Rollback

gradio_demo.py

@@ -79,7 +79,7 @@ def check(input_image):
 def reset_feedback():
     return 3, ''
 
-@spaces.GPU(duration=600)
+@spaces.GPU(duration=540)
 def stage1_process(input_image, gamma_correction):
     print('stage1_process ==>>')
     if torch.cuda.device_count() == 0:
@@ -101,7 +101,7 @@ def stage1_process(input_image, gamma_correction):
     print('<<== stage1_process')
     return LQ, gr.update(visible = True)
 
-@spaces.GPU(duration=600)
+@spaces.GPU(duration=540)
 def llave_process(input_image, temperature, top_p, qs=None):
     print('llave_process ==>>')
     if torch.cuda.device_count() == 0:
@@ -117,6 +117,7 @@ def llave_process(input_image, temperature, top_p, qs=None):
     print('<<== llave_process')
     return captions[0]
 
+@spaces.GPU(duration=540)
 def stage2_process(
     noisy_image,
     denoise_image,
@@ -160,6 +161,7 @@ def stage2_process(
     if 1 < downscale:
         input_height, input_width, input_channel = np.array(input_image).shape
         input_image = input_image.resize((input_width // downscale, input_height // downscale), Image.LANCZOS)
+    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,
                   'n_prompt': n_prompt, 'num_samples': num_samples, 'upscale': upscale, 'edm_steps': edm_steps,
@@ -180,47 +182,6 @@ def stage2_process(
     input_image = upscale_image(input_image, upscale, unit_resolution=32,
                                 min_size=min_size)
 
-    result_slider, result_gallery, restore_information, event_id = restore(
-        model,
-    edm_steps,
-    s_stage1,
-    s_churn,
-    s_noise,
-    s_cfg,
-    s_stage2,
-    seed,
-    num_samples,
-    a_prompt,
-    n_prompt,
-    color_fix_type,
-    linear_CFG,
-    linear_s_stage2,
-    spt_linear_CFG,
-    spt_linear_s_stage2
-    )
-
-    return result_slider, result_gallery, restore_information, event_id
-
-@spaces.GPU(duration=600)
-def restore(
-    model,
-    edm_steps,
-    s_stage1,
-    s_churn,
-    s_noise,
-    s_cfg,
-    s_stage2,
-    seed,
-    num_samples,
-    a_prompt,
-    n_prompt,
-    color_fix_type,
-    linear_CFG,
-    linear_s_stage2,
-    spt_linear_CFG,
-    spt_linear_s_stage2
-):
-    torch.cuda.set_device(SUPIR_device)
     LQ = np.array(input_image) / 255.0
     LQ = np.power(LQ, gamma_correction)
     LQ *= 255.0
@@ -328,7 +289,7 @@ def submit_feedback(event_id, fb_score, fb_text):
 
 title_html = """
     <h1><center>SUPIR</center></h1>
-    <center><big>Upscale your images up to x8 freely, without account, without watermark and download it</big></center>
+    <big><center>Upscale your images up to x8 freely, without account, without watermark and download it</center></big>
     <center><big><big>🤸<big><big><big><big><big><big>🤸</big></big></big></big></big></big></big></big></center>
     
     <p>This is an online demo of SUPIR, a practicing model scaling for photo-realistic image restoration.
@@ -336,7 +297,7 @@ title_html = """
     LlaVa is not integrated in this demo. The content added by SUPIR is imagination, not real-world information.
     The aim of SUPIR is the beauty and the illustration.
     Most of the processes only last few minutes.
-    This demo can handle huge images but the process will be aborted if it lasts more than 10 min.
+    This demo can handle huge images but the process will be aborted if it lasts more than 9 min.
     
     <p><center><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></center></p>
     """
@@ -344,15 +305,10 @@ title_html = """
 
 claim_md = """
 ## **Piracy**
-
 The images are not stored but the logs are saved during a month.
-
 ## **Terms of use**
-
 By using this service, users are required to agree to the following terms: The service is a research preview intended for non-commercial use only. It only provides limited safety measures and may generate offensive content. It must not be used for any illegal, harmful, violent, racist, or sexual purposes. The service may collect user dialogue data for future research. Please submit a feedback to us if you get any inappropriate answer! We will collect those to keep improving our models. For an optimal experience, please use desktop computers for this demo, as mobile devices may compromise its quality.
-
 ## **License**
-
 The service is a research preview intended for non-commercial use only, subject to the model [License](https://github.com/Fanghua-Yu/SUPIR) of SUPIR.
 """
 
@@ -550,4 +506,4 @@ with gr.Blocks(title="SUPIR") as interface:
         fb_text
     ])
         
-    interface.queue(10).launch()
+    interface.queue(10).launch()