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Update app.py
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app.py
CHANGED
@@ -1,9 +1,9 @@
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import os
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import subprocess
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import tempfile
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from huggingface_hub import snapshot_download
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import gradio as gr
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import spaces
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# ---------------- Step 1: Download Model ----------------
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repo_id = "Wan-AI/Wan2.2-TI2V-5B"
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@@ -12,45 +12,23 @@ ckpt_dir = snapshot_download(repo_id, local_dir_use_symlinks=False)
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print(f"Using checkpoints from {ckpt_dir}")
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# ---------------- Step 2: Duration Calculation ----------------
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def get_duration(prompt, size, duration_seconds):
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try:
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h, w = size.lower().replace(" ", "").split("*")
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h, w = int(h), int(w)
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except Exception:
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h, w = 704, 1280
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return duration
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# ---------------- Step 3: Helpers ----------------
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def find_generated_mp4():
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mp4_files = [f for f in os.listdir(".") if f.lower().endswith(".mp4")]
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if not mp4_files:
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return None
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mp4_files.sort(key=lambda x: os.path.getmtime(x), reverse=True)
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return mp4_files[0]
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def run_generate_command(cmd):
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print(f"[RUN] {' '.join(cmd)}")
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try:
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subprocess.run(cmd, check=True)
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except subprocess.CalledProcessError as e:
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return None, None, f"Error: {e}"
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if not mp4_file:
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return None, None, "No output video found."
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temp_dir = tempfile.mkdtemp()
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output_path = os.path.join(temp_dir, mp4_file)
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os.rename(mp4_file, output_path)
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return output_path, output_path, "Generation successful!"
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# ---------------- Step 4: Generation Functions ----------------
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@spaces.GPU(duration=get_duration)
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def generate_t2v(prompt, size="1280*704", duration_seconds=5):
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if not prompt.strip():
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return None, None, "Please enter a prompt."
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cmd = [
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"python", "generate.py",
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"--task", "ti2v-5B",
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@@ -59,14 +37,25 @@ def generate_t2v(prompt, size="1280*704", duration_seconds=5):
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"--offload_model", "True",
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"--convert_model_dtype",
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"--t5_cpu",
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"--prompt", prompt
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"--steps", "50",
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"--guidance_scale", "5.0"
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]
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@spaces.GPU(duration=get_duration)
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def generate_i2v(image, prompt, size="1280*704", duration_seconds=5):
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if image is None or not prompt.strip():
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return None, None, "Please upload an image and enter a prompt."
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@@ -74,6 +63,8 @@ def generate_i2v(image, prompt, size="1280*704", duration_seconds=5):
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image_path = os.path.join(temp_dir, "input.jpg")
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image.save(image_path)
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cmd = [
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"python", "generate.py",
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"--task", "ti2v-5B",
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"--convert_model_dtype",
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"--t5_cpu",
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"--image", image_path,
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"--prompt", prompt
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"--steps", "50",
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"--guidance_scale", "5.0"
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]
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# ---------------- Step
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with gr.Blocks() as demo:
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gr.Markdown("## π₯ Wan2.2-TI2V-5B Video Generator")
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gr.Markdown("
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with gr.Tab("Text-to-Video"):
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t2v_prompt = gr.Textbox(
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)
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t2v_size = gr.Textbox(label="Video Size", value="1280*704")
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t2v_duration = gr.Number(label="Video Length (seconds)", value=5)
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t2v_btn = gr.Button("Generate from Text")
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t2v_video = gr.Video(label="Generated Video"
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t2v_download = gr.
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t2v_status = gr.Textbox(label="Status")
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t2v_btn.click(
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generate_t2v,
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[t2v_prompt, t2v_size, t2v_duration],
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[t2v_video, t2v_download, t2v_status]
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)
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)
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i2v_size = gr.Textbox(label="Video Size", value="1280*704")
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i2v_duration = gr.Number(label="Video Length (seconds)", value=5)
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i2v_btn = gr.Button("Generate from Image")
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i2v_video = gr.Video(label="Generated Video"
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i2v_download = gr.
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i2v_status = gr.Textbox(label="Status")
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i2v_btn.click(
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generate_i2v,
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[i2v_image, i2v_prompt, i2v_size, i2v_duration],
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[i2v_video, i2v_download, i2v_status]
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)
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import spaces
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import os
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import subprocess
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import tempfile
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from huggingface_hub import snapshot_download
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import gradio as gr
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# ---------------- Step 1: Download Model ----------------
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repo_id = "Wan-AI/Wan2.2-TI2V-5B"
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print(f"Using checkpoints from {ckpt_dir}")
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# ---------------- Step 2: Duration Calculation ----------------
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def get_duration(prompt, size, duration_seconds, steps):
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try:
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h, w = size.lower().replace(" ", "").split("*")
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h, w = int(h), int(w)
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except Exception:
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h, w = 704, 1280
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return int(duration_seconds) * int(steps) * 2.25 + 5
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# ---------------- Step 3: Generation Functions ----------------
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@spaces.GPU(duration=get_duration)
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def generate_t2v(prompt, size="1280*704", duration_seconds=5, steps=25):
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if not prompt.strip():
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return None, None, "Please enter a prompt."
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temp_dir = tempfile.mkdtemp()
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output_path = os.path.join(temp_dir, "output.mp4")
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cmd = [
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"python", "generate.py",
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"--task", "ti2v-5B",
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"--offload_model", "True",
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"--convert_model_dtype",
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"--t5_cpu",
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"--prompt", prompt
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]
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print(f"[T2V] Running command: {' '.join(cmd)}")
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try:
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subprocess.run(cmd, check=True)
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except subprocess.CalledProcessError as e:
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return None, None, f"Error during T2V generation: {e}"
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if os.path.exists("output.mp4"):
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os.rename("output.mp4", output_path)
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if not os.path.exists(output_path):
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return None, None, "Generation finished but output file not found."
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download_link = f"<a href='file/{output_path}' download>π₯ Download Video</a>"
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return output_path, download_link, "Text-to-Video generated successfully!"
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@spaces.GPU(duration=get_duration)
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def generate_i2v(image, prompt, size="1280*704", duration_seconds=5, steps=25):
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if image is None or not prompt.strip():
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return None, None, "Please upload an image and enter a prompt."
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image_path = os.path.join(temp_dir, "input.jpg")
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image.save(image_path)
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output_path = os.path.join(temp_dir, "output.mp4")
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cmd = [
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"python", "generate.py",
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"--task", "ti2v-5B",
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"--convert_model_dtype",
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"--t5_cpu",
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"--image", image_path,
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"--prompt", prompt
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]
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print(f"[I2V] Running command: {' '.join(cmd)}")
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try:
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subprocess.run(cmd, check=True)
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except subprocess.CalledProcessError as e:
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return None, None, f"Error during I2V generation: {e}"
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if os.path.exists("output.mp4"):
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os.rename("output.mp4", output_path)
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if not os.path.exists(output_path):
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return None, None, "Generation finished but output file not found."
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download_link = f"<a href='file/{output_path}' download>π₯ Download Video</a>"
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return output_path, download_link, "Image-to-Video generated successfully!"
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# ---------------- Step 4: Gradio UI ----------------
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with gr.Blocks() as demo:
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gr.Markdown("## π₯ Wan2.2-TI2V-5B Video Generator")
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gr.Markdown("Choose **Text-to-Video** or **Image-to-Video** mode below.")
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with gr.Tab("Text-to-Video"):
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t2v_prompt = gr.Textbox(
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)
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t2v_size = gr.Textbox(label="Video Size", value="1280*704")
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t2v_duration = gr.Number(label="Video Length (seconds)", value=5)
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t2v_steps = gr.Number(label="Inference Steps", value=25)
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t2v_btn = gr.Button("Generate from Text")
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t2v_video = gr.Video(label="Generated Video")
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t2v_download = gr.HTML()
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t2v_status = gr.Textbox(label="Status")
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t2v_btn.click(
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generate_t2v,
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[t2v_prompt, t2v_size, t2v_duration, t2v_steps],
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[t2v_video, t2v_download, t2v_status]
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)
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)
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i2v_size = gr.Textbox(label="Video Size", value="1280*704")
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i2v_duration = gr.Number(label="Video Length (seconds)", value=5)
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i2v_steps = gr.Number(label="Inference Steps", value=25)
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i2v_btn = gr.Button("Generate from Image")
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i2v_video = gr.Video(label="Generated Video")
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i2v_download = gr.HTML()
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i2v_status = gr.Textbox(label="Status")
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i2v_btn.click(
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generate_i2v,
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[i2v_image, i2v_prompt, i2v_size, i2v_duration, i2v_steps],
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[i2v_video, i2v_download, i2v_status]
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)
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