Update app.py

app.py

@@ -107,14 +107,14 @@ examples = [
     [
         "./asset/0.jpg",
         None,
-        "a cute monster, masterpiece, best quality, high quality",
+        "3D model, cute monster, high quality",
         1.0,
         0.0,
     ],
     [
         "./asset/2.jpg",
         "./asset/house.jpg",
-        "a house, masterpiece, best quality, high quality",
+        "3d model, house, kawai, cute, sci-fi, solarpunk, high quality",
         1.0,
         0.6,
     ],
@@ -232,30 +232,17 @@ def pil_to_cv2(image_pil):
 
 # Description
 title = r"""
-<h1 align="center">InstantStyle: Free Lunch towards Style-Preserving in Text-to-Image Generation</h1>
+<h1 align="center">I2I mit SDXL-Lightning & IP-Adapter</h1>
 """
 
 description = r"""
-<b>Forked from <a href='https://github.com/InstantStyle/InstantStyle' target='_blank'>InstantStyle: Free Lunch towards Style-Preserving in Text-to-Image Generation</a>.<br>
-<b>Model by <a href='https://huggingface.co/ByteDance/SDXL-Lightning' target='_blank'>SDXL Lightning</a> and <a href='https://huggingface.co/h94/IP-Adapter' target='_blank'>IP-Adapter</a>.</b><br>
+<b>ARM <3 GoldExtra Testversion<br>
+<b>Wir schauen uns gut funktionierende Prompts. Bitte diese notieren und an Hidéo weiterleiten!</b><br>
 """
 
 article = r"""
----
-📝 **Citation**
 <br>
-If our work is helpful for your research or applications, please cite us via:
-```bibtex
-@article{wang2024instantstyle,
-  title={InstantStyle: Free Lunch towards Style-Preserving in Text-to-Image Generation},
-  author={Wang, Haofan and Wang, Qixun and Bai, Xu and Qin, Zekui and Chen, Anthony},
-  journal={arXiv preprint arXiv:2404.02733},
-  year={2024}
-}
-```
-📧 **Contact**
-<br>
-If you have any questions, please feel free to open an issue or directly reach us out at <b>[email protected]</b>.
+Bei Fragen: <a href="mailto:[email protected]">Mail an Hidéo</a>
 """
 
 block = gr.Blocks()
@@ -273,14 +260,14 @@ with block:
                     with gr.Column():
                         prompt = gr.Textbox(
                             label="Prompt",
-                            value="a cat, masterpiece, best quality, high quality",
+                            value="mewmewmew, uWu, space kitten, unicorn",
                         )
 
                         scale = gr.Slider(
                             minimum=0, maximum=2.0, step=0.01, value=1.0, label="Scale"
                         )
 
-                with gr.Accordion(open=False, label="Advanced Options"):
+                with gr.Accordion(open=False, label="Details (optional)"):
                     target = gr.Radio(
                         [
                             "Load only style blocks",
@@ -288,7 +275,7 @@ with block:
                             "Load original IP-Adapter",
                         ],
                         value="Load only style blocks",
-                        label="Style mode",
+                        label="Style mode (optional, sb works best!)",
                     )
                     with gr.Column():
                         src_image_pil = gr.Image(
@@ -299,23 +286,23 @@ with block:
                         maximum=1.0,
                         step=0.01,
                         value=0.5,
-                        label="Controlnet conditioning scale",
+                        label="ControlNet Scale (test this!)",
                     )
 
                     n_prompt = gr.Textbox(
-                        label="Neg Prompt",
+                        label="Negative Prompt // n_prompt",
                         value="text, watermark, lowres, low quality, worst quality, deformed, glitch, low contrast, noisy, saturation, blurry",
                     )
 
                     neg_content_prompt = gr.Textbox(
-                        label="Neg Content Prompt", value=""
+                        label="Negative Content Prompt (Ignore this!)", value=""
                     )
                     neg_content_scale = gr.Slider(
                         minimum=0,
                         maximum=1.0,
                         step=0.01,
                         value=0.5,
-                        label="Neg Content Scale",
+                        label="NCS (Ignore this!) // neg_content_scale",
                     )
 
                     guidance_scale = gr.Slider(
@@ -323,27 +310,27 @@ with block:
                         maximum=10.0,
                         step=0.01,
                         value=0.0,
-                        label="guidance scale",
+                        label="Guidance Scale (test this!)",
                     )
                     num_inference_steps = gr.Slider(
                         minimum=2,
                         maximum=50.0,
                         step=1.0,
                         value=2,
-                        label="num inference steps",
+                        label="Inference Steps (optional but test with 2+)",
                     )
                     seed = gr.Slider(
                         minimum=-1,
                         maximum=MAX_SEED,
                         value=-1,
                         step=1,
-                        label="Seed Value",
+                        label="Seed Value (Seed-Proof) // -1 == random",
                     )
 
-                generate_button = gr.Button("Generate Image")
+                generate_button = gr.Button("Simsalabim")
 
             with gr.Column():
-                generated_image = gr.Image(label="Generated Image")
+                generated_image = gr.Image(label="Magix uWu")
 
     inputs = [
         image_pil,