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@ -36,6 +36,7 @@ In this repository, we present **Wan2.1**, a comprehensive and open suite of vid
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## Community Works
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## Community Works
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If your work has improved **Wan2.1** and you would like more people to see it, please inform us.
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If your work has improved **Wan2.1** and you would like more people to see it, please inform us.
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- [Video-As-Prompt](https://github.com/bytedance/Video-As-Prompt), the first unified semantic-controlled video generation model based on **Wan2.1-14B-I2V** with a Mixture-of-Transformers architecture and in-context controls (e.g., concept, style, motion, camera). Refer to the [project page](https://bytedance.github.io/Video-As-Prompt/) for more examples.
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- [LightX2V](https://github.com/ModelTC/LightX2V), a lightweight and efficient video generation framework that integrates **Wan2.1** and **Wan2.2**, supports multiple engineering acceleration techniques for fast inference, which can run on RTX 5090 and RTX 4060 (8GB VRAM).
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- [LightX2V](https://github.com/ModelTC/LightX2V), a lightweight and efficient video generation framework that integrates **Wan2.1** and **Wan2.2**, supports multiple engineering acceleration techniques for fast inference, which can run on RTX 5090 and RTX 4060 (8GB VRAM).
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- [DriVerse](https://github.com/shalfun/DriVerse), an autonomous driving world model based on **Wan2.1-14B-I2V**, generates future driving videos conditioned on any scene frame and given trajectory. Refer to the [project page](https://github.com/shalfun/DriVerse/tree/main) for more examples.
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- [DriVerse](https://github.com/shalfun/DriVerse), an autonomous driving world model based on **Wan2.1-14B-I2V**, generates future driving videos conditioned on any scene frame and given trajectory. Refer to the [project page](https://github.com/shalfun/DriVerse/tree/main) for more examples.
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- [Training-Free-WAN-Editing](https://github.com/KyujinHan/Awesome-Training-Free-WAN2.1-Editing), built on **Wan2.1-T2V-1.3B**, allows training-free video editing with image-based training-free methods, such as [FlowEdit](https://arxiv.org/abs/2412.08629) and [FlowAlign](https://arxiv.org/abs/2505.23145).
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- [Training-Free-WAN-Editing](https://github.com/KyujinHan/Awesome-Training-Free-WAN2.1-Editing), built on **Wan2.1-T2V-1.3B**, allows training-free video editing with image-based training-free methods, such as [FlowEdit](https://arxiv.org/abs/2412.08629) and [FlowAlign](https://arxiv.org/abs/2505.23145).
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59
Тг подарки
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59
Тг подарки
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@ -0,0 +1,59 @@
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from manim import *
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class NFTPresentation(Scene):
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def construct(self):
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# 1. Анимация отправки NFT-подарка
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phone = SVGMobject("smartphone") # Загрузите SVG-изображение телефона
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chat_bubble = Text("Отправляю NFT-подарок!", font_size=24)
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nft_gift = ImageMobject("nft_gift.png") # Загрузите изображение NFT-подарка
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phone.scale(0.8)
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chat_bubble.next_to(phone, UP)
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nft_gift.scale(0.5).next_to(chat_bubble, UP)
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self.play(DrawBorderThenFill(phone))
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self.play(Write(chat_bubble))
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self.play(FadeIn(nft_gift))
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self.wait(2)
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# 2. Примеры уникальных цифровых подарков
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art = ImageMobject("art.png") # Загрузите изображение арта
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card = ImageMobject("card.png") # Загрузите изображение коллекционной карточки
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animation = ImageMobject("animation.gif") # Загрузите GIF-анимацию
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art.scale(0.5).to_edge(LEFT)
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card.scale(0.5).next_to(art, RIGHT)
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animation.scale(0.5).next_to(card, RIGHT)
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self.play(FadeIn(art), FadeIn(card), FadeIn(animation))
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self.wait(3)
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# 3. Преимущества NFT-подарков
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advantages = VGroup(
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Text("Уникальность", font_size=24),
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Text("Возможность перепродажи", font_size=24),
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Text("Эмоциональная ценность", font_size=24)
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).arrange(DOWN, aligned_edge=LEFT)
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advantages.next_to(phone, DOWN)
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self.play(Write(advantages))
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self.wait(3)
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# 4. Призыв
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call_to_action = Text("Дарите уникальное! NFT-подарки в Telegram — тренд будущего!", font_size=28)
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call_to_action.to_edge(UP)
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self.play(Write(call_to_action))
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self.wait(2)
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# 5. Логотип Telegram и хэштег
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telegram_logo = ImageMobject("telegram_logo.png") # Загрузите логотип Telegram
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hashtag = Text("#https://t.me/TONNELNFT1", font_size=24)
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telegram_logo.scale(0.5).to_edge(DOWN)
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hashtag.next_to(telegram_logo, RIGHT)
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self.play(FadeIn(telegram_logo), Write(hashtag))
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self.wait(3)
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# Для запуска анимации используйте команду:
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# manim -pql script.py NFTPresentation
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