Seed

gradio_demo.py

@@ -65,10 +65,18 @@ if torch.cuda.device_count() > 0:
     else:
         llava_agent = None
 
+def update_seed(is_randomize_seed, seed):
+    if is_randomize_seed:
+        return random.randint(0, max_64_bit_int)
+    return seed
+
 def check(input_image):
     if input_image is None:
         raise gr.Error("Please provide an image to restore.")
 
+def reset_feedback():
+    return 3, ''
+
 @spaces.GPU(duration=180)
 def stage1_process(input_image, gamma_correction):
     print('Start stage1_process')
@@ -114,7 +122,7 @@ def stage2_process(input_image, prompt, a_prompt, n_prompt, num_samples, upscale
     print('Start stage2_process')
     if torch.cuda.device_count() == 0:
         gr.Warning('Set this space to GPU config to make it work.')
-        return None, None, None, None
+        return None, None
     torch.cuda.set_device(SUPIR_device)
     event_id = str(time.time_ns())
     event_dict = {'event_id': event_id, 'localtime': time.ctime(), 'prompt': prompt, 'a_prompt': a_prompt,
@@ -169,7 +177,7 @@ def stage2_process(input_image, prompt, a_prompt, n_prompt, num_samples, upscale
         for i, result in enumerate(results):
             Image.fromarray(result).save(f'./history/{event_id[:5]}/{event_id[5:]}/HQ_{i}.png')
     print('End stage2_process')
-    return [input_image] + results, event_id, 3, ''
+    return [input_image] + results, event_id
 
 def load_and_reset(param_setting):
     print('Start load_and_reset')
@@ -231,10 +239,10 @@ else:
     title_md = """
     <h1><center>SUPIR Image Upscaler</center></h1>
     
-    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.
     
-    <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>
+    <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>
     """
 
 
@@ -249,7 +257,7 @@ The service is a research preview intended for non-commercial use only, subject
 """
 
 # Gradio interface
-with gr.Blocks(title='SUPIR') as interface:
+with gr.Blocks(title="SUPIR") as interface:
     with gr.Row():
         gr.HTML(title_md)
 
@@ -275,13 +283,14 @@ with gr.Blocks(title='SUPIR') as interface:
             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
                                         , value=1, step=1)
-                upscale = gr.Slider(label="Upscale", info="The resolution increase factor", minimum=1, maximum=8, 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)
                 s_cfg = gr.Slider(label="Text Guidance Scale", info="lower=follow the image, higher=follow the prompt", minimum=1.0, maximum=15.0,
                                   value=default_setting.s_cfg_Quality if torch.cuda.device_count() > 0 else 1.0, step=0.1)
                 s_stage2 = gr.Slider(label="Restoring Guidance Strength", minimum=0., maximum=1., value=1., step=0.05)
                 s_stage1 = gr.Slider(label="Pre-denoising Guidance Strength", minimum=-1.0, maximum=6.0, value=-1.0, step=1.0)
-                seed = gr.Slider(label="Seed", info="-1=Different each time, other=Reproducible", minimum=-1, maximum=2147483647, step=1, randomize=True)
+                randomize_seed = gr.Checkbox(label = "\U0001F3B2 Randomize seed", value = True, info = "If checked, result is always different")
+                seed = gr.Slider(label="Seed", minimum=0, maximum=2147483647, step=1, randomize=True)
                 s_churn = gr.Slider(label="S-Churn", minimum=0, maximum=40, value=5, step=1)
                 s_noise = gr.Slider(label="S-Noise", minimum=1.0, maximum=1.1, value=1.003, step=0.001)
                 a_prompt = gr.Textbox(label="Default Positive Prompt",
@@ -329,9 +338,9 @@ with gr.Blocks(title='SUPIR') as interface:
                 result_gallery = ImageSlider(label='Output', show_label=False, elem_id="gallery1")
             with gr.Row():
                 with gr.Column():
-                    denoise_button = gr.Button(value="Pre-denoise (KO)")
+                    denoise_button = gr.Button(value="Pre-denoise")
                 with gr.Column():
-                    llave_button = gr.Button(value="Generate description by LlaVa (KO)")
+                    llave_button = gr.Button(value="Generate description by LlaVa (disabled)")
                 with gr.Column():
                     diffusion_button = gr.Button(value="🚀 Restore", variant = "primary")
             with gr.Row():
@@ -369,9 +378,17 @@ with gr.Blocks(title='SUPIR') as interface:
         prompt
     ])
 
-    diffusion_button.click(fn = check, inputs = [
+    diffusion_button.click(fn = update_seed, inputs = [
+        randomize_seed,
+        seed
+    ], outputs = [
+        seed
+    ], queue = False, show_progress = False).then(fn = check, inputs = [
         input_image
-    ], outputs = [], queue = False, show_progress = False).success(fn=stage2_process, inputs = [
+    ], outputs = [], queue = False, show_progress = False).then(fn = reset_feedback, inputs = [], outputs = [
+        fb_score,
+        fb_text
+    ], queue = False, show_progress = False).success(fn=stage2_process, inputs = [
         input_image,
         prompt,
         a_prompt,
@@ -396,9 +413,7 @@ with gr.Blocks(title='SUPIR') as interface:
         model_select
     ], outputs = [
         result_gallery,
-        event_id,
-        fb_score,
-        fb_text
+        event_id
     ])
 
     restart_button.click(fn = load_and_reset, inputs = [