C3D-tensorflow

Requirements:

1. You must have installed the following two python libs: a) tensorflow b) Pillow
2. You must have downloaded the UCF101 (Action Recognition Data Set)
3. Each single avi file is decoded with 5FPS (it's depend your decision) in a single directory.
   • you can use the ./list/convert_video_to_images.sh script to decode the ucf101 video files
   • run ./list/convert_video_to_images.sh .../UCF101 5
4. Generate {train,test}.list files in list directory. Each line corresponds to "image directory" and a class (zero-based). For example:
   • you can use the ./list/convert_images_to_list.sh script to generate the {train,test}.list for the dataset
   • run ./list/convert_images_to_list.sh .../dataset_images 4, this will generate test.list and train.list files by a factor 4 inside the root folder

database/ucf101/train/ApplyEyeMakeup/v_ApplyEyeMakeup_g01_c01 0
database/ucf101/train/ApplyEyeMakeup/v_ApplyEyeMakeup_g01_c02 0
database/ucf101/train/ApplyEyeMakeup/v_ApplyEyeMakeup_g01_c03 0
database/ucf101/train/ApplyLipstick/v_ApplyLipstick_g01_c01 1
database/ucf101/train/ApplyLipstick/v_ApplyLipstick_g01_c02 1
database/ucf101/train/ApplyLipstick/v_ApplyLipstick_g01_c03 1
database/ucf101/train/Archery/v_Archery_g01_c01 2
database/ucf101/train/Archery/v_Archery_g01_c02 2
database/ucf101/train/Archery/v_Archery_g01_c03 2
database/ucf101/train/Archery/v_Archery_g01_c04 2
database/ucf101/train/BabyCrawling/v_BabyCrawling_g01_c01 3
database/ucf101/train/BabyCrawling/v_BabyCrawling_g01_c02 3
database/ucf101/train/BabyCrawling/v_BabyCrawling_g01_c03 3
database/ucf101/train/BabyCrawling/v_BabyCrawling_g01_c04 3
database/ucf101/train/BalanceBeam/v_BalanceBeam_g01_c01 4
database/ucf101/train/BalanceBeam/v_BalanceBeam_g01_c02 4
database/ucf101/train/BalanceBeam/v_BalanceBeam_g01_c03 4
database/ucf101/train/BalanceBeam/v_BalanceBeam_g01_c04 4
...

5. If you want to test my pre-trained model, you need to download my model from here: https://www.dropbox.com/sh/8wcjrcadx4r31ux/AAAkz3dQ706pPO8ZavrztRCca?dl=0

Run command:

1. python train_c3d_ucf101.py will train C3D model. The trained model will saved in models directory.
2. python predict_c3d_ucf101.py will test C3D model on a validation data set.

Experiment result:

Top-1 accuracy of 72.6% should be achieved for the validation dataset with this code and pre-trained from the sports1M model. You can download my pretrained UCF101 model and mean file from here: https://www.dropbox.com/sh/8wcjrcadx4r31ux/AAAkz3dQ706pPO8ZavrztRCca?dl=0

References:

• Thanks the author Du tran's code: C3D-caffe
• C3D: Generic Features for Video Analysis