ]
         gr.Examples(examples=examples, inputs=[prompt])
-    gr.on(
-        triggers=[run_button.click, prompt.submit],
-        fn=infer,
-        inputs=[
-            prompt,
-            [ref1, ref2],                # 新增：两张图
-            seed,
-            randomize_seed,
-            width,
-            height,
-            guidance_scale,
-            num_inference_steps,
-        ],
-        outputs=[result, seed],
-    )
+
+        # 用于装“可变长度”的参考图列表
+        refs_state = gr.State([])
+
+        # 先把两张图打包到 state，自动过滤 None，这样 ref2 就是可选的
+        def pack_refs(a, b):
+            return [x for x in (a, b) if x is not None]
+
+        # 你的推理函数接受“列表”refs
+        def infer(prompt, refs, seed, randomize_seed, width, height, guidance_scale, num_steps):
+            # 如需长度为2，可补齐到 [ref1, None]
+            if len(refs) == 0:
+                refs = [None, None]
+            elif len(refs) == 1:
+                refs = [refs[0], None]
+
+            # TODO: 在这里调用你的模型，使用 refs[0], refs[1]（第二张可能是 None）
+            # out_img = ...
+            # used_seed = ...
+            return out_img, used_seed
+
+        # 第一步：把 ref1/ref2 打包进 refs_state
+        dep = gr.on(
+            triggers=[run_button.click, prompt.submit],
+            fn=pack_refs,
+            inputs=[ref1, ref2],
+            outputs=refs_state,
+        )
+        # 第二步：再把打包好的列表传给 infer
+        dep.then(
+            fn=infer,
+            inputs=[prompt, refs_state, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
+            outputs=[result, seed],
+        )
 
 if __name__ == "__main__":
     demo.launch()