Merge fe59c68fb4 into 8f7f6514f1

README.md

@@ -36,7 +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.
-- [Phantom](https://github.com/Phantom-video/Phantom) has developed a unified video generation framework for single and multi-subject references based on **Wan2.1-T2V-1.3B**. Please refer to [their examples](https://github.com/Phantom-video/Phantom).
+- [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.
+- [MagicTryOn](https://vivocameraresearch.github.io/magictryon/), a video virtual try-on framework built upon **Wan2.1-14B-I2V**, addresses the limitations of existing models in expressing garment details and maintaining dynamic stability during human motion. Refer to [their website](https://vivocameraresearch.github.io/magictryon/) for more examples.
+- [ATI](https://github.com/bytedance/ATI), built on **Wan2.1-I2V-14B**, is a trajectory-based motion-control framework that unifies object, local, and camera movements in video generation. Refer to [their website](https://anytraj.github.io/) for more examples.
+- [Phantom](https://github.com/Phantom-video/Phantom) has developed a unified video generation framework for single and multi-subject references based on both **Wan2.1-T2V-1.3B** and **Wan2.1-T2V-14B**. Please refer to [their examples](https://github.com/Phantom-video/Phantom).
 - [UniAnimate-DiT](https://github.com/ali-vilab/UniAnimate-DiT), based on **Wan2.1-14B-I2V**, has trained a Human image animation model and has open-sourced the inference and training code. Feel free to enjoy it!
 - [CFG-Zero](https://github.com/WeichenFan/CFG-Zero-star) enhances **Wan2.1** (covering both T2V and I2V models) from the perspective of CFG.
 - [TeaCache](https://github.com/ali-vilab/TeaCache) now supports **Wan2.1** acceleration, capable of increasing speed by approximately 2x. Feel free to give it a try!

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