Update app.py

app.py

@@ -51,7 +51,6 @@ def generate_image(prompt: str, negative_prompt: str = "", inference_steps: int
     images = pipeline.numpy_to_pil(images)
     return images[0]
 
-
 examples = [
     ["A watercolor painting of a bird"],
     ["A watercolor painting of an otter"]
@@ -59,6 +58,9 @@ examples = [
 css = """
         .gradio-container {
             font-family: 'IBM Plex Sans', sans-serif;
+            max-width: 730px!important;
+            margin: auto;
+            padding-top: 1.5rem;
         }
         .gr-button {
             color: white;
@@ -154,7 +156,7 @@ css = """
             display: flex; padding-left: 0.5rem !important; padding-right: 0.5rem !important; background-color: #000000; justify-content: center; align-items: center; border-radius: 9999px !important; width: 13rem;
             margin-top: 10px;
             margin-left: auto;
-        }
+        
         #share-btn {
             all: initial; color: #ffffff;font-weight: 600; cursor:pointer; font-family: 'IBM Plex Sans', sans-serif; margin-left: 0.5rem !important; padding-top: 0.25rem !important; padding-bottom: 0.25rem !important;right:0;
         }
@@ -168,16 +170,18 @@ css = """
         #share-btn-container .wrap {
             display: none !important;
         }
-        
+        .share_button {
+            color:#6366f1!important;
+        }
         .gr-form{
             flex: 1 1 50%; border-top-right-radius: 0; border-bottom-right-radius: 0;
         }
         #prompt-text-input, #negative-prompt-text-input{padding: .45rem 0.625rem}
-        #component-16{border-top-width: 1px!important;margin-top: 1em}
         .image_duplication{position: absolute; width: 100px; left: 50px}
+
 """
 
-block = gr.Blocks(css=css)
+block = gr.Blocks(theme="gradio/soft",css=css)
 
 with block as demo:
     gr.HTML(
@@ -237,64 +241,51 @@ with block as demo:
     with gr.Group():
         with gr.Box():
             with gr.Row(elem_id="prompt-container").style(equal_height=True):
-                with gr.Column():
+                with gr.Column(scale=2):
                     prompt_input = gr.Textbox(
                         label="Enter your prompt",
                         max_lines=1,
-                        placeholder="A watercolor painting of a bird",
+                        placeholder="Enter your prompt",
                         elem_id="prompt-text-input",
-                    ).style(
-                        border=(True, False, True, True),
-                        rounded=(True, False, False, True),
-                        container=False,
+                        show_label=False,
                     )
                     negative = gr.Textbox(
                         label="Enter your negative prompt",
                         max_lines=1,
-                        placeholder="tree",
+                        placeholder="Enter a negative prompt",
                         elem_id="negative-prompt-text-input",
-                    ).style(
-                        border=(True, False, True, True),
-                        rounded=(True, False, False, True),
-                        container=False,
+                        show_label=False,
                     )
-                btn = gr.Button("Generate image").style(
-                    margin=False,
-                    rounded=(False, True, True, False),
-                    full_width=False,
-                )
+                btn = gr.Button("Generate image", label="Primary Button", variant="primary")
 
         gallery = gr.Gallery(
             label="Generated images", show_label=False, elem_id="gallery"
         ).style(grid=[2], height="auto")
 
-        with gr.Group(elem_id="container-advanced-btns"):
-            # advanced_button = gr.Button("Advanced options", elem_id="advanced-btn")
-            with gr.Group(elem_id="share-btn-container"):
-                community_icon = gr.HTML(community_icon_html)
-                loading_icon = gr.HTML(loading_icon_html)
-                share_button = gr.Button(
-                    "Share to community", elem_id="share-btn")
 
-        with gr.Accordion("Advanced settings", open=False):
-            #    gr.Markdown("Advanced settings are temporarily unavailable")
-            #    samples = gr.Slider(label="Images", minimum=1, maximum=4, value=4, step=1)
-            #    steps = gr.Slider(label="Steps", minimum=1, maximum=50, value=45, step=1)
-            inf_steps_input = gr.inputs.Slider(
-                minimum=1, maximum=100, default=25, step=1, label="Inference Steps"
-            )
-            seed_input = gr.inputs.Number(default=0, label="Seed")
-            guidance_scale = gr.Slider(
-                label="Guidance Scale", minimum=0, maximum=50, value=9, step=0.1
-            )
+        with gr.Row():
+            with gr.Column(scale=2):
+                with gr.Accordion("Advanced settings"):
+                    seed_input = gr.inputs.Number(default=0, label="Seed")
+                    inf_steps_input = gr.inputs.Slider(
+                        minimum=1, maximum=100, default=25, step=1, label="Inference Steps"
+                    )
+                    guidance_scale = gr.inputs.Slider(
+                        label="Guidance Scale", minimum=0, maximum=50, default=9, step=0.1
+                    )
+            with gr.Column(scale=1):
+                # advanced_button = gr.Button("Advanced options", elem_id="advanced-btn")
+                ex = gr.Examples(examples=examples,
+                    fn=generate_image,
+                    inputs=[prompt_input, negative,
+                            inf_steps_input, seed_input, guidance_scale],
+                    outputs=[gallery],
+                    cache_examples=False)
+                ex.dataset.headers = [""]
+
+                share_button = gr.Button("Share to community",elem_classes="share_button")
+        
 
-        ex = gr.Examples(examples=examples,
-                         fn=generate_image,
-                         inputs=[prompt_input, negative,
-                                 inf_steps_input, seed_input, guidance_scale],
-                         outputs=[gallery],
-                         cache_examples=True)
-        ex.dataset.headers = [""]
         negative.submit(generate_image, inputs=[
                         prompt_input, negative, inf_steps_input, seed_input, guidance_scale], outputs=[gallery], postprocess=False)
         prompt_input.submit(generate_image, inputs=[
@@ -308,14 +299,7 @@ with block as demo:
             [],
             _js=share_js,
         )
-        gr.HTML(
-            """
-                <div class="footer">
-                    <p>Model by Stable Diffusion Nano Team
-                    </p>
-                </div>
-           """
-        )
+        gr.Markdown("Model by Stable Diffusion Nano Team",elem_classes="footer")
         with gr.Accordion(label="License", open=False):
             gr.HTML(
                 """
@@ -323,9 +307,10 @@ with block as demo:
                     <p><h4>LICENSE</h4>
                     The model is licensed with a <a href="https://huggingface.co/stabilityai/stable-diffusion-2/blob/main/LICENSE-MODEL" style="text-decoration: underline;" target="_blank">CreativeML OpenRAIL++</a> license. The authors claim no rights on the outputs you generate, you are free to use them and are accountable for their use which must not go against the provisions set in this license. The license forbids you from sharing any content that violates any laws, produce any harm to a person, disseminate any personal information that would be meant for harm, spread misinformation and target vulnerable groups. For the full list of restrictions please <a href="https://huggingface.co/spaces/CompVis/stable-diffusion-license" target="_blank" style="text-decoration: underline;" target="_blank">read the license</a></p>
                     <p><h4>Biases and content acknowledgment</h4>
-                    Despite how impressive being able to turn text into image is, beware to the fact that this model may output content that reinforces or exacerbates societal biases, as well as realistic faces, pornography and violence. The model was trained on the <a href="https://laion.ai/blog/laion-5b/" style="text-decoration: underline;" target="_blank">LAION-5B dataset</a>, which scraped non-curated image-text-pairs from the internet (the exception being the removal of illegal content) and is meant for research purposes. You can read more in the <a href="https://huggingface.co/CompVis/stable-diffusion-v1-4" style="text-decoration: underline;" target="_blank">model card</a></p>
+                    Despite how impressive being able to turn text into image is, beware to the fact that this model may output content that reinforces or exacerbates societal biases, as well as realistic faces, pornography and violence. The model was trained on the <a href="https://huggingface.co/datasets/laion/laion2B-en-aesthetic" style="text-decoration: underline;" target="_blank">LAION-2B Aesthetic dataset</a>, which scraped non-curated image-text-pairs from the internet (the exception being the removal of illegal content) and is meant for research purposes. You can read more in the <a href="https://huggingface.co/bguisard/stable-diffusion-nano-2-1" style="text-decoration: underline;" target="_blank">model card</a></p>
                </div>
                 """
             )
 demo.queue(concurrency_count=10)
 demo.launch()
+