Activate Half & VAE

gradio_demo.py

@@ -29,8 +29,8 @@ parser.add_argument("--port", type=int, default='6688')
 parser.add_argument("--no_llava", action='store_true', default=True)#False
 parser.add_argument("--use_image_slider", action='store_true', default=False)
 parser.add_argument("--log_history", action='store_true', default=False)
-parser.add_argument("--loading_half_params", action='store_true', default=False)#False
-parser.add_argument("--use_tile_vae", action='store_true', default=False)#False
+parser.add_argument("--loading_half_params", action='store_true', default=True)#False
+parser.add_argument("--use_tile_vae", action='store_true', default=True)#False
 parser.add_argument("--encoder_tile_size", type=int, default=512)
 parser.add_argument("--decoder_tile_size", type=int, default=64)
 parser.add_argument("--load_8bit_llava", action='store_true', default=False)
@@ -231,9 +231,9 @@ if torch.cuda.device_count() == 0:
     """
 else:
     title_md = """
-    <h1><center>SUPIR: Practicing Model Scaling for Photo-Realistic Image Restoration</center></h1>
+    <h1><center>SUPIR Image Upscaler</center></h1>
     
-    ⚠️SUPIR is still a research project under tested and is not yet a stable commercial product.
+    SUPIR is a practicing model scaling for photo-realistic image restoration. It is still a research project under tested and is not yet a stable commercial product.
     
     <a href="https://arxiv.org/abs/2401.13627">Paper</a> &emsp; <a href="http://supir.xpixel.group/">Project Page</a> &emsp; <a href="https://github.com/Fanghua-Yu/SUPIR/blob/master/assets/DemoGuide.png">How to play</a> &emsp; <a href="https://huggingface.co/blog/MonsterMMORPG/supir-sota-image-upscale-better-than-magnific-ai">Local Install Guide</a>
     <p style="background-color: blue;">For now, only the restoring is working (the most important one). The pre-denoising and LLaVa description are failing. LLaVa is disabled.</p>
@@ -338,9 +338,9 @@ with gr.Blocks(title='SUPIR') as interface:
                     diffusion_button = gr.Button(value="🚀 Restore", variant = "primary")
             with gr.Row():
                 with gr.Column():
-                    param_setting = gr.Radio(["Quality", "Fidelity"], interactive=True, label="Param Setting", value="Quality")
+                    param_setting = gr.Radio(["Quality", "Fidelity"], interactive=True, label="Parameter setting", value="Quality")
                 with gr.Column():
-                    restart_button = gr.Button(value="Reset Param", scale=2, variant="stop")
+                    restart_button = gr.Button(value="Apply parameter setting", scale=2)
 
             with gr.Accordion("Feedback", open=True):
                 fb_score = gr.Slider(label="Feedback Score", minimum=1, maximum=5, value=3, step=1,