add zerogpu
Browse files- inference/inference.py +5 -2
inference/inference.py
CHANGED
@@ -2,6 +2,7 @@ import torch
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import numpy as np
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import matplotlib.pyplot as plt
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from inference.utils import get_seg_color, load_model, preprocess_pcd, encode_text
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DEVICE = "cpu"
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if torch.cuda.is_available():
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@@ -75,14 +76,16 @@ def get_heatmap_rgb(model, data, N_CHUNKS=5): # evaluate loader can only have ba
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scores = all_logits.squeeze().cpu()
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heatmap_rgb = torch.tensor(plt.cm.jet(scores.numpy())[:,:3]).squeeze()
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return heatmap_rgb
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-
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def segment_obj(xyz, rgb, normal, queries):
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model = load_model()
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data_dict = preprocess_pcd(torch.tensor(xyz).float().to(DEVICE), torch.tensor(rgb).float().to(DEVICE), torch.tensor(normal).float().to(DEVICE))
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data_dict["label_embeds"] = encode_text(queries)
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seg_rgb = get_segmentation_rgb(model, data_dict)
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return seg_rgb
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-
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def get_heatmap(xyz, rgb, normal, query):
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model = load_model()
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data_dict = preprocess_pcd(torch.tensor(xyz).float().to(DEVICE), torch.tensor(rgb).float().to(DEVICE), torch.tensor(normal).float().to(DEVICE))
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import numpy as np
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import matplotlib.pyplot as plt
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from inference.utils import get_seg_color, load_model, preprocess_pcd, encode_text
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+
import spaces
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DEVICE = "cpu"
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if torch.cuda.is_available():
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scores = all_logits.squeeze().cpu()
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heatmap_rgb = torch.tensor(plt.cm.jet(scores.numpy())[:,:3]).squeeze()
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return heatmap_rgb
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+
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@spaces.GPU(duration=90)
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def segment_obj(xyz, rgb, normal, queries):
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model = load_model()
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data_dict = preprocess_pcd(torch.tensor(xyz).float().to(DEVICE), torch.tensor(rgb).float().to(DEVICE), torch.tensor(normal).float().to(DEVICE))
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data_dict["label_embeds"] = encode_text(queries)
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seg_rgb = get_segmentation_rgb(model, data_dict)
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return seg_rgb
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+
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@spaces.GPU(duration=90)
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def get_heatmap(xyz, rgb, normal, query):
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model = load_model()
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data_dict = preprocess_pcd(torch.tensor(xyz).float().to(DEVICE), torch.tensor(rgb).float().to(DEVICE), torch.tensor(normal).float().to(DEVICE))
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