Update app.py

app.py

@@ -37,7 +37,7 @@ torch.backends.cuda.preferred_linalg_library="cusolver"
 
 torch.set_float32_matmul_precision("highest")
 
-MAX_SEED = np.iinfo(np.int64).max
+MAX_SEED = np.iinfo(np.int32).max
 
 # Load Hugging Face token if needed
 hf_token = os.getenv("HF_TOKEN")
@@ -124,7 +124,7 @@ def center_crop_and_resize(frame, target_height, target_width):
     frame_resized = cv2.resize(frame_cropped, (target_width, target_height))
     return frame_resized
 
-def load_image_to_tensor_with_resize(image_path, target_height=512, target_width=768):
+def load_image_to_tensor_with_resize(image_path, target_height=768, target_width=768):
     image = Image.open(image_path).convert("RGB")
     image_np = np.array(image)
     frame_resized = center_crop_and_resize(image_np, target_height, target_width)
@@ -246,7 +246,7 @@ def generate_video_from_text(
     frame_rate=25,
     seed=random.randint(0, MAX_SEED),
     num_inference_steps=30,
-    guidance_scale=4.2,
+    guidance_scale=3.2,
     height=768,
     width=768,
     num_frames=60,
@@ -326,7 +326,7 @@ def generate_video_from_image(
     frame_rate=20,
     seed=random.randint(0, MAX_SEED),
     num_inference_steps=35,
-    guidance_scale=4.2,
+    guidance_scale=3.2,
     height=768,
     width=768,
     num_frames=60,
@@ -412,7 +412,7 @@ def create_advanced_options():
     with gr.Accordion("Step 4: Advanced Options (Optional)", open=False):
         seed = gr.Slider(label="4.1 Seed", minimum=0, maximum=1000000, step=1, value=646373)
         inference_steps = gr.Slider(label="4.2 Inference Steps", minimum=5, maximum=150, step=5, value=40)
-        guidance_scale = gr.Slider(label="4.3 Guidance Scale", minimum=1.0, maximum=10.0, step=0.1, value=4.2)
+        guidance_scale = gr.Slider(label="4.3 Guidance Scale", minimum=1.0, maximum=10.0, step=0.1, value=3.2)
         
         gpu_duration = gr.Dropdown(
             label="GPU Duration",