Keypoint Detection
Transformers
PyTorch
Safetensors
superpoint
feature-extraction
vision
image-matching
Instructions to use magic-leap-community/superpoint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use magic-leap-community/superpoint with Transformers:
# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("magic-leap-community/superpoint") model = AutoModel.from_pretrained("magic-leap-community/superpoint", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 443 Bytes
0c13f95 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | {
"architectures": [
"SuperPointModel"
],
"border_removal_distance": 4,
"decoder_hidden_size": 256,
"descriptor_decoder_dim": 256,
"encoder_hidden_sizes": [
64,
64,
128,
128
],
"initializer_range": 0.02,
"keypoint_decoder_dim": 65,
"keypoint_threshold": 0.005,
"max_keypoints": -1,
"model_type": "superpoint",
"nms_radius": 4,
"torch_dtype": "float32",
"transformers_version": "4.35.0.dev0"
}
|