it works

app.py

@@ -9,8 +9,222 @@ from huggingface_hub import snapshot_download
 os.makedirs("checkpoints", exist_ok=True)
 snapshot_download("alex4727/InstantDrag", local_dir="./checkpoints")
 
-def greet(name):
-    return "Hello " + name + "!!"
+from demo.demo_utils import (
+    process_img,
+    get_points,
+    undo_points_image,
+    clear_all,
+    InstantDragPipeline,
+)
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+LENGTH = 480  # Length of the square area displaying/editing images
+
+with gr.Blocks() as demo:
+    pipeline = InstantDragPipeline(seed=42, device="cuda", dtype=torch.float16)
+
+    with gr.Row():
+        gr.Markdown(
+            """
+            # InstantDrag: Improving Interactivity in Drag-based Image Editing
+            """
+        )
+    with gr.Tab(label="InstantDrag Demo"):
+        selected_points = gr.State([])         # Store points
+        original_image = gr.State(value=None)  # Store original input image
+        with gr.Row():
+            # Upload & Preprocess Image Column
+            with gr.Column():
+                gr.Markdown(
+                    """<p style="text-align: center; font-size: 20px">Upload & Preprocess Image</p>"""
+                )
+                canvas = gr.ImageEditor(
+                    height=LENGTH,
+                    width=LENGTH,
+                    type="numpy",
+                    image_mode="RGB",
+                    label="Preprocess Image",
+                    show_label=True,
+                    interactive=True,
+                )
+                with gr.Row():
+                    save_results = gr.Checkbox(
+                        value=False,
+                        label="Save Results",
+                        scale=1,
+                    )
+                    undo_button = gr.Button("Undo Clicked Points", scale=3)
+
+            # Click Points Column
+            with gr.Column():
+                gr.Markdown(
+                    """<p style="text-align: center; font-size: 20px">Click Points</p>"""
+                )
+                input_image = gr.Image(
+                    type="numpy",
+                    label="Click Points",
+                    show_label=True,
+                    height=LENGTH,
+                    width=LENGTH,
+                    interactive=False,
+                    show_fullscreen_button=False,
+                )
+                with gr.Row():
+                    run_button = gr.Button("Run")
+
+            # Editing Results Column
+            with gr.Column():
+                gr.Markdown(
+                    """<p style="text-align: center; font-size: 20px">Editing Results</p>"""
+                )
+                edited_image = gr.Image(
+                    type="numpy",
+                    label="Editing Results",
+                    show_label=True,
+                    height=LENGTH,
+                    width=LENGTH,
+                    interactive=False,
+                    show_fullscreen_button=False,
+                )
+                with gr.Row():
+                    clear_all_button = gr.Button("Clear All")
+        with gr.Tab("Configs - make sure to check README for details"):
+            with gr.Row():
+                with gr.Column():
+                    with gr.Row():
+                        flowgen_choices = sorted(
+                            [model for model in os.listdir("checkpoints/") if "flowgen" in model]
+                        )
+                        flowgen_ckpt = gr.Dropdown(
+                            value=flowgen_choices[0],
+                            label="Select FlowGen to use",
+                            choices=flowgen_choices,
+                            info="config2 for most cases, config3 for more fine-grained dragging",
+                            scale=2,
+                        )
+                        flowdiffusion_choices = sorted(
+                            [model for model in os.listdir("checkpoints/") if "flowdiffusion" in model]
+                        )
+                        flowdiffusion_ckpt = gr.Dropdown(
+                            value=flowdiffusion_choices[0],
+                            label="Select FlowDiffusion to use",
+                            choices=flowdiffusion_choices,
+                            info="single model for all cases",
+                            scale=1,
+                        )
+                        image_guidance = gr.Number(
+                            value=1.5,
+                            label="Image Guidance Scale",
+                            precision=2,
+                            step=0.1,
+                            scale=1,
+                            info="typically between 1.0-2.0.",
+                        )
+                        flow_guidance = gr.Number(
+                            value=1.5,
+                            label="Flow Guidance Scale",
+                            precision=2,
+                            step=0.1,
+                            scale=1,
+                            info="typically between 1.0-5.0",
+                        )
+                        num_steps = gr.Number(
+                            value=20,
+                            label="Inference Steps",
+                            precision=0,
+                            step=1,
+                            scale=1,
+                            info="typically between 20-50, 20 is usually enough",
+                        )
+                        flowgen_output_scale = gr.Number(
+                            value=-1.0,
+                            label="FlowGen Output Scale",
+                            precision=1,
+                            step=0.1,
+                            scale=2,
+                            info="-1.0, by default, forces flowgen's output to [-1, 1], could be adjusted to [0, ∞] for stronger/weaker effects",
+                        )
+        gr.Markdown(
+            """
+            <p style="text-align: center; font-size: 18px;">Examples</p>
+            """
+        )
+        with gr.Row():
+            gr.Examples(
+                examples=[
+                    "/home/user/app/InstDrag/demo/samples/airplane.jpg",
+                    "/home/user/app/InstDrag/demo/samples/anime.jpg",
+                    "/home/user/app/InstDrag/demo/samples/caligraphy.jpg",
+                    "/home/user/app/InstDrag/demo/samples/crocodile.jpg",
+                    "/home/user/app/InstDrag/demo/samples/elephant.jpg",
+                    "/home/user/app/InstDrag/demo/samples/meteor.jpg",
+                    "/home/user/app/InstDrag/demo/samples/monalisa.jpg",
+                    "/home/user/app/InstDrag/demo/samples/portrait.jpg",
+                    "/home/user/app/InstDrag/demo/samples/sketch.jpg",
+                    "/home/user/app/InstDrag/demo/samples/surreal.jpg",
+                ],
+                inputs=[canvas],
+                outputs=[original_image, selected_points, input_image],
+                fn=process_img,
+                cache_examples=False,
+                examples_per_page=10,
+            )
+        gr.Markdown(
+            """
+            <p style="text-align: center; font-size: 9">[Important] Our base models are solely trained on real-world talking head (facial) videos, with a focus on achieving fine-grained facial editing. <br>
+            Their application to other types of scenes, without fine-tuning, should be considered more of an experimental byproduct and may not perform well in many cases (we currently support only square images).</p>
+            """
+        )
+    # Event Handlers
+    canvas.change(
+        process_img,
+        [canvas],
+        [original_image, selected_points, input_image],
+    )
+
+    input_image.select(
+        get_points,
+        [input_image, selected_points],
+        [input_image],
+    )
+
+    undo_button.click(
+        undo_points_image,
+        [original_image],
+        [input_image, selected_points],
+    )
+
+    run_button.click(
+        pipeline.run,
+        [
+            original_image,
+            selected_points,
+            flowgen_ckpt,
+            flowdiffusion_ckpt,
+            image_guidance,
+            flow_guidance,
+            flowgen_output_scale,
+            num_steps,
+            save_results,
+        ],
+        [edited_image],
+    )
+
+    clear_all_button.click(
+        clear_all,
+        [],
+        [
+            canvas,
+            input_image,
+            edited_image,
+            selected_points,
+            original_image,
+        ],
+    )
+
+demo.queue().launch(ssr_mode=False)
+
+# def greet(name):
+#     return "Hello " + name + "!!"
+
+# demo = gr.Interface(fn=greet, inputs="text", outputs="text")
+# demo.launch()