Hide LlaVa

gradio_demo.py

@@ -78,7 +78,7 @@ def check(input_image):
 def reset_feedback():
     return 3, ''
 
-@spaces.GPU(duration=180)
+@spaces.GPU(duration=240)
 def stage1_process(input_image, gamma_correction):
     print('Start stage1_process')
     if torch.cuda.device_count() == 0:
@@ -100,7 +100,7 @@ def stage1_process(input_image, gamma_correction):
     print('End stage1_process')
     return LQ
 
-@spaces.GPU(duration=180)
+@spaces.GPU(duration=240)
 def llave_process(input_image, temperature, top_p, qs=None):
     print('Start llave_process')
     if torch.cuda.device_count() == 0:
@@ -116,7 +116,7 @@ def llave_process(input_image, temperature, top_p, qs=None):
     print('End llave_process')
     return captions[0]
 
-@spaces.GPU(duration=180)
+@spaces.GPU(duration=240)
 def stage2_process(input_image, prompt, a_prompt, n_prompt, num_samples, upscale, edm_steps, s_stage1, s_stage2,
                    s_cfg, seed, s_churn, s_noise, color_fix_type, diff_dtype, ae_dtype, gamma_correction,
                    linear_CFG, linear_s_stage2, spt_linear_CFG, spt_linear_s_stage2, model_select):
@@ -240,10 +240,9 @@ else:
     title_md = """
     <h1><center>SUPIR Image Upscaler</center></h1>
     
-    <p>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.
+    <p>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. LLaVa is not available in this demo. If you want to auto-generate the description of your image, use another <a href="https://huggingface.co/spaces/MaziyarPanahi/llava-llama-3-8b">LLaVa space</a>.
     
     <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>
-    <p style="background-color: blue;">LLaVa is disabled.</p>
     """
 
 
@@ -276,13 +275,13 @@ with gr.Blocks(title="SUPIR") as interface:
             with gr.Accordion("Pre-denoising options", open=False):
                 gamma_correction = gr.Slider(label="Gamma Correction", minimum=0.1, maximum=2.0, value=1.0, step=0.1)
 
-            with gr.Accordion("LLaVA options", open=False):
+            with gr.Accordion("LLaVA options", open=False, visible=False):
                 temperature = gr.Slider(label="Temperature", info = "lower=Always similar, higher=More creative", minimum=0., maximum=1.0, value=0.2, step=0.1)
                 top_p = gr.Slider(label="Top P", info = "Percent of tokens shortlisted", minimum=0., maximum=1.0, value=0.7, step=0.1)
                 qs = gr.Textbox(label="Question", info="Ask LLaVa what description you want", value="Describe the image and its style in a very detailed manner. The image is a realistic photography, not an art painting.", lines=3)
 
             with gr.Accordion("Restoring options", open=False):
-                num_samples = gr.Slider(label="Num Samples", info="Number of generated results; I discourage to increase because the process is limited to 3 min", minimum=1, maximum=4 if not args.use_image_slider else 1
+                num_samples = gr.Slider(label="Num Samples", info="Number of generated results; I discourage to increase because the process is limited to 4 min", minimum=1, maximum=4 if not args.use_image_slider else 1
                                         , value=1, step=1)
                 upscale = gr.Slider(label="Upscale factor", info="Resolution x1, x2, x3, x4, x5, x6, x7 or x8", minimum=1, maximum=8, value=1, step=1)
                 edm_steps = gr.Slider(label="Steps", info="lower=faster, higher=more details", minimum=1, maximum=200, value=default_setting.edm_steps if torch.cuda.device_count() > 0 else 1, step=1)
@@ -340,7 +339,7 @@ with gr.Blocks(title="SUPIR") as interface:
             with gr.Row():
                 with gr.Column():
                     denoise_button = gr.Button(value="Pre-denoise")
-                with gr.Column():
+                with gr.Column(visible=False):
                     llave_button = gr.Button(value="Generate description by LlaVa (disabled)")
                 with gr.Column():
                     diffusion_button = gr.Button(value="🚀 Restore", variant = "primary")