Update app.py

app.py

@@ -106,7 +106,7 @@ def prepare_image(image, preset_key):
     return image
 # 🌟 وظيفة لتوليد الفيديو من الصورة والـ prompt
 @torch.no_grad()
-def generate_video(image, prompt, negative_prompt, num_frames, preset_key, guidance_scale=7.5, num_inference_steps=50):
+def generate_video(image, prompt, negative_prompt, num_frames, preset_key, guidance_scale=7.5, num_inference_steps=20):  # Reduced default steps to 20 for faster/less memory
     if image is None:
         raise ValueError("No image provided!")
    
@@ -116,6 +116,11 @@ def generate_video(image, prompt, negative_prompt, num_frames, preset_key, guida
     # Clamp num_frames
     num_frames = max(MIN_FRAMES_MODEL, min(num_frames, MAX_FRAMES_MODEL))
    
+    # Memory check and cleanup before generation
+    if torch.cuda.is_available():
+        print(f"GPU Memory before generation: {torch.cuda.memory_allocated() / 1024**3:.2f} GB")
+        torch.cuda.empty_cache()
+    
     video_frames = pipe(
         prompt=prompt,
         image=prepared_image,
@@ -140,20 +145,27 @@ def generate_video_only(image, prompt, negative_prompt, num_frames, preset_key):
         print("Generating video...")
         final_video = generate_video(image, prompt, negative_prompt, num_frames, preset_key)
        
+        # Cleanup after generation
+        gc.collect()
+        if torch.cuda.is_available():
+            torch.cuda.empty_cache()
+       
         return final_video, "Success!"
+    except torch.cuda.OutOfMemoryError:
+        return None, "Error: Out of GPU memory. Try reducing frames or resolution."
     except Exception as e:
         return None, f"Error: {str(e)}"
 # 🌟 إعداد الواجهة بـ Gradio
 with gr.Blocks(title="Wan2.2 Image-to-Video Generator") as demo:
     gr.Markdown("# 🌟 Wan2.2 I2V Generator")
-    gr.Markdown("Upload an image, add a prompt, and generate a video!")
+    gr.Markdown("Upload an image, add a prompt, and generate a video! Note: For T4 GPU, use <32 frames for best results.")
    
     with gr.Row():
         with gr.Column(scale=1):
             image_input = gr.Image(type="pil", label="Input Image")
             prompt_input = gr.Textbox(label="Prompt", placeholder="A dynamic scene from the image...", lines=2)
             negative_prompt_input = gr.Textbox(label="Negative Prompt", placeholder="blurry, low quality", lines=1)
-            num_frames_slider = gr.Slider(MIN_FRAMES_MODEL, MAX_FRAMES_MODEL, value=64, step=8, label="Number of Frames (Max 45s at 16 FPS)")
+            num_frames_slider = gr.Slider(MIN_FRAMES_MODEL, MAX_FRAMES_MODEL, value=16, step=8, label="Number of Frames (Max 45s at 16 FPS)")  # Default to 16 to avoid OOM
             preset_dropdown = gr.Dropdown(choices=list(DIMENSION_PRESETS.keys()), value="Custom (Default)", label="Output Preset")
             generate_btn = gr.Button("Generate Video", variant="primary")
        
@@ -180,7 +192,7 @@ with gr.Blocks(title="Wan2.2 Image-to-Video Generator") as demo:
                 None, # No example image; user to upload
                 "The person in the image starts walking towards the camera with a smile.",
                 "static, blurry",
-                32,
+                16,  # Reduced for example
                 "YouTube Full HD (16:9)"
             ]
         ],