Fix minor issues for final release

verlab · Apr 1, 2022 · b63fc5d · b63fc5d
1 parent 4beea9e
commit b63fc5d
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Showing 4 changed files with 34 additions and 33 deletions.
diff --git a/TextDrivenVideoAcceleration_TPAMI_2022.ipynb b/TextDrivenVideoAcceleration_TPAMI_2022.ipynb
@@ -55,21 +55,26 @@
       },
       "outputs": [],
       "source": [
-        "VIDEO_ID = 'eQZEf3NCCo4'\n",
-        "document = ['combine rice vinegar sugar and salt',\n",
-        "            'mix the sauce and pour on the rice',\n",
-        "            'prepare some crab meat chop and peel an avocado into thin slices',\n",
-        "            'wrap the mat with plastic',\n",
-        "            'place the seaweed down and put the rice on it',\n",
-        "            'add sesame seeds crab meat and avocado roll it up and press firmly',\n",
-        "            'slice the roll']\n",
+        "VIDEO_ID = 'jnewhlK2USg'\n",
+        "document = ['chop some tuna meat into small pieces',\n",
+        "            'mix the tuna pieces and some fish eggs in a bowl',\n",
+        "            'add hot sauce and mayo and then mix them together',\n",
+        "            'spread some cooked rice on seaweed sushi wrapper',\n",
+        "            'add the tuna mix on top and season with some sesame seeds',\n",
+        "            'roll it up and press firmly',\n",
+        "            'cut the roll into small rolls']\n",
         "\n",
-        "! yt-dlp https://www.youtube.com/watch?v=$VIDEO_ID -o $VIDEO_ID # Download Video File\n",
+        "! yt-dlp https://www.youtube.com/watch?v=$VIDEO_ID -o $VIDEO_ID --merge-output-format mp4 # Download Video File\n",
         "\n",
-        "sf = model.fast_forward_video(video_filename=f'{VIDEO_ID}.webm',\n",
+        "print('\\nExtracting VDAN+ Features...')\n",
+        "semantic_embeddings = model.get_semantic_embeddings(video_filename=f'{VIDEO_ID}.mp4', document=document)\n",
+        "\n",
+        "print('\\nFast Forwarding Video...')\n",
+        "sf = model.fast_forward_video(video_filename=f'{VIDEO_ID}.mp4',\n",
         "                              document=document,\n",
         "                              desired_speedup=12,\n",
-        "                              output_video_filename=f'{VIDEO_ID}_FF.avi')"
+        "                              output_video_filename=f'{VIDEO_ID}_FF.avi',\n",
+        "                              semantic_embeddings=semantic_embeddings)"
       ]
     },
     {

diff --git a/requirements.txt b/requirements.txt
@@ -1,14 +1,16 @@
-gym==0.18.3
-matplotlib==3.4.2
-nltk==3.6.2
-numpy==1.20.3
-opencv_python==4.5.2.54
-pandas==1.3.5
-pandas_stubs==1.2.0.39
-Pillow==9.0.1
-scipy==1.7.0
-seaborn==0.11.1
-torch==1.10.0
-torchvideo==0.0.1
-torchvision==0.8.2
-tqdm==4.61.2
+gym>=0.18.3
+matplotlib>=3.4.2
+nltk>=3.6.2
+numpy>=1.20.3
+opencv_python>=4.5.2.54
+pandas>=1.3.5
+pandas_stubs>=1.2.0.39
+Pillow>=8.2.0
+scipy>=1.7.0
+seaborn>=0.11.1
+torch>=1.10.0
+torchvideo>=0.0.1
+torchvision>=0.8.2
+tqdm>=4.61.2
+youtube-dl
+yt-dlp
diff --git a/semantic_encoding/train.py b/semantic_encoding/train.py
@@ -245,10 +245,7 @@ def validate(validation_dataloader, validation_data, model, criterion, epoch, wr
 
 def main(model_params, train_params):
 
-    if not os.path.isdir(train_params['log_folder']):
-        print('Log folder "{}" does not exist. We are attempting creating it... '.format(train_params['log_folder']))
-        os.mkdir(train_params['log_folder'])
-        print('Folder created!')
+    os.makedirs(train_params['log_folder'], exist_ok=True)
 
     if train_params['model_checkpoint_filename']:
         print('[{}] Loading saved model weights to finetune (or continue training): {}...'.format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), train_params['model_checkpoint_filename']))

diff --git a/semantic_encoding/utils.py b/semantic_encoding/utils.py
@@ -82,10 +82,7 @@ def save_checkpoint(epoch, model, optimizer, word_map, datetimestamp, model_para
              'model_params': model_params,
              'train_params': train_params}
 
-    if not os.path.isdir(train_params['checkpoint_folder']):
-        print('Folder "{}" does not exist. We are attempting creating it... '.format(train_params['checkpoint_folder']))
-        os.mkdir(train_params['checkpoint_folder'])
-        print('Folder created!')
+    os.makedirs(train_params['checkpoint_folder'], exist_ok=True)
 
     if train_params['model_checkpoint_filename']:
         filename = '{}/{}_checkpoint_lr{}_{}eps{}{}_{}_{}_ft{}.pth'.format(train_params['checkpoint_folder'], datetimestamp, train_params['learning_rate'], train_params['num_epochs'], '_w-att' if model_params['use_word_level_attention'] else '', '_s-att' if model_params['use_sentence_level_attention'] else '', train_params['hostname'], train_params['username'], train_params['model_checkpoint_filename'].split('/')[-1].split('.')[0])