add seed for CCD

CCD/src/main.py

@@ -306,8 +306,17 @@ def train():
             torch.save(ddpm.state_dict(), save_dir + f"model_{ep}.pth")
             print('saved model at ' + save_dir + f"model_{ep}.pth")
 
+def set_seed(seed: int):
+    random.seed(seed)
+    np.random.seed(seed)
+    torch.manual_seed(seed)
+    if torch.cuda.is_available():
+        torch.cuda.manual_seed_all(seed)
 
-def gen(text: str):
+
+def gen(text: str, seed: int):
+    set_seed(seed)
+    
     script_dir = os.path.dirname(os.path.abspath(__file__))
 
     mean_std_path = os.path.join(script_dir, "..", "checkpoints", "Mean_Std.npy")
@@ -373,8 +382,8 @@ def gen(text: str):
             #         f.write(txt+"\n")
 
 
-def generate_CCD_sample(text: str):
-    return gen(text)
+def generate_CCD_sample(text: str, seed : int):
+    return gen(text, seed)
 
 if __name__ == "__main__":
     import sys

app.py

@@ -111,7 +111,7 @@ def generate_ccd(
     character_position: list,
 ) -> Dict[str, Any]:
     
-    results = generate_CCD_sample(prompt)
+    results = generate_CCD_sample(prompt, seed)
 
     rr.init(f"{3}")
     rr.save(".tmp_gr.rrd")
@@ -198,7 +198,7 @@ def launch_app(gen_fn_et: Callable, gen_fn_ccd: Callable):
                         show_label=True,
                         label="Character Position (3D vector)",
                         value="[0.0, 0.0, 0.0]",
-                        interactive=True,  # Ensure this is set to True
+                        interactive=True, 
                         
                     )
                     text = gr.Textbox(
@@ -206,13 +206,13 @@ def launch_app(gen_fn_et: Callable, gen_fn_ccd: Callable):
                         show_label=True,
                         label="Text prompt",
                         value=DEFAULT_TEXT[0],
-                        interactive=True,  # Ensure this is set to True
+                        interactive=True, 
 
                     )
                     seed = gr.Number(value=33, label="Seed")
                     guidance = gr.Slider(0, 10, value=1.4, label="Guidance", step=0.1)
 
-                    # Add a dropdown menu for selecting the generation model
+
                     model_selector = gr.Dropdown(
                         choices=list(model_options.keys()),
                         value=list(model_options.keys())[0],