add input image column

app.py

@@ -46,7 +46,7 @@ def infer(
         negative_prompt=negative_prompt,
         guidance_scale=0.,
         num_inference_steps=4,
-        width=1920,
+        width=1420,
         height=1080,
         max_sequence_length=256,
     ).images[0]
@@ -68,90 +68,94 @@ css = """
 """
 
 with gr.Blocks(css=css) as demo:
-    with gr.Column(elem_id="col-container"):
-        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,
-            )
-
-            run_button = gr.Button("Run", scale=0, variant="primary")
-
-        result = gr.Image(label="Result", show_label=False)
-
-        with gr.Accordion("Advanced Settings", open=False):
-            negative_prompt = gr.Text(
-                label="Negative prompt",
-                max_lines=1,
-                placeholder="Enter a negative prompt",
-                visible=False,
-            )
-
-            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():
+        with gr.Column(elem_id="col-input-image"):
+            gr.Markdown(" # Drop your image here")
+            gr.Image()
+        with gr.Column(elem_id="col-container"):
+            gr.Markdown(" # Text-to-Image Gradio Template")
 
             with gr.Row():
-                width = gr.Slider(
-                    label="Width",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=1024,  # Replace with defaults that work for your model
+                prompt = gr.Text(
+                    label="Prompt",
+                    show_label=False,
+                    max_lines=1,
+                    placeholder="Enter your prompt",
+                    container=False,
                 )
 
-                height = gr.Slider(
-                    label="Height",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=1024,  # Replace with defaults that work for your model
-                )
+                run_button = gr.Button("Run", scale=0, variant="primary")
 
-            with gr.Row():
-                guidance_scale = gr.Slider(
-                    label="Guidance scale",
-                    minimum=0.0,
-                    maximum=10.0,
-                    step=0.1,
-                    value=0.0,  # Replace with defaults that work for your model
+            result = gr.Image(label="Result", show_label=False)
+
+            with gr.Accordion("Advanced Settings", open=False):
+                negative_prompt = gr.Text(
+                    label="Negative prompt",
+                    max_lines=1,
+                    placeholder="Enter a negative prompt",
+                    visible=False,
                 )
 
-                num_inference_steps = gr.Slider(
-                    label="Number of inference steps",
-                    minimum=1,
-                    maximum=50,
+                seed = gr.Slider(
+                    label="Seed",
+                    minimum=0,
+                    maximum=MAX_SEED,
                     step=1,
-                    value=2,  # Replace with defaults that work for your model
+                    value=0,
                 )
 
-        gr.Examples(examples=examples, inputs=[prompt])
-    gr.on(
-        triggers=[run_button.click, prompt.submit],
-        fn=infer,
-        inputs=[
-            prompt,
-            negative_prompt,
-            seed,
-            randomize_seed,
-            width,
-            height,
-            guidance_scale,
-            num_inference_steps,
-        ],
-        outputs=[result, seed],
-    )
+                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,  # Replace with defaults that work for your model
+                    )
+
+                    height = gr.Slider(
+                        label="Height",
+                        minimum=256,
+                        maximum=MAX_IMAGE_SIZE,
+                        step=32,
+                        value=1024,  # Replace with defaults that work for your model
+                    )
+
+                with gr.Row():
+                    guidance_scale = gr.Slider(
+                        label="Guidance scale",
+                        minimum=0.0,
+                        maximum=10.0,
+                        step=0.1,
+                        value=0.0,  # Replace with defaults that work for your model
+                    )
+
+                    num_inference_steps = gr.Slider(
+                        label="Number of inference steps",
+                        minimum=1,
+                        maximum=50,
+                        step=1,
+                        value=2,  # Replace with defaults that work for your model
+                    )
+
+            gr.Examples(examples=examples, inputs=[prompt])
+        gr.on(
+            triggers=[run_button.click, prompt.submit],
+            fn=infer,
+            inputs=[
+                prompt,
+                negative_prompt,
+                seed,
+                randomize_seed,
+                width,
+                height,
+                guidance_scale,
+                num_inference_steps,
+            ],
+            outputs=[result, seed],
+        )
 
 if __name__ == "__main__":
     demo.launch()