add api example, why deleted?

api_example/demo.py

@@ -0,0 +1,47 @@
+"""
+Copyright $today.year LY Corporation
+
+LY Corporation licenses this file to you under the Apache License,
+version 2.0 (the "License"); you may not use this file except in compliance
+with the License. You may obtain a copy of the License at:
+
+  https://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
+WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
+License for the specific language governing permissions and limitations
+under the License.
+"""
+import os
+import subprocess
+import torch
+
+from lighthouse.models import CGDETRPredictor
+from typing import Dict, List, Optional
+
+def load_weights(weight_dir: str) -> None:
+    if not os.path.exists(os.path.join(weight_dir, 'clip_slowfast_pann_cg_detr_qvhighlight.ckpt')):  
+        command = 'wget -P gradio_demo/weights/ https://zenodo.org/records/13960580/files/clip_slowfast_pann_cg_detr_qvhighlight.ckpt'
+        subprocess.run(command, shell=True)
+
+    if not os.path.exists('SLOWFAST_8x8_R50.pkl'):
+        subprocess.run('wget https://dl.fbaipublicfiles.com/pyslowfast/model_zoo/kinetics400/SLOWFAST_8x8_R50.pkl', shell=True)
+
+    if not os.path.exists('Cnn14_mAP=0.431.pth'):
+        subprocess.run('wget https://zenodo.org/record/3987831/files/Cnn14_mAP%3D0.431.pth', shell=True)
+
+# use GPU if available
+device: str = 'cpu'
+weight_dir: str = 'gradio_demo/weights'
+weight_path: str = os.path.join(weight_dir, 'clip_slowfast_cg_detr_qvhighlight.ckpt')
+model: CGDETRPredictor = CGDETRPredictor(weight_path, device=device, feature_name='clip_slowfast', 
+                                         slowfast_path='SLOWFAST_8x8_R50.pkl', pann_path=None)
+
+# encode video features
+model.encode_video('api_example/RoripwjYFp8_60.0_210.0.mp4')
+
+# moment retrieval & highlight detection
+query: str = 'A woman wearing a glass is speaking in front of the camera'
+prediction: Optional[Dict[str, List[float]]] = model.predict(query)
+print(prediction)

gradio_demo/demo.py

@@ -37,7 +37,7 @@ def load_pretrained_weights():
     for model_name in MODEL_NAMES:
         for feature in FEATURES:
             file_urls.append(
-                "https://zenodo.org/records/13639198/files/{}_{}_qvhighlight.ckpt".format(feature, model_name)
+                "https://zenodo.org/records/13960580/files/{}_{}_qvhighlight.ckpt".format(feature, model_name)
             )
     for file_url in tqdm(file_urls):
         if not os.path.exists('gradio_demo/weights/' + os.path.basename(file_url)):