test

app.py

@@ -89,21 +89,22 @@ def txt2img_generate(prompt, steps=25, seed=42, guidance_scale=7.5):
         print("Compute node: ", json.loads(resp.text)["ip"])
     except:
         print('No inference result. Please check server connection')
-        return [None, gr.update(visible=True), gr.update(visible=False)]
+        return None
+        # return [None, gr.update(visible=True), gr.update(visible=False)]
 
     img_byte = base64.b64decode(img_str)
     img_io = BytesIO(img_byte)  # convert image to file-like object
     img = Image.open(img_io)   # img is now PIL Image object
     print("elapsed time: ", time.time() - start_time)
 
-    if queue_size.isdigit():
-        if int(queue_size) > 4:
-            return [img, gr.update(visible=False), gr.update(visible=True)]
-        elif int(queue_size) <= 4:
-            return [img, gr.update(visible=True), gr.update(visible=False)]
-    else:
-        return [img, gr.update(visible=True), gr.update(visible=False)]   
-
+    # if queue_size.isdigit():
+    #     if int(queue_size) > 4:
+    #         return [img, gr.update(visible=False), gr.update(visible=True)]
+    #     elif int(queue_size) <= 4:
+    #         return [img, gr.update(visible=True), gr.update(visible=False)]
+    # else:
+    #     return [img, gr.update(visible=True), gr.update(visible=False)]   
+    return img
 
 md = """
 This demo shows the accelerated inference performance of a Stable Diffusion model on **Intel Xeon Gold 64xx (4th Gen Intel Xeon Scalable Processors codenamed Sapphire Rapids)**. Try it and generate photorealistic images from text! Please note that the demo is in **preview** under limited HW resources. We are committed to continue improving the demo and happy to hear your feedbacks. Thanks for your trying！
@@ -167,9 +168,11 @@ with gr.Blocks(css=css) as demo:
             with gr.Column():
                 result_image_2 = gr.Image()
 
-    txt2img_button.click(fn=txt2img_generate, inputs=[prompt, inference_steps, seed, guidance_scale], outputs=[result_image, textBoxGreen, textBoxOrange])
+    txt2img_button.click(fn=txt2img_generate, inputs=[prompt, inference_steps, seed, guidance_scale], outputs=[result_image])
+    # txt2img_button.click(fn=txt2img_generate, inputs=[prompt, inference_steps, seed, guidance_scale], outputs=[result_image, textBoxGreen, textBoxOrange])
 
-    img2img_button.click(fn=img2img_generate, inputs=[source_img, prompt_2, inference_steps_2, strength, seed_2, guidance_scale_2], outputs=[result_image_2, textBoxGreen, textBoxOrange])
+    img2img_button.click(fn=img2img_generate, inputs=[source_img, prompt_2, inference_steps_2, strength, seed_2, guidance_scale_2], outputs=[result_image_2])
+    # img2img_button.click(fn=img2img_generate, inputs=[source_img, prompt_2, inference_steps_2, strength, seed_2, guidance_scale_2], outputs=[result_image_2, textBoxGreen, textBoxOrange])
 
     gr.Markdown("**Additional Test Configuration Details:**", elem_id='mdStyle')
     gr.Markdown(details, elem_id='mdStyle')