Closed Haozong-Zeng closed 9 months ago
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I am using DensePose CSE for capturing poses from videos and guiding a mesh model. My goal is to use my own mesh and the corresponding dataset to train a DensePose CSE model.
I formated the dataset & annotation correctly, and successfully registered the mesh by providing the vertices, geometric distances, symmetry, etc. information. The only thing I missed is the INIT_FILE which contains 'eigenvalues', 'features', & 'baricel_area'. My trained model seems to work well on providing the
&
However, when I tried to find the closest vertices, I noticed that the
is a all-zeros tensor and thus I could not calculate the squared_euclidean_distance_matrix.
When training the model, I received the following warning:
Full changes you made:
_BASE_: "Base-DensePose-RCNN-FPN.yaml" MODEL: WEIGHTS: "https://dl.fbaipublicfiles.com/densepose/cse/a_checkpoint.pkl" RESNETS: DEPTH: 50 ROI_HEADS: NUM_CLASSES: 1 ROI_DENSEPOSE_HEAD: NAME: "DensePoseV1ConvXHead" COARSE_SEGM_TRAINED_BY_MASKS: True CSE: EMBED_LOSS_NAME: "SoftEmbeddingLoss" EMBEDDING_DIST_GAUSS_SIGMA: 0.1 GEODESIC_DIST_GAUSS_SIGMA: 0.1 EMBEDDERS: "my_mesh": TYPE: vertex_feature NUM_VERTICES: n FEATURE_DIM: 256 FEATURES_TRAINABLE: True (also try False) IS_TRAINABLE: True INIT_FILE: ""
What exact command you run: The train_net.py script in the tutorial