Meta AI’s animate feature, which lets people generate a short animation of a generated image, carried unique challenges in this regard. To deploy and run at scale, our model to generate image animations had to be able to serve billions of people who use our products and services, d...
Llama.generate: prefix-match hit llama_print_timings: load time = 10599.68 ms llama_pri...
Automate AI image generation Learn how To add vision to its latest models, Meta trained the image system separately to align it with the existing language models. This means that the 11B-Vision and 90B-Vision models are the same as the existing 8B and 70B Llama models when it comes to tex...
Prompt AI: Send a message to the AI and get a response from Llama 3. Image Generation: Generate images using the AI. (Only for FB authenticated users) Get Up To Date Information: Get the latest information from the AI thanks to its connection to the internet. ...
Standard text-image data sets of labeled still images helped the AI learn what objects are called and what they look like. And a database of videos helped it learn how those objects are supposed to move in the world. The combination of the two approaches helped Make-A-Video, which is ...
masks=mask_generator.generate(image)print(len(masks))print(masks[0].keys()) 说明上一张图片的预测结果当中,包含了44个mask,每一个mask又包含下面的参数: segmentation: the mask area: the area of the mask in pixels bbox: the boundary box of the mask in XYWH format ...
concepts = ["floral dress", "straw hat"] # 生成图像 image = multibooth.generate(text_prompt, concepts) image.save("output.png") 资源 项目官网:multibooth.github.io/ GitHub 仓库:github.com/chenyangzhu1 arXiv 技术论文:arxiv.org/pdf/2404.1423 ️ 如果你也关注 AI 的发展现状,且对 AI ...
This repository is for the first comprehensive survey on Meta AI's Segment Anything Model (SAM). - GitHub - liliu-avril/Awesome-Segment-Anything: This repository is for the first comprehensive survey on Meta AI's Segment Anything Model (SAM).
masks = mask_generator.generate(image) 掩码对象包含关于区域和稳定性分数的多个信息,稍后会将标签添加到此掩码对象中。让我们来看一下输出: plt.figure(figsize=(20,20)) plt.imshow(image) show_anns(masks) plt.axis('off') plt.show() 您还可以通过更改以下变量来调整遮罩生成器的参数: mask_generator_...
image_embeddings:从image_encoder中嵌入的图像。具有长度为1的批索引。 point_coords:稀疏输入提示的坐标,对应于点输入和框输入。方框使用两个点进行编码,一个用于左上角,另一个用于右下角。坐标必须已转换为长边1024。具有长度为1的批索引。 point_labels:稀疏输入提示的标签。0是负输入点,1是正输入点,2是左...