openai
How to improve the quality of 3d model?
I think it is possible to generate 3D models from multi-view images to improve accuracy, rather than just one image. I used the following code to try to load three views in the project deployed by Google gloab, but the result failed.
`batch_size = 1 guidance_scale = 3.0
要读取的多个图片文件路径
image_paths = ["test1.png", "test2.png","test3.png"]
读取图片并存储在一个列表中
images = [load_image(path) for path in image_paths]
latents = sample_latents( batch_size=batch_size, model=model, diffusion=diffusion, guidance_scale=guidance_scale, model_kwargs=dict(images=images * batch_size), # 将图片列表传递给 images 参数 progress=True, clip_denoised=True, use_fp16=True, use_karras=True, karras_steps=64, sigma_min=1e-3, sigma_max=160, s_churn=0, ) `
Use it with Zero 123 model its used for generating multiple views you can try it there: https://huggingface.co/spaces/cvlab/zero123-live
I think it is possible to generate 3D models from multi-view images to improve accuracy, rather than just one image. I used the following code to try to load three views in the project deployed by Google gloab, but the result failed.
`batch_size = 1 guidance_scale = 3.0
要读取的多个图片文件路径
image_paths = ["test1.png", "test2.png","test3.png"]
读取图片并存储在一个列表中
images = [load_image(path) for path in image_paths]
latents = sample_latents( batch_size=batch_size, model=model, diffusion=diffusion, guidance_scale=guidance_scale, model_kwargs=dict(images=images * batch_size), # 将图片列表传递给 images 参数 progress=True, clip_denoised=True, use_fp16=True, use_karras=True, karras_steps=64, sigma_min=1e-3, sigma_max=160, s_churn=0, ) `
It looks that the image300M model does not support multiple-views.
I think it is possible to generate 3D models from multi-view images to improve accuracy, rather than just one image. I used the following code to try to load three views in the project deployed by Google gloab, but the result failed. `batch_size = 1 guidance_scale = 3.0
要读取的多个图片文件路径
image_paths = ["test1.png", "test2.png","test3.png"]
读取图片并存储在一个列表中
images = [load_image(path) for path in image_paths] latents = sample_latents( batch_size=batch_size, model=model, diffusion=diffusion, guidance_scale=guidance_scale, model_kwargs=dict(images=images * batch_size), # 将图片列表传递给 images 参数 progress=True, clip_denoised=True, use_fp16=True, use_karras=True, karras_steps=64, sigma_min=1e-3, sigma_max=160, s_churn=0, ) `
It looks that the image300M model does not support multiple-views.
i was facing same issue, so which model supports multiple images?
