diff --git a/app.py b/app.py index a805d39..9baab6e 100644 --- a/app.py +++ b/app.py @@ -23,6 +23,13 @@ from src.utils.infer_util import remove_background, resize_foreground, images_to import tempfile from huggingface_hub import hf_hub_download +if torch.cuda.is_available() and torch.cuda.device_count() >= 2: + device0 = torch.device('cuda:0') + device1 = torch.device('cuda:1') +else: + device0 = torch.device('cuda' if torch.cuda.is_available() else 'cpu') + device1 = device0 + def get_render_cameras(batch_size=1, M=120, radius=2.5, elevation=10.0, is_flexicubes=False): """ @@ -86,7 +93,7 @@ unet_ckpt_path = hf_hub_download(repo_id="TencentARC/InstantMesh", filename="dif state_dict = torch.load(unet_ckpt_path, map_location='cpu') pipeline.unet.load_state_dict(state_dict, strict=True) -pipeline = pipeline.to(device) +pipeline = pipeline.to(device0) # load reconstruction model print('Loading reconstruction model ...') @@ -96,9 +103,9 @@ state_dict = torch.load(model_ckpt_path, map_location='cpu')['state_dict'] state_dict = {k[14:]: v for k, v in state_dict.items() if k.startswith('lrm_generator.') and 'source_camera' not in k} model.load_state_dict(state_dict, strict=True) -model = model.to(device) +model = model.to(device1) if IS_FLEXICUBES: - model.init_flexicubes_geometry(device, fovy=30.0) + model.init_flexicubes_geometry(device1, fovy=30.0) model = model.eval() print('Loading Finished!') @@ -124,7 +131,7 @@ def generate_mvs(input_image, sample_steps, sample_seed): seed_everything(sample_seed) # sampling - generator = torch.Generator(device=device) + generator = torch.Generator(device=device0) z123_image = pipeline( input_image, num_inference_steps=sample_steps, @@ -172,11 +179,11 @@ def make3d(images): images = torch.from_numpy(images).permute(2, 0, 1).contiguous().float() # (3, 960, 640) images = rearrange(images, 'c (n h) (m w) -> (n m) c h w', n=3, m=2) # (6, 3, 320, 320) - input_cameras = get_zero123plus_input_cameras(batch_size=1, radius=4.0).to(device) + input_cameras = get_zero123plus_input_cameras(batch_size=1, radius=4.0).to(device1) render_cameras = get_render_cameras( - batch_size=1, radius=4.5, elevation=20.0, is_flexicubes=IS_FLEXICUBES).to(device) + batch_size=1, radius=4.5, elevation=20.0, is_flexicubes=IS_FLEXICUBES).to(device1) - images = images.unsqueeze(0).to(device) + images = images.unsqueeze(0).to(device1) images = v2.functional.resize(images, (320, 320), interpolation=3, antialias=True).clamp(0, 1) mesh_fpath = tempfile.NamedTemporaryFile(suffix=f".obj", delete=False).name