elapsed_time

app.py

@@ -1,6 +1,8 @@
 import gradio as gr
 import modin.pandas as pd
 import torch
+import time
+
 import numpy as np
 from PIL import Image
 from diffusers import AutoPipelineForImage2Image
@@ -17,12 +19,16 @@ def resize(value,img):
     return img
 
 def infer(source_img, prompt, steps, seed, Strength):
+    start_time = time.time()
     generator = torch.Generator(device).manual_seed(seed)  
     if int(steps * Strength) < 1:
         steps = math.ceil(1 / max(0.10, Strength))
     source_image = resize(512, source_img)
     source_image.save('source.png')
     image = pipe(prompt, image=source_image, strength=Strength, guidance_scale=0.0, num_inference_steps=steps).images[0]
+    end_time = time.time()
+    elapsed_time = end_time - start_time
+    print("生成时间",elapsed_time)
     return image
 
 gr.Interface(fn=infer, inputs=[