Update app.py

app.py

@@ -10,7 +10,6 @@ import numpy as np
 from PIL import Image
 import random
 import gc
-
 from torchao.quantization import quantize_
 from torchao.quantization import Float8DynamicActivationFloat8WeightConfig, Int8WeightOnlyConfig
 import aoti
@@ -25,13 +24,11 @@ MAX_DIM = 832
 MIN_DIM = 480
 SQUARE_DIM = 640
 MULTIPLE_OF = 16
-
 MAX_SEED = np.iinfo(np.int32).max
 
 FIXED_FPS = 16
 MIN_FRAMES_MODEL = 8
 MAX_FRAMES_MODEL = 7720
-
 MIN_DURATION = round(MIN_FRAMES_MODEL / FIXED_FPS, 1)
 MAX_DURATION = round(MAX_FRAMES_MODEL / FIXED_FPS, 1)
 
@@ -95,6 +92,7 @@ aoti.aoti_blocks_load(pipe.transformer_2, 'zerogpu-aoti/Wan2', variant='fp8da')
 # DEFAULT PROMPTS
 # =========================================================
 default_prompt_i2v = "Make this image come alive with dynamic, cinematic human motion. Create smooth, natural, lifelike animation with fluid transitions, expressive body movement, realistic physics, and elegant camera flow. Deliver a polished, high-quality motion style that feels immersive, artistic, and visually captivating."
+
 default_negative_prompt = (
     "low quality, worst quality, motion artifacts, unstable motion, jitter, frame jitter, wobbling limbs, motion distortion, inconsistent movement, robotic movement, animation-like motion, awkward transitions, incorrect body mechanics, unnatural posing, off-balance poses, broken motion paths, frozen frames, duplicated frames, frame skipping, warped motion, stretching artifacts bad anatomy, incorrect proportions, deformed body, twisted torso, broken joints, dislocated limbs, distorted neck, unnatural spine curvature, malformed hands, extra fingers, missing fingers, fused fingers, distorted legs, extra limbs, collapsed feet, floating feet, foot sliding, foot jitter, backward walking, unnatural gait blurry details, long exposure blur, ghosting, shadow trails, smearing, washed-out colors, overexposure, underexposure, excessive contrast, blown highlights, poorly rendered clothing, fabric glitches, texture warping, clothing merging with body, incorrect cloth physics ugly background, cluttered scene, crowded background, random objects, unwanted text, subtitles, logos, graffiti, grain, noise, static artifacts, compression noise, jpeg artifacts, image-like stillness, painting-like look, cartoon texture, low-resolution textures"
 )
@@ -106,13 +104,12 @@ def resize_image(image: Image.Image) -> Image.Image:
     width, height = image.size
     if width == height:
         return image.resize((SQUARE_DIM, SQUARE_DIM), Image.LANCZOS)
-
+    
     aspect_ratio = width / height
     MAX_ASPECT_RATIO = MAX_DIM / MIN_DIM
     MIN_ASPECT_RATIO = MIN_DIM / MAX_DIM
 
     image_to_resize = image
-
     if aspect_ratio > MAX_ASPECT_RATIO:
         crop_width = int(round(height * MAX_ASPECT_RATIO))
         left = (width - crop_width) // 2
@@ -121,20 +118,20 @@ def resize_image(image: Image.Image) -> Image.Image:
         crop_height = int(round(width / MIN_ASPECT_RATIO))
         top = (height - crop_height) // 2
         image_to_resize = image.crop((0, top, width, top + crop_height))
-
+    
     if width > height:
         target_w = MAX_DIM
         target_h = int(round(target_w / aspect_ratio))
     else:
         target_h = MAX_DIM
         target_w = int(round(target_h * aspect_ratio))
-
+        
     final_w = round(target_w / MULTIPLE_OF) * MULTIPLE_OF
     final_h = round(target_h / MULTIPLE_OF) * MULTIPLE_OF
-
+    
     final_w = max(MIN_DIM, min(MAX_DIM, final_w))
     final_h = max(MIN_DIM, min(MAX_DIM, final_h))
-
+    
     return image_to_resize.resize((final_w, final_h), Image.LANCZOS)
 
 # =========================================================
@@ -152,9 +149,9 @@ def get_duration(
     if input_image is None:
         return 120 # Return default duration if image is missing to prevent crash
     # -----------------------------------------------------
-
     BASE_FRAMES_HEIGHT_WIDTH = 81 * 832 * 624
     BASE_STEP_DURATION = 15
+    
     width, height = resize_image(input_image).size
     frames = get_num_frames(duration_seconds)
     factor = frames * width * height / BASE_FRAMES_HEIGHT_WIDTH
@@ -179,7 +176,7 @@ def generate_video(
 ):
     if input_image is None:
         raise gr.Error("Please upload an input image.")
-
+        
     num_frames = get_num_frames(duration_seconds)
     current_seed = random.randint(0, MAX_SEED) if randomize_seed else int(seed)
     resized_image = resize_image(input_image)
@@ -199,6 +196,7 @@ def generate_video(
 
     with tempfile.NamedTemporaryFile(suffix=".mp4", delete=False) as tmpfile:
         video_path = tmpfile.name
+    
     export_to_video(output_frames_list, video_path, fps=FIXED_FPS)
     return video_path, current_seed
 
@@ -209,7 +207,7 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
     
     # --- ADVERTISEMENT BANNER FOR DREAM HUB PRO ---
     gr.HTML("""
-    <div style="background: linear-gradient(90deg, #4f46e5, #9333ea); color: white; padding: 15px; border-radius: 10px; text-align: center; margin-bottom: 20px; box-shadow: 0 4px 15px rgba(0,0,0,0.1);">
+    <div style="background: linear-gradient(90deg, #4f46e5, #9333ea); color: white; padding: 15px; border-radius: 10px; text-align: center; margin-bottom: 10px; box-shadow: 0 4px 15px rgba(0,0,0,0.1);">
         <div style="display: flex; align-items: center; justify-content: center; gap: 20px; flex-wrap: wrap;">
             <div style="text-align: left;">
                 <h3 style="margin: 0; font-weight: bold; font-size: 18px;">✨ New: Dream Hub Pro (All-in-One)</h3>
@@ -223,6 +221,26 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
         </div>
     </div>
     """)
+    
+    # --- NEW: PROFESSIONAL YOUTUBE CHANNEL BANNER ---
+    gr.HTML("""
+    <div style="background: linear-gradient(90deg, #cc0000, #ff0000); color: white; padding: 12px; border-radius: 10px; text-align: center; margin-bottom: 20px; box-shadow: 0 4px 15px rgba(255,0,0,0.2);">
+        <div style="display: flex; align-items: center; justify-content: center; gap: 20px; flex-wrap: wrap;">
+            <div style="display: flex; align-items: center; gap: 10px;">
+                <span style="font-size: 28px;">▶️</span>
+                <div style="text-align: left;">
+                    <h3 style="margin: 0; font-weight: bold; font-size: 18px;">Imagination Engineering</h3>
+                    <p style="margin: 2px 0 0 0; opacity: 0.9; font-size: 13px;">Tutorials, AI Engineering & Creative Tech</p>
+                </div>
+            </div>
+            <a href="https://www.youtube.com/@ImaginationEngineering" target="_blank" style="text-decoration: none;">
+                <button style="background-color: white; color: #cc0000; border: none; padding: 8px 25px; border-radius: 25px; font-weight: bold; cursor: pointer; transition: transform 0.2s; font-size: 15px; box-shadow: 0 2px 5px rgba(0,0,0,0.2);">
+                    Subscribe & Watch 📺
+                </button>
+            </a>
+        </div>
+    </div>
+    """)
     # ---------------------------------------------
 
     gr.Markdown("# 🚀 Dream Wan 2.2 Faster Pro (14B) — Ultra Fast I2V with Lightning LoRA")
@@ -232,12 +250,13 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
         with gr.Column():
             input_image_component = gr.Image(type="pil", label="Input Image")
             prompt_input = gr.Textbox(label="Prompt", value=default_prompt_i2v)
+            
             duration_seconds_input = gr.Slider(
                 minimum=MIN_DURATION, maximum=MAX_DURATION, step=0.1, value=3.5,
                 label="Duration (seconds)",
                 info=f"Model range: {MIN_FRAMES_MODEL}-{MAX_FRAMES_MODEL} frames at {FIXED_FPS}fps."
             )
-
+            
             with gr.Accordion("Advanced Settings", open=False):
                 negative_prompt_input = gr.Textbox(label="Negative Prompt", value=default_negative_prompt, lines=3)
                 seed_input = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=42)
@@ -245,7 +264,7 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
                 steps_slider = gr.Slider(minimum=1, maximum=30, step=1, value=6, label="Inference Steps")
                 guidance_scale_input = gr.Slider(minimum=0.0, maximum=10.0, step=0.5, value=1, label="Guidance Scale (high noise)")
                 guidance_scale_2_input = gr.Slider(minimum=0.0, maximum=10.0, step=0.5, value=1, label="Guidance Scale 2 (low noise)")
-
+            
             generate_button = gr.Button("🎬 Generate Video", variant="primary")
 
         with gr.Column():
@@ -257,6 +276,7 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
         guidance_scale_input, guidance_scale_2_input,
         seed_input, randomize_seed_checkbox
     ]
+
     generate_button.click(fn=generate_video, inputs=ui_inputs, outputs=[video_output, seed_input])
 
     gr.Examples(