update

main.py

@@ -25,44 +25,38 @@ def root():
     
 @app.post("/img2img")
 async def predict(prompt=Body(...),imgbase64data=Body(...)):
+    pipeline = get_pipeline()
     MAX_QUEUE_SIZE = 4
     start = time.time()
-    pipeline = get_pipeline()
-    
-    url = "https://img2.baidu.com/it/u=1845675188,2679793929&fm=253&fmt=auto&app=138&f=JPEG?w=667&h=500"
-    prompt = "a nice Comfortable and clean. According to Baidu Education Information, the adjectives for a room include: comfortable, clean, beautiful, spacious, warm, quiet, luxurious, pleasant, exquisite, and warm ,colorful, light room width sofa,8k"
-    
-    init_image = load_image(url).convert("RGB")
-    # image1 = replace_background(init_image.resize((256, 256)))
-    w, h = init_image.size
-    newW = 512
+    print("参数",imgbase64data,prompt)
+    image_data = base64.b64decode(imgbase64data)
+    image1 = Image.open(io.BytesIO(image_data))
+    w, h = image1.size
+    newW = 256
     newH = int(h * newW / w)
-    
-    img = init_image.resize((newW, newH))  
+    img = image1.resize((newW, newH))  
     end1 = time.time()
+    now = datetime.now()
+    print(now)
+    print("图像:", img.size)
     print("加载管道:", end1 - start)
     result = pipeline(
         prompt=prompt,
-        image=img,
+        image=image1,
         strength=0.6,
         seed=10,
-        width=512,
-        height=512,
+        width=256,
+        height=256,
         guidance_scale=1,
         num_inference_steps=4,
     )
     output_image = result.images[0]
     end2 = time.time()
     print("测试",output_image)
-    print("s生成完成:", end2 - end1)
-    end2 = time.time()
-    print("测试",output_image)
     print("s生成完成:", end2 - end1)    
     # 将图片对象转换为bytes
-    end3 = time.time()
     output_image_base64 = base64.b64encode(output_image.tobytes()).decode()
     print("完成的图片:", output_image_base64) 
-    print("图像转换时间:", end3 - end2)
     return output_image_base64