python

.gitignore

@@ -1,3 +1,4 @@
+# javascript
 node_modules
 *.log*
 .nuxt
@@ -6,3 +7,6 @@ node_modules
 .output
 .env
 dist
+
+# python
+venv

requirements.txt

@@ -0,0 +1,5 @@
+certifi==2022.12.7
+charset-normalizer==3.0.1
+idna==3.4
+requests==2.28.2
+urllib3==1.26.14

server.py

@@ -210,6 +210,40 @@ def put_watermark(img, wm_encoder=None):
         img = Image.fromarray(img[:, :, ::-1])
     return img
 
+import time
+import requests
+
+# 获取model, 如果和之前的model不一样，重新加载
+def get_model(model_name):
+    global model
+    global config
+    global device
+    if model_name != model_name:
+        config = OmegaConf.load(f"{opt.config}")
+        device = torch.device("cuda") if opt.device == "cuda" else torch.device("cpu")
+        model = load_model_from_config(config, f"{opt.ckpt}", device)
+    return model
+
+# 使用指定的模型和配置文件进行推理一组参数
+def drawing(model_name):
+    model = get_model(model_name)
+    if opt.plms:
+        sampler = PLMSSampler(model, device=device)
+    elif opt.dpm:
+        sampler = DPMSolverSampler(model, device=device)
+    else:
+        sampler = DDIMSampler(model, device=device)
+
+
+def main_dev(opt):
+    while True:
+        time.sleep(1) # 延时1s执行, 避免cpu占用过高
+        # 从局域网中获取一组参数
+        request = requests.get("http://localhost:3000/api/drawing")
+        if request.status_code == 200:
+            data = request.json()
+            print("data: ", data)
+        #drawing("model_name")
 
 def main(opt):
     seed_everything(opt.seed)
@@ -385,4 +419,4 @@ def main(opt):
 
 if __name__ == "__main__":
     opt = parse_args()
-    main(opt)
+    main_dev(opt)