nodes/image_gesture_nodes.py

@@ -38,7 +38,7 @@ class JMUtils:
         self.cos_secret_key = yaml_config["cos_secret_key"]
         self.cos_bucket_name = yaml_config["cos_sucai_bucket_name"]
 
-    def submit_task(self, prompt: str, img_url: str, duration: str = "10"):
+    def submit_task(self, prompt: str, img_url: str, duration: str = "5"):
         try:
             headers = {
                 "Content-Type": "application/json",
@@ -46,11 +46,11 @@ class JMUtils:
             }
 
             json_data = {
-                "model": "doubao-seedance-1-0-pro-250528",
+                "model": "doubao-seedance-1-0-lite-i2v-250428",
                 "content": [
                     {
                         "type": "text",
-                        "text": f"{prompt}  --resolution 1080p  --dur {duration} --camerafixed false",
+                        "text": f"{prompt}  --resolution 720p  --dur {duration} --camerafixed false",
                     },
                     {
                         "type": "image_url",
@@ -291,7 +291,7 @@ class JMGestureCorrect:
     CATEGORY = "不忘科技-自定义节点🚩/图片/姿态"
 
     def gen(self, image: torch.Tensor):
-        wait_time = 240
+        wait_time = 120
         interval = 2
         client = JMUtils()
         image_io = client.tensor_to_io(image)
@@ -331,8 +331,7 @@ class JMCustom:
                 "prompt": ("STRING", {
                     "default": "Stand straight ahead, facing the camera, showing your full body, maintaining a proper posture, keeping the camera still, and ensuring that your head and feet are all within the frame",
                     "multiline": True}),
-                "duration": ("INT", {"default": 5, "min": 2, "max": 10}),
+                "duration": ("INT", {"default": 5, "min": 2, "max": 30}),
-                "wait_time": ("INT", {"default": 180, "min": 60, "max": 600}),
             }
         }
 
@@ -341,7 +340,8 @@ class JMCustom:
     FUNCTION = "gen"
     CATEGORY = "不忘科技-自定义节点🚩/视频/即梦"
 
-    def gen(self, image: torch.Tensor, prompt: str, duration: int, wait_time: int):
+    def gen(self, image: torch.Tensor, prompt: str, duration: int):
+        wait_time = 120
         interval = 2
         client = JMUtils()
         image_io = client.tensor_to_io(image)