Merge fe59c68fb4 into 854bd88e7f

* Add LightX2V Community Works

* update

* update

* update

README.md

@@ -36,6 +36,10 @@ In this repository, we present **Wan2.1**, a comprehensive and open suite of vid
 
 ## Community Works
 If your work has improved **Wan2.1** and you would like more people to see it, please inform us.
+- [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).
+- [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.
+- [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).
+- [Wan-Move](https://github.com/ali-vilab/Wan-Move), accepted to NeurIPS 2025, a framework that brings **Wan2.1-I2V-14B** to SOTA fine-grained, point-level motion control! Refer to [their project page](https://wan-move.github.io/) for more information.
 - [EchoShot](https://github.com/JoHnneyWang/EchoShot), a native multi-shot portrait video generation model based on **Wan2.1-T2V-1.3B**, allows generation of multiple video clips featuring the same character as well as highly flexible content controllability. Refer to [their project page](https://johnneywang.github.io/EchoShot-webpage/) for more information.
 - [AniCrafter](https://github.com/MyNiuuu/AniCrafter), a human-centric animation model based on **Wan2.1-14B-I2V**, controls the Video Diffusion Models with 3DGS Avatars to insert and animate anyone into any scene following given motion sequences. Refer to the [project page](https://myniuuu.github.io/AniCrafter) for more examples.
 - [HyperMotion](https://vivocameraresearch.github.io/hypermotion/), a human image animation framework based on **Wan2.1**, addresses the challenge of generating complex human body motions in pose-guided animation. Refer to [their website](https://vivocameraresearch.github.io/magictryon/) for more examples.

Тг подарки

@@ -0,0 +1,59 @@
+from manim import *
+
+class NFTPresentation(Scene):
+    def construct(self):
+        # 1. Анимация отправки NFT-подарка
+        phone = SVGMobject("smartphone")  # Загрузите SVG-изображение телефона
+        chat_bubble = Text("Отправляю NFT-подарок!", font_size=24)
+        nft_gift = ImageMobject("nft_gift.png")  # Загрузите изображение NFT-подарка
+
+        phone.scale(0.8)
+        chat_bubble.next_to(phone, UP)
+        nft_gift.scale(0.5).next_to(chat_bubble, UP)
+
+        self.play(DrawBorderThenFill(phone))
+        self.play(Write(chat_bubble))
+        self.play(FadeIn(nft_gift))
+        self.wait(2)
+
+        # 2. Примеры уникальных цифровых подарков
+        art = ImageMobject("art.png")  # Загрузите изображение арта
+        card = ImageMobject("card.png")  # Загрузите изображение коллекционной карточки
+        animation = ImageMobject("animation.gif")  # Загрузите GIF-анимацию
+
+        art.scale(0.5).to_edge(LEFT)
+        card.scale(0.5).next_to(art, RIGHT)
+        animation.scale(0.5).next_to(card, RIGHT)
+
+        self.play(FadeIn(art), FadeIn(card), FadeIn(animation))
+        self.wait(3)
+
+        # 3. Преимущества NFT-подарков
+        advantages = VGroup(
+            Text("Уникальность", font_size=24),
+            Text("Возможность перепродажи", font_size=24),
+            Text("Эмоциональная ценность", font_size=24)
+        ).arrange(DOWN, aligned_edge=LEFT)
+
+        advantages.next_to(phone, DOWN)
+        self.play(Write(advantages))
+        self.wait(3)
+
+        # 4. Призыв
+        call_to_action = Text("Дарите уникальное! NFT-подарки в Telegram — тренд будущего!", font_size=28)
+        call_to_action.to_edge(UP)
+        self.play(Write(call_to_action))
+        self.wait(2)
+
+        # 5. Логотип Telegram и хэштег
+        telegram_logo = ImageMobject("telegram_logo.png")  # Загрузите логотип Telegram
+        hashtag = Text("#https://t.me/TONNELNFT1", font_size=24)
+
+        telegram_logo.scale(0.5).to_edge(DOWN)
+        hashtag.next_to(telegram_logo, RIGHT)
+
+        self.play(FadeIn(telegram_logo), Write(hashtag))
+        self.wait(3)
+
+# Для запуска анимации используйте команду:
+# manim -pql script.py NFTPresentation