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fucking llms

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Scott Register
2025-07-27 10:01:12 -07:00
parent a479d6a5f0
commit 300ae5613e
1 changed files with 12 additions and 3 deletions
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15
vr180_streaming/sam2_streaming_simple.py
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@@ -28,14 +28,23 @@ class SAM2StreamingProcessor:
self.device = torch.device(config.get('hardware', {}).get('device', 'cuda'))
# SAM2 model configuration
model_cfg = config.get('matting', {}).get('sam2_model_cfg', 'sam2.1_hiera_l')
model_cfg_name = config.get('matting', {}).get('sam2_model_cfg', 'sam2.1_hiera_l')
checkpoint = config.get('matting', {}).get('sam2_checkpoint',
'segment-anything-2/checkpoints/sam2.1_hiera_large.pt')
# Map config name to Hydra path (like the examples show)
config_mapping = {
'sam2.1_hiera_t': 'configs/sam2.1/sam2.1_hiera_t.yaml',
'sam2.1_hiera_s': 'configs/sam2.1/sam2.1_hiera_s.yaml',
'sam2.1_hiera_b+': 'configs/sam2.1/sam2.1_hiera_b+.yaml',
'sam2.1_hiera_l': 'configs/sam2.1/sam2.1_hiera_l.yaml',
}
model_cfg = config_mapping.get(model_cfg_name, model_cfg_name)
# Build predictor (simple, clean approach)
# Note: SAM2 uses Hydra to find configs automatically in sam2/configs/
self.predictor = build_sam2_video_predictor(
model_cfg, # Just the config name, Hydra finds it automatically
model_cfg, # Relative path from sam2 package
checkpoint,
device=self.device,
vos_optimized=True # Enable VOS optimizations for speed