From 78691256781dc76c6a67773298412fe352e3b53f Mon Sep 17 00:00:00 2001 From: bomri Date: Wed, 24 Feb 2021 17:11:26 +0200 Subject: [PATCH] Video Transformer Network (https://arxiv.org/abs/2102.00719) - VTN model setup - add the ability to return the entire video - add support to return the frames index - update defaults - VIT_B_VTN.yaml - adjusting the if-else in pack_pathway_output - VTN README.md + update main README.md + update MODEL_ZOO --- MODEL_ZOO.md | 8 +- README.md | 3 + configs/Kinetics/VIT_B_VTN.yaml | 60 +++++++++++++ projects/vtn/README.md | 70 ++++++++++++++++ projects/vtn/fig/a.png | Bin 0 -> 158874 bytes projects/vtn/fig/arch.png | Bin 0 -> 98945 bytes projects/vtn/fig/b.png | Bin 0 -> 156252 bytes projects/vtn/fig/c.png | Bin 0 -> 218996 bytes projects/vtn/fig/d.png | Bin 0 -> 216499 bytes projects/vtn/fig/e.png | Bin 0 -> 271565 bytes projects/vtn/fig/vtn_demo.gif | Bin 0 -> 8804073 bytes slowfast/config/defaults.py | 53 ++++++++++++ slowfast/datasets/decoder.py | 23 +++-- slowfast/datasets/kinetics.py | 30 ++++++- slowfast/datasets/ssv2.py | 1 + slowfast/datasets/utils.py | 10 ++- slowfast/models/video_model_builder.py | 112 ++++++++++++++++++++++++- slowfast/models/vtn_helper.py | 55 ++++++++++++ slowfast/utils/misc.py | 8 +- 19 files changed, 415 insertions(+), 18 deletions(-) create mode 100644 configs/Kinetics/VIT_B_VTN.yaml create mode 100644 projects/vtn/README.md create mode 100644 projects/vtn/fig/a.png create mode 100644 projects/vtn/fig/arch.png create mode 100644 projects/vtn/fig/b.png create mode 100644 projects/vtn/fig/c.png create mode 100644 projects/vtn/fig/d.png create mode 100644 projects/vtn/fig/e.png create mode 100644 projects/vtn/fig/vtn_demo.gif create mode 100644 slowfast/models/vtn_helper.py diff --git a/MODEL_ZOO.md b/MODEL_ZOO.md index 32e9e2d02..780abd43a 100644 --- a/MODEL_ZOO.md +++ b/MODEL_ZOO.md @@ -25,6 +25,12 @@ We provided original pretrained models from Caffe2 on heavy models (testing Caff | X3D | M | - | 16 x 5 | 75.1 | 76.2 | 3.8 | 4.73 | [`link`](https://dl.fbaipublicfiles.com/pyslowfast/x3d_models/x3d_m.pyth) | Kinetics/X3D_M | | X3D | L | - | 16 x 5 | 76.9 | 77.5 | 6.2 | 18.37 | [`link`](https://dl.fbaipublicfiles.com/pyslowfast/x3d_models/x3d_l.pyth) | Kinetics/X3D_L | +## VTN model (details in projects/vtn) + +| architecture | backbone | pretrain | frame length x sample rate | top1 | top5 | model | config | +| :-------------: | :-------------: | :-------------: | :-------------: | :-------------: | :-------------: | ------------- | ------------- | +| VTN | ViT-B | ImageNet-21K | - | 77.72 | 93.24 | [`link`](https://researchpublic.blob.core.windows.net/vtn/VTN_VIT_B_KINETICS.pyth) | Kinetics/VIT_B_VTN | + ## AVA | architecture | depth | Pretrain Model | frame length x sample rate | MAP | AVA version | model | @@ -67,4 +73,4 @@ We also release the imagenet pretrained model if finetuning from ImageNet is pre | architecture | depth | Top1 | Top5 | model | | ------------- | ------------- | ------------- | ------------- | ------------- | -| ResNet | R50 | 23.6 | 6.8 | [`link`](https://dl.fbaipublicfiles.com/pyslowfast/model_zoo/kinetics400/R50_IN1K.pyth) | +| ResNet | R50 | 23.6 | 6.8 | [`link`](https://dl.fbaipublicfiles.com/pyslowfast/model_zoo/kinetics400/R50_IN1K.pyth) | \ No newline at end of file diff --git a/README.md b/README.md index 07a7221e8..eb8c56dc1 100644 --- a/README.md +++ b/README.md @@ -6,6 +6,7 @@ PySlowFast is an open source video understanding codebase from FAIR that provide - [Non-local Neural Networks](https://arxiv.org/abs/1711.07971) - [A Multigrid Method for Efficiently Training Video Models](https://arxiv.org/abs/1912.00998) - [X3D: Progressive Network Expansion for Efficient Video Recognition](https://arxiv.org/abs/2004.04730) +- [Video Transformer Network](https://arxiv.org/abs/2102.00719)
@@ -21,8 +22,10 @@ The goal of PySlowFast is to provide a high-performance, light-weight pytorch co - I3D - Non-local Network - X3D +- VTN ## Updates + - We now support [VTN Model](https://arxiv.org/abs/2102.00719). See [`projects/vtn`](./projects/vtn/README.md) for more information. - We now support [X3D Models](https://arxiv.org/abs/2004.04730). See [`projects/x3d`](./projects/x3d/README.md) for more information. - We now support [Multigrid Training](https://arxiv.org/abs/1912.00998) for efficiently training video models. See [`projects/multigrid`](./projects/multigrid/README.md) for more information. - PySlowFast is released in conjunction with our [ICCV 2019 Tutorial](https://alexander-kirillov.github.io/tutorials/visual-recognition-iccv19/). diff --git a/configs/Kinetics/VIT_B_VTN.yaml b/configs/Kinetics/VIT_B_VTN.yaml new file mode 100644 index 000000000..ecd33b878 --- /dev/null +++ b/configs/Kinetics/VIT_B_VTN.yaml @@ -0,0 +1,60 @@ +TRAIN: + ENABLE: True + DATASET: kinetics + BATCH_SIZE: 16 + EVAL_PERIOD: 1 + CHECKPOINT_PERIOD: 1 + AUTO_RESUME: True + EVAL_FULL_VIDEO: True + EVAL_NUM_FRAMES: 250 +DATA: + NUM_FRAMES: 16 + SAMPLING_RATE: 8 + TARGET_FPS: 25 + TRAIN_JITTER_SCALES: [256, 320] + TRAIN_CROP_SIZE: 224 + TEST_CROP_SIZE: 224 + INPUT_CHANNEL_NUM: [3] +SOLVER: + BASE_LR: 0.001 + LR_POLICY: steps_with_relative_lrs + STEPS: [0, 13, 24] + LRS: [1, 0.1, 0.01] + MAX_EPOCH: 25 + MOMENTUM: 0.9 + OPTIMIZING_METHOD: sgd +MODEL: + NUM_CLASSES: 400 + ARCH: VIT + MODEL_NAME: VTN + LOSS_FUNC: cross_entropy + DROPOUT_RATE: 0.5 +VTN: + PRETRAINED: True + MLP_DIM: 768 + DROP_PATH_RATE: 0.0 + DROP_RATE: 0.0 + HIDDEN_DIM: 768 + MAX_POSITION_EMBEDDINGS: 288 + NUM_ATTENTION_HEADS: 12 + NUM_HIDDEN_LAYERS: 3 + ATTENTION_MODE: 'sliding_chunks' + PAD_TOKEN_ID: -1 + ATTENTION_WINDOW: [18, 18, 18] + INTERMEDIATE_SIZE: 3072 + ATTENTION_PROBS_DROPOUT_PROB: 0.1 + HIDDEN_DROPOUT_PROB: 0.1 +TEST: + ENABLE: True + DATASET: kinetics + BATCH_SIZE: 16 + NUM_ENSEMBLE_VIEWS: 1 + NUM_SPATIAL_CROPS: 1 +DATA_LOADER: + NUM_WORKERS: 8 + PIN_MEMORY: True +NUM_GPUS: 4 +NUM_SHARDS: 1 +RNG_SEED: 0 +OUTPUT_DIR: . +LOG_MODEL_INFO: False \ No newline at end of file diff --git a/projects/vtn/README.md b/projects/vtn/README.md new file mode 100644 index 000000000..fe4a9f0ac --- /dev/null +++ b/projects/vtn/README.md @@ -0,0 +1,70 @@ +# Video Transformer Network +Daniel Neimark, Omri Bar, Maya Zohar, Dotan Asselmann [[Paper](https://arxiv.org/abs/2102.00719)] + +
+ + +
+
+ + +## Installation +``` +pip install timm +pip install transformers[torch] +``` + +## Getting started +To use VTN models please refer to the configs under `configs/Kinetics`, or see +the [MODEL_ZOO.md](https://github.com/facebookresearch/SlowFast/blob/master/MODEL_ZOO.md) +for pre-trained models*. + +To train ViT-B-VTN on your dataset (see [paper](https://arxiv.org/abs/2102.00719) for details): +``` +python tools/run_net.py \ + --cfg configs/Kinetics/VIT_B_VTN.yaml \ + DATA.PATH_TO_DATA_DIR path_to_your_dataset \ +``` + +To test the trained ViT-B-VTN on Kinetics-400 dataset: +``` +python tools/run_net.py \ + --cfg configs/Kinetics/VIT_B_VTN.yaml \ + DATA.PATH_TO_DATA_DIR path_to_kinetics_dataset \ + TRAIN.ENABLE False \ + TEST.CHECKPOINT_FILE_PATH path_to_model \ + TEST.CHECKPOINT_TYPE pytorch +``` + +\* VTN models in [MODEL_ZOO.md](https://github.com/facebookresearch/SlowFast/blob/master/MODEL_ZOO.md) produce slightly +different results than those reported in the paper due to differences between the PySlowFast code base and the +original code used to train the models (mainly around data and video loading). + +## Citing VTN +If you find VTN useful for your research, please consider citing the paper using the following BibTeX entry. +```BibTeX +@article{neimark2021video, + title={Video Transformer Network}, + author={Neimark, Daniel and Bar, Omri and Zohar, Maya and Asselmann, Dotan}, + journal={arXiv preprint arXiv:2102.00719}, + year={2021} +} +``` + + +## Additional Qualitative Results + +
+

+ Label: Tai chi. Prediction: Tai chi.

+

+ Label: Chopping wood. Prediction: Chopping wood.

+

+ Label: Archery. Prediction: Archery.

+

+ Label: Throwing discus. Prediction: Flying kite.

+

+ Label: Surfing water. Prediction: Parasailing.

+

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