created application

app.py

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+import gradio as gr
+import torch
+from diffusers import I2VGenXLPipeline
+from diffusers.utils import export_to_gif, load_image
+
+def generate_video(prompt, image_url, negative_prompt, num_inference_steps, guidance_scale, seed):
+    try:
+        # Load pipeline
+        pipeline = I2VGenXLPipeline.from_pretrained("ali-vilab/i2vgen-xl", torch_dtype=torch.float16, variant="fp16")
+        pipeline.enable_model_cpu_offload()
+
+        # Load image
+        image = load_image(image_url).convert("RGB")
+
+        # Set random seed
+        generator = None if seed == -1 else torch.manual_seed(seed)
+
+        # Generate frames
+        result = pipeline(
+            prompt=prompt,
+            image=image,
+            num_inference_steps=num_inference_steps,
+            negative_prompt=negative_prompt,
+            guidance_scale=guidance_scale,
+            generator=generator,
+        ).frames[0]
+
+        # Export to GIF
+        gif_path = "i2v_output.gif"
+        export_to_gif(result, gif_path)
+
+        return gif_path
+    except Exception as e:
+        return f"An error occurred: {e}"
+
+# Gradio Interface
+interface = gr.Interface(
+    fn=generate_video,
+    inputs=[
+        gr.Textbox(label="Enter your prompt", lines=2, placeholder="Describe your desired video."),
+        gr.Textbox(label="Enter image URL", placeholder="Paste the URL of the input image."),
+        gr.Textbox(label="Enter negative prompt (optional)", placeholder="Describe undesired aspects (e.g., blurry, distorted)."),
+        gr.Slider(label="Number of Inference Steps", minimum=10, maximum=100, value=50, step=1),
+        gr.Slider(label="Guidance Scale", minimum=1.0, maximum=20.0, value=9.0, step=0.1),
+        gr.Number(label="Seed (set to -1 for random)", value=8888),
+    ],
+    outputs=gr.Image(label="Generated Video (GIF)", type="filepath"),
+    title="Image-to-Video Generator",
+    description="Generate videos from text prompts and input images using AI.",
+    article="Made by: Mostafa Hazem, Daiee Elchazly, Mohamed Mostafa, Noreen Hamdy"
+)
+
+if __name__ == "__main__":
+    interface.launch()

requirments.txt

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+gradio
+diffusers
+streamlit
+torch