Dependecy update for demo

docs/GETTING_STARTED.md

@@ -45,14 +45,14 @@ And the full feature extraction is updated in [movienet-tools](https://github.co
 
 ### Demo
 #### Preparation
-- [pytube](https://github.com/nficano/pytube) is to download YouTube video. Install with ```pip install pytube3 --upgrade```
+- [pytube](https://github.com/nficano/pytube) is to download YouTube video. Install with ```pip install -U pytube```
 - FFMPEG is to cut scene video and it is usually installed by your OS
 
 #### Run
 ```sh
 cd pre
 python demodownload.py ## Download a YouTube video with pytube
-python ShotDetect/shotdetect.py --print_result --save_keyf --save_keyf_txt ## Cut shot 
+python ShotDetection/shotdetect.py --print_result --save_keyf --save_keyf_txt ## Cut shot 
 cd ../lgss
 python run.py config/demo.py ## Cut scene 
  ```

docs/requirements.txt

@@ -1,2 +1,4 @@
 tqdm
-mmcv
+mmcv-full
+tensorboardX
+scikit-learn

lgss/config/demo.py

@@ -11,12 +11,12 @@
 video_name = "demo"
 shot_num = 4  # even
 seq_len = 10  # even
-gpus = "0,1,2,3,4,5,6,7"
+gpus = "0"
 
 # dataset settings
 dataset = dict(
     name="demo",
-    mode=['image'],
+    mode=['image', 'place'],
 )
 # model settings
 model = dict(
@@ -39,7 +39,7 @@
 resume = None
 trainFlag = False
 testFlag = True
-batch_size = 16
+batch_size = 4
 epochs = 30
 logger = dict(log_interval=200, logs_dir="../run/{}".format(experiment_name))
 data_loader_kwargs = dict(num_workers=32, pin_memory=True, drop_last=False)

lgss/run.py

@@ -1,6 +1,6 @@
 from __future__ import print_function
 
-from mmcv import Config
+from mmengine import Config
 from tensorboardX import SummaryWriter
 
 import src.models as models

pre/demodownload.py

@@ -9,7 +9,7 @@ def main():
     os.makedirs("../data/demo", exist_ok = True)
     os.makedirs("../data/demo/video", exist_ok = True)
     video_save_path = "../data/demo/video"
-    yt = YouTube('https://www.youtube.com/watch?v=rT22nYLaVbo')
+    yt = YouTube('https://www.youtube.com/watch?v=9Puz_zu3O3g')
     yt.streams.get_highest_resolution().download(video_save_path)
     shutil.move(osp.join(video_save_path,os.listdir(video_save_path)[0]),osp.join(video_save_path,"demo.mp4"))
 

pre/place/extract_feat.py

@@ -230,7 +230,7 @@ def main(args):
 
 
 if __name__ == '__main__':
-    data_root = "data/demo"
+    data_root = "../data/demo"
     parser = argparse.ArgumentParser("Place feature using ResNet50 with ImageNet pretrain")
     parser.add_argument('--save-one-frame-feat', action="store_true")
     parser.add_argument('-b', '--batch-size', type=int, default=512)