Resolution

gradio_demo.py

@@ -78,7 +78,7 @@ def check(input_image):
 def reset_feedback():
     return 3, ''
 
-@spaces.GPU(duration=240)
+@spaces.GPU(duration=3600)
 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, gr.update(visible = True)
 
-@spaces.GPU(duration=240)
+@spaces.GPU(duration=3600)
 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=240)
+@spaces.GPU(duration=3600)
 def stage2_process(
     noisy_image,
     denoise_image,
@@ -145,6 +145,7 @@ def stage2_process(
 ):
     start = time.time()
     print('Start stage2_process')
+    print(a_prompt)
     if torch.cuda.device_count() == 0:
         gr.Warning('Set this space to GPU config to make it work.')
         return None, None, None
@@ -213,7 +214,12 @@ def stage2_process(
     secondes = secondes - (minutes * 60)
     hours = minutes // 60
     minutes = minutes - (hours * 60)
-    information = ("Restart the process to get another result. " if randomize_seed else "") + "The image(s) has(ve) been generated in " + ((str(hours) + " h, ") if hours != 0 else "") + ((str(minutes) + " min, ") if hours != 0 or minutes != 0 else "") + str(secondes) + " sec."
+    information = ("Start the process again if you want a different result. " if randomize_seed else "") +
+    "The new image resolution is " + str(result_width) + " pixels large and " + str(result_height) + " pixels high, so a resolution of " + f'{result_width * result_height:,}' + " pixels. "
+    "The image(s) has(ve) been generated in " +
+    ((str(hours) + " h, ") if hours != 0 else "") +
+    ((str(minutes) + " min, ") if hours != 0 or minutes != 0 else "") +
+    str(secondes) + " sec."
 
     return [noisy_image] + results, [noisy_image] + results, gr.update(value = information, visible = True), event_id
 
@@ -278,6 +284,10 @@ 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.
@@ -309,7 +319,8 @@ with gr.Blocks(title="SUPIR") as interface:
                                 'Grading, ultra HD, extreme meticulous detailing, skin pore detailing, '
                                 'hyper sharpness, perfect without deformations.',
                           lines=3)
-    a_prompt_hint = gr.HTML("You can use a <a href='"'https://huggingface.co/spaces/MaziyarPanahi/llava-llama-3-8b'"'>LlaVa space</a> to auto-generate the description of your image.")
+    with gr.Group():
+        a_prompt_hint = gr.HTML("You can use a <a href='"'https://huggingface.co/spaces/MaziyarPanahi/llava-llama-3-8b'"'>LlaVa space</a> to auto-generate the description of your image.")
 
     with gr.Accordion("Pre-denoising (optional)", open=False):
         gamma_correction = gr.Slider(label="Gamma Correction", minimum=0.1, maximum=2.0, value=1.0, step=0.1)