Age | Commit message (Collapse) | Author | |
---|---|---|---|
2021-01-07 | Type hint for python version lower than 3.9 | Jordan Gong | |
2021-01-07 | Type hint for python version lower than 3.9 | Jordan Gong | |
2021-01-07 | Add typical training script and some bug fixes | Jordan Gong | |
1. Resolve deprecated scheduler stepping issue 2. Make losses in the same scale(replace mean with sum in separate triplet loss, enlarge pose similarity loss 10x) 3. Add ReLU when compute distance in triplet loss 4. Remove classes except Model from `models` package init | |||
2021-01-07 | Change device config and add enable multi-GPU computing | Jordan Gong | |
1. Add `disable_acc` switch for disabling accelerator. When it is off, system will automatically choosing accelerator. 2. Enable multi-GPU training using torch.nn.DataParallel | |||
2021-01-06 | Add CUDA support | Jordan Gong | |
2021-01-06 | Add TensorBoard support | Jordan Gong | |
2021-01-05 | Implement checkpoint mechanism | Jordan Gong | |
2021-01-05 | Implement Batch All Triplet Loss | Jordan Gong | |
2021-01-05 | Change and improve weight initialization | Jordan Gong | |
1. Change initial weights for Conv layers 2. Find a way to init last fc in init_weights | |||
2021-01-03 | Separate last fc matrix from weight init function | Jordan Gong | |
Recursive apply will override other parameters too | |||
2021-01-03 | Delete dead training judge | Jordan Gong | |
2021-01-03 | Implement weight initialization | Jordan Gong | |
2021-01-03 | Update hyperparameter configuration, implement prototype fit function | Jordan Gong | |
2021-01-03 | Add separate fully connected layers | Jordan Gong | |
2021-01-03 | Unit testing on auto-encoder, HPM and Part Net | Jordan Gong | |
2021-01-03 | Bump up version for pillow | Jordan Gong | |
2021-01-02 | Separate training and evaluating | Jordan Gong | |
2021-01-02 | Correct feature dims after disentanglement and HPM backbone removal | Jordan Gong | |
1. Features used in HPM is decoded canonical embedding without transpose convolution 2. Decode pose embedding to image for Part Net 3. Backbone seems to be redundant, we can use feature map given by auto-decoder | |||
2021-01-02 | Change type of pose similarity loss to tensor | Jordan Gong | |
2020-12-31 | Implement some parts of RGB-GaitPart wrapper | Jordan Gong | |
1. Triplet loss function and weight init function haven't been implement yet 2. Tuplize features returned by auto-encoder for later unpack 3. Correct comment error in auto-encoder 4. Swap batch_size dim and time dim in HPM and PartNet in case of redundant transpose 5. Find backbone problems in HPM and disable it temporarily 6. Make feature structure by HPM consistent to that by PartNet 7. Fix average pooling dimension issue and incorrect view change in HP | |||
2020-12-31 | Make HPM capable of processing frames in all batches | Jordan Gong | |
2020-12-31 | Make super class constructor revoke consistent | Jordan Gong | |
2020-12-31 | Bug Fixes in HPM and PartNet | Jordan Gong | |
1. Register list of torch.nn.Module to the network using torch.nn.ModuleList 2. Fix operation error in squeeze list of tensor 3. Replace squeeze with view in HP in case batch size is 1 | |||
2020-12-30 | Correct and refine PartNet | Jordan Gong | |
1. Let FocalConv block capable of processing frames in all batches 2. Correct input dims of TFA and output dims of HP 3. Change torch.unsqueeze and torch.cat to torch.stack | |||
2020-12-30 | Combine FPFE and TFA to PartNet | Jordan Gong | |
2020-12-30 | Combine FPFE and TFA to GaitPart | Jordan Gong | |
2020-12-30 | Add pooling options in HPM | Jordan Gong | |
According to [1], we can use GAP and GMP together, or one of both in ablation study. [1]Y. Fu et al., “Horizontal pyramid matching for person re-identification,” in Proceedings of the AAAI Conference on Artificial Intelligence, 2019, vol. 33, pp. 8295–8302. | |||
2020-12-29 | Return canonical features at condition 1 for later aggregation | Jordan Gong | |
2020-12-29 | Correct batch splitter | Jordan Gong | |
We can disentangle features from different subjects, but cannot do it at different temporal orders | |||
2020-12-29 | Add type hint for new label (numpy.int64) | Jordan Gong | |
2020-12-29 | Encode class names to label and some access improvement | Jordan Gong | |
1. Encode class names using LabelEncoder from sklearn 2. Remove unneeded class variables 3. Protect some variables from being accessed in userspace | |||
2020-12-28 | Wrap the auto-encoder, return 3 losses at t2 | Jordan Gong | |
2020-12-27 | Try some unit tests on CASIA-B dataset | Jordan Gong | |
2020-12-27 | Change default dataset directory | Jordan Gong | |
2020-12-27 | Implement some parts of main model structure | Jordan Gong | |
1. Configuration parsers 2. Model signature generator | |||
2020-12-27 | Fix inconsistency and API deprecation issues in decoder | Jordan Gong | |
1. Add default output channels of decoder 2. Replace deprecated torch.nn.functional.sigmoid with torch.sigmoid | |||
2020-12-27 | Refine auto-encoder | Jordan Gong | |
1. Wrap fully connected layers 2. Introduce hyperparameter tuning in constructor | |||
2020-12-27 | Prepare for FVG dataset | Jordan Gong | |
2020-12-27 | Make naming scheme consistent | Jordan Gong | |
Use `dir` instead of `path` | |||
2020-12-27 | Add dataset selector to config type hint, change ClipLabels typo to ClipViews | Jordan Gong | |
2020-12-27 | Adopt type hinting generics in standard collections (PEP 585) | Jordan Gong | |
2020-12-26 | Implement batch splitter to split sampled data | Jordan Gong | |
Disentanglement cannot be processed on different subjects at the same time, we need to load `pr` subjects one by one. The batch splitter will return a pr-length list of tuples (with 2 dicts containing k-length lists of labels, conditions, view and k-length tensor of clip data, representing condition 1 and condition 2 respectively). | |||
2020-12-26 | Sample k more clips for disentanglement | Jordan Gong | |
2020-12-26 | Add config file and corresponding type hint | Jordan Gong | |
2020-12-26 | Combine transformed height and width to `frame_size` | Jordan Gong | |
2020-12-26 | Bump up version for tqdm | Jordan Gong | |
2020-12-24 | Implement Horizontal Pyramid Matching (HPM) | Jordan Gong | |
2020-12-24 | Optimize imports | Jordan Gong | |
2020-12-24 | Change the usage of layers and reorganize relations of layers | Jordan Gong | |
1. Add batch normalization and activation to layers 2. VGGConv2d and FocalConv2d inherits to BasicConv2d; DCGANConvTranspose2d inherits to BasicConvTranspose2d | |||
2020-12-23 | Make activation inplace | Jordan Gong | |