fix app

app.py

@@ -22,17 +22,16 @@ ckpt_dir_1024 = "checkpoints/base_1024_v1"
 os.makedirs(ckpt_dir_1024, exist_ok=True)
 hf_hub_download(repo_id="VideoCrafter/Text2Video-1024", filename="model.ckpt", local_dir=ckpt_dir_1024)
 
-ckpt_path_256 = "checkpoints/base_256_v1/model.pth"
-ckpt_dir_256 = "checkpoints/base_256_v1"
-os.makedirs(ckpt_dir_256, exist_ok=True)
-hf_hub_download(repo_id="MoonQiu/LongerCrafter", filename="model.pth", local_dir=ckpt_dir_256)
+# ckpt_path_256 = "checkpoints/base_256_v1/model.pth"
+# ckpt_dir_256 = "checkpoints/base_256_v1"
+# os.makedirs(ckpt_dir_256, exist_ok=True)
+# hf_hub_download(repo_id="MoonQiu/LongerCrafter", filename="model.pth", local_dir=ckpt_dir_256)
 
 
-def infer(prompt, output_size="256x256"):
+def infer(prompt, output_size, seed):
     num_frames = 32 
     ddim_steps = 50
     unconditional_guidance_scale = 12.0
-    seed = 123
     save_fps = 10
     window_size = 16
     window_stride = 4
@@ -48,19 +47,19 @@ def infer(prompt, output_size="256x256"):
         model_1024 = load_model_checkpoint(model_1024, ckpt_path_1024)
         model_1024.eval()
         model = model_1024
-        fps = 24
-    elif output_size == "256x256":
-        width = 256 
-        height = 256
-        config_256 = "configs/inference_t2v_tconv256_v1.0_freenoise.yaml"
-        config_256 = OmegaConf.load(config_256)
-        model_config_256 = config_256.pop("model", OmegaConf.create())
-        model_256 = instantiate_from_config(model_config_256)
-        model_256 = model_256.cuda()
-        model_256 = load_model_checkpoint(model_256, ckpt_path_256)
-        model_256.eval()
-        model = model_256
-        fps = 8
+        fps = 28
+    # elif output_size == "256x256":
+    #     width = 256 
+    #     height = 256
+    #     config_256 = "configs/inference_t2v_tconv256_v1.0_freenoise.yaml"
+    #     config_256 = OmegaConf.load(config_256)
+    #     model_config_256 = config_256.pop("model", OmegaConf.create())
+    #     model_256 = instantiate_from_config(model_config_256)
+    #     model_256 = model_256.cuda()
+    #     model_256 = load_model_checkpoint(model_256, ckpt_path_256)
+    #     model_256.eval()
+    #     model = model_256
+    #     fps = 8
 
     if seed is None:
         seed = int.from_bytes(os.urandom(2), "big")
@@ -253,14 +252,26 @@ with gr.Blocks(css=css) as demo:
         )
 
         prompt_in = gr.Textbox(label="Prompt", placeholder="A chihuahua in astronaut suit floating in space, cinematic lighting, glow effect")
-        output_size = gr.Dropdown(["576x1024", "256x256"], value="576x1024", label="Output Size", info="576x1024 is watermark-free")
+
+        with gr.Row():
+            with gr.Accordion('FreeNoise Parameters (feel free to adjust these parameters based on your prompt): ', open=False):
+                with gr.Row():
+                    output_size = gr.Dropdown(["576x1024"], value="576x1024", label="Output Size")
+                    # output_size = gr.Dropdown(["576x1024", "256x256"], value="576x1024", label="Output Size", info="576x1024 is watermark-free")
+                with gr.Row():
+                    seed = gr.Slider(label='seed',
+                             minimum=0,
+                             maximum=1000,
+                             step=1,
+                             value=123)
+
         submit_btn = gr.Button("Generate")
         video_result = gr.Video(label="Video Output")
 
-        gr.Examples(examples=examples, inputs=[prompt_in, output_size])
+        gr.Examples(examples=examples, inputs=[prompt_in, output_size, seed])
 
     submit_btn.click(fn=infer,
-            inputs=[prompt_in, output_size],
+            inputs=[prompt_in, output_size, seed],
             outputs=[video_result],
             api_name="zrscp")